artificial intelligence long essay

Artificial Intelligence Essay for Students and Children

500+ words essay on artificial intelligence.

Artificial Intelligence refers to the intelligence of machines. This is in contrast to the natural intelligence of humans and animals. With Artificial Intelligence, machines perform functions such as learning, planning, reasoning and problem-solving. Most noteworthy, Artificial Intelligence is the simulation of human intelligence by machines. It is probably the fastest-growing development in the World of technology and innovation . Furthermore, many experts believe AI could solve major challenges and crisis situations.

Types of Artificial Intelligence

First of all, the categorization of Artificial Intelligence is into four types. Arend Hintze came up with this categorization. The categories are as follows:

Type 1: Reactive machines – These machines can react to situations. A famous example can be Deep Blue, the IBM chess program. Most noteworthy, the chess program won against Garry Kasparov , the popular chess legend. Furthermore, such machines lack memory. These machines certainly cannot use past experiences to inform future ones. It analyses all possible alternatives and chooses the best one.

Type 2: Limited memory – These AI systems are capable of using past experiences to inform future ones. A good example can be self-driving cars. Such cars have decision making systems . The car makes actions like changing lanes. Most noteworthy, these actions come from observations. There is no permanent storage of these observations.

Type 3: Theory of mind – This refers to understand others. Above all, this means to understand that others have their beliefs, intentions, desires, and opinions. However, this type of AI does not exist yet.

Type 4: Self-awareness – This is the highest and most sophisticated level of Artificial Intelligence. Such systems have a sense of self. Furthermore, they have awareness, consciousness, and emotions. Obviously, such type of technology does not yet exist. This technology would certainly be a revolution .

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Applications of Artificial Intelligence

First of all, AI has significant use in healthcare. Companies are trying to develop technologies for quick diagnosis. Artificial Intelligence would efficiently operate on patients without human supervision. Such technological surgeries are already taking place. Another excellent healthcare technology is IBM Watson.

Artificial Intelligence in business would significantly save time and effort. There is an application of robotic automation to human business tasks. Furthermore, Machine learning algorithms help in better serving customers. Chatbots provide immediate response and service to customers.

AI can greatly increase the rate of work in manufacturing. Manufacture of a huge number of products can take place with AI. Furthermore, the entire production process can take place without human intervention. Hence, a lot of time and effort is saved.

Artificial Intelligence has applications in various other fields. These fields can be military , law , video games , government, finance, automotive, audit, art, etc. Hence, it’s clear that AI has a massive amount of different applications.

To sum it up, Artificial Intelligence looks all set to be the future of the World. Experts believe AI would certainly become a part and parcel of human life soon. AI would completely change the way we view our World. With Artificial Intelligence, the future seems intriguing and exciting.

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Artificial Intelligence Essay

500+ words essay on artificial intelligence.

Artificial intelligence (AI) has come into our daily lives through mobile devices and the Internet. Governments and businesses are increasingly making use of AI tools and techniques to solve business problems and improve many business processes, especially online ones. Such developments bring about new realities to social life that may not have been experienced before. This essay on Artificial Intelligence will help students to know the various advantages of using AI and how it has made our lives easier and simpler. Also, in the end, we have described the future scope of AI and the harmful effects of using it. To get a good command of essay writing, students must practise CBSE Essays on different topics.

Artificial Intelligence is the science and engineering of making intelligent machines, especially intelligent computer programs. It is concerned with getting computers to do tasks that would normally require human intelligence. AI systems are basically software systems (or controllers for robots) that use techniques such as machine learning and deep learning to solve problems in particular domains without hard coding all possibilities (i.e. algorithmic steps) in software. Due to this, AI started showing promising solutions for industry and businesses as well as our daily lives.

Importance and Advantages of Artificial Intelligence

Advances in computing and digital technologies have a direct influence on our lives, businesses and social life. This has influenced our daily routines, such as using mobile devices and active involvement on social media. AI systems are the most influential digital technologies. With AI systems, businesses are able to handle large data sets and provide speedy essential input to operations. Moreover, businesses are able to adapt to constant changes and are becoming more flexible.

By introducing Artificial Intelligence systems into devices, new business processes are opting for the automated process. A new paradigm emerges as a result of such intelligent automation, which now dictates not only how businesses operate but also who does the job. Many manufacturing sites can now operate fully automated with robots and without any human workers. Artificial Intelligence now brings unheard and unexpected innovations to the business world that many organizations will need to integrate to remain competitive and move further to lead the competitors.

Artificial Intelligence shapes our lives and social interactions through technological advancement. There are many AI applications which are specifically developed for providing better services to individuals, such as mobile phones, electronic gadgets, social media platforms etc. We are delegating our activities through intelligent applications, such as personal assistants, intelligent wearable devices and other applications. AI systems that operate household apparatus help us at home with cooking or cleaning.

Future Scope of Artificial Intelligence

In the future, intelligent machines will replace or enhance human capabilities in many areas. Artificial intelligence is becoming a popular field in computer science as it has enhanced humans. Application areas of artificial intelligence are having a huge impact on various fields of life to solve complex problems in various areas such as education, engineering, business, medicine, weather forecasting etc. Many labourers’ work can be done by a single machine. But Artificial Intelligence has another aspect: it can be dangerous for us. If we become completely dependent on machines, then it can ruin our life. We will not be able to do any work by ourselves and get lazy. Another disadvantage is that it cannot give a human-like feeling. So machines should be used only where they are actually required.

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Essay On Artificial Intelligence in English (100,150, 200, 250, 300, 500 Words)

Essay on Artificial Intelligence

Artificial Intelligence is also known as the intelligence of machines. This is in contrast to the natural intelligence of humans. With Artificial Intelligence, machines can perform functions like learning, planning, reasoning and problem-solving. Most important, Artificial Intelligence i.e AI is the simulation of human intelligence by machines. It is probably the fastest-growing development in the World of technology and innovation till now. Moreover, many technical experts believe AI could solve major challenges and crisis situations.

Our life in this modern age totally depends largely on computers. It is impossible to think about our life without computers. We need computers in everything that we use in our day to day life. So it becomes very important to make computers intelligent so that our lives become very easy. Artificial Intelligence or AI is the theory and development of computers, which imitates the human intelligence and senses, such as visual perception, speech recognition, decision-making, and translation of languages. AI has brought a revolution in the world of technology. 

Why is the Essay on Artificial Intelligence Important For Your Exams? 

An essay on Artificial Intelligence (AI) is crucial for exams because it demonstrates an understanding of a rapidly evolving and impactful field. It showcases awareness of AI's applications, ethical considerations, and societal implications, reflecting a well-rounded comprehension of contemporary technological advancements. Additionally, such essays often assess critical thinking and analytical skills, essential for evaluating the multifaceted aspects of AI. Overall, tackling this topic in exams enhances your ability to articulate informed opinions on complex issues, a valuable skill in various academic and professional contexts.

An essay on artificial intelligence demonstrates your grasp of fundamental concepts, showcasing your knowledge of AI's principles, applications, and impact. Crafting such an essay hones your ability to analyze complex topics, fostering critical thinking as you explore the implications, benefits, and challenges of AI. 

AI is increasingly integral to various fields. An essay on this topic highlights its relevance in addressing current societal, economic, and technological challenges. AI's global impact makes it a noteworthy subject. Demonstrating an understanding of its implications helps you connect your knowledge to broader global trends and issues.

Essay on Artificial Intelligence (100 words)

Artificial intelligence or AI is known as machine intelligence. It basically refers to the ability of machines to imitate human intelligence. Machines are now capable of learning, planning, thinking, and problem-solving, all thanks to artificial intelligence. The most notable aspect of artificial intelligence is how robots duplicate human intellect. It is one of the fastest-growing developments in the world of technology. AI is a technology that is transforming every day to day life. Today, artificial intelligence is being used more and more in practically every industry and our daily lives. While technology has improved and eased our lives, it has also put many employment at risk.

Essay on Artificial Intelligence (150 words)

Artificial Intelligence, or AI, is like teaching computers to be really smart. It's like magic that makes machines think and learn. AI is everywhere – in games, phones, and even some toys! It helps us by understanding what we say and do. Imagine having a friend in our computers! But, we must be careful and use AI nicely. It's important to share and be good to others. AI can do amazing things, like talking to us or helping with homework. So, let's be happy with our smart machines, always be kind, and remember that technology is here to make our lives fun and easier!

If we observe, many aspects of our day-to-day lives now involve the use of artificial intelligence, for instance, face ID and image recognition features in mobile phones, emails, various apps, digital voice assistants like Apple’s Siri and Amazon’s Alexa, Google search, route mapping, traffic updates, weather updates, Netflix and Amazon for entertainment, etc.

Essay on Artificial Intelligence (200 words)

Artificial Intelligence, or AI, is like a clever robot that can think and learn on its own. It's like having a smart friend made of computer programs. AI helps machines do things that normally need human brains, like solving problems or understanding pictures.

Imagine your AI friend is good at puzzles. If you show it different puzzles, it learns how to solve them by itself. That's AI learning! It's like when you practice math problems to get better.

AI also helps in games. Have you played a game where the computer acts like a player? That's AI making the game more interesting!

Another cool thing about AI is talking to it. Have you ever asked a question to a voice assistant? That's AI too! It can answer questions and even tell jokes.

But, just like with our friends, we need to teach AI the right things. We want it to be helpful and kind. People work hard to make sure AI helps us in good ways.

In the future, AI might help us even more, like in medicine or exploring space. So, AI is like a smart buddy, learning, helping, and making things exciting!

Essay on Artificial Intelligence (250 words)

Artificial intelligence was developed around 1950 by John McCarthy who is considered as the “Father of artificial intelligence” as he first coined the term. The development of gadgets or machines that can mimic human intelligence, including abilities such as voice recognition, decision-making, and language translation, is known as artificial intelligence. Making computers understand like humans, think like humans, and also act like humans is done by instilling data as instructions and inputs to the machine.

Taking Over Industry

The need for human help is reduced as AI has taken over many parts of the industry, which may result in concerns with unemployment in many occupations. However, the degree of control the human species chooses to give technology will always be up to humans species. As is well said, technology works best when it unites people.

AI In Everyday Life

Advancement in technology has a direct influence on humans' lives, businesses and social life. Whether or not we purposefully realize it, AI has begun to penetrate the different aspects of our everyday lives. If we observe, many feature of our everyday lives now involve the use of artificial intelligence, for instance, face ID and image recognition features in mobile phones, emails, various apps, digital voice assistants like Apple’s Siri and Amazon’s Alexa, Google search, route mapping, traffic updates, weather updates, Netflix and Amazon for entertainment, etc.

Essay on Artificial Intelligence (300 words)

Artificial Intelligence (AI) is a rapidly evolving field that has garnered immense attention and significance in recent years. At its core, AI refers to the development of computer systems capable of performing tasks that typically require human intelligence. This encompasses a broad spectrum of activities, from speech recognition and problem-solving to learning and decision-making.

One of the key facets of AI is machine learning, where systems are designed to learn and improve from experience. This ability allows AI to adapt to new data and patterns, making it exceptionally versatile. Machine learning is employed in various applications, such as image and speech recognition, recommendation systems, and autonomous vehicles.

The impact of AI extends across diverse industries, enhancing efficiency and innovation. In healthcare, AI aids in diagnostics, drug discovery, and personalized treatment plans. In finance, it optimizes trading strategies and detects fraudulent activities. Moreover, AI contributes to the development of smart cities, where it manages traffic, energy consumption, and public services.

However, the rise of AI also raises ethical considerations and challenges. Concerns regarding job displacement due to automation have surfaced, prompting discussions on the need for workforce adaptation. Additionally, ethical dilemmas related to data privacy, bias in algorithms, and the potential misuse of AI technology demand careful scrutiny and regulation.

Looking ahead, the future of AI holds both promise and responsibility. As the technology advances, it is crucial to strike a balance between innovation and ethical considerations. Striving for transparency, accountability, and inclusive development will be essential in ensuring the responsible deployment of AI for the benefit of society.

In conclusion, Artificial Intelligence represents a transformative force with far-reaching implications. Its application spans various sectors, revolutionizing the way we work and live. As we navigate this AI-driven era, a thoughtful and ethical approach will be pivotal in harnessing its potential for the greater good.

Essay on Artificial Intelligence (400 words)

Introduction 

As per the famous Daniel Bell, “Technology, like art, is the soaring exercise of human imagination.” It is also most difficult to imagine the world today without the internet and cellphones, but this has not always been the case. It has almost taken 30 years and four industrial revolutions to reach the world we live in today! Modern technology has become so advanced that it is on the brink of replacing human activities and human emotions. One such advanced form of technology includes AI or machine learning.

What is Artificial Intelligence ?

Artificial Intelligence is a part of technology that can process information and make decisions without human supervision. Researchers have been working hard on the technology for a very long time, and they still have a long road ahead of them, but AI has now become an integral part of our everyday lives. Many useful characteristics such as navigation apps, video suggestions, facial recognition, and smart assistants are a by-product of artificial intelligence.

Classifications of Artificial Intelligence 

According to researchers, there are four broad classifications of AI. The first includes ‘Reactive Machine’ where these machines do not have any memory storage capacity but can process information and make situation-based decisions. These machine learning devices use algorithms and are frequently used in gaming software such as chess and ludo. It is very easy for such programs to think of a million permutations and combinations  and reach the most suitable results. Some of the gaming software based on AI is so advanced that even the champions of the field have to take a bow in front of these programmes.

The second type of AI is called ‘Limited Memory’ technology and has taken the entire world by storm. Not only can such devices take situation-based decisions, but they also store previously analyzed data for future use. A good example of ‘limited memory’ technology is the video recommendation system on any video streaming platform like YouTube. Once the AI figures out the likes and dislikes of the user, it can make decisions on the user’s behalf and recommend shows and videos as per the user's interest. The ‘limited memory’ technology has become an easy way to influence and manipulate the data in masses as they use the thought process of the person himself. Although this is a revolutionary feat, it has also made people more vulnerable and prone to wasteful online shopping and other unusual activities.

The third type of AI, which has not seen much progress yet, includes ‘Theory of Mind.’ The idea is to develop a technology that can store and process data and have a human-like thought process that will allow the machine to make important decisions during a crisis. Scientists are working continuously on this project and have come up with some humanoid robots, but the results have not been good enough to replace human work and services. However, we can hope in the future to have a lot of robots doing our work.

The fourth type of AI is the ‘Self-awareness’ program which seems almost unachievable at this time. It refers to the knowledge of identifying oneself from given surroundings. A machine that would be self-aware would have its own emotions and its own thought process. If someday in the future, science is able to evolve to create ‘self-aware’ machines, the human race could achieve immortality. And although this idea sounds difficult to believe, it has its supporters in many advanced scientists such as Stephen Hawking and Albert Einstein. These scientists believed that it was possible to store and replicate human consciousness.

Conclusion 

AI has indeed made the world smaller and life more achievable. The distance that would take months to travel, a year ago, now can be traversed in a matter of a few hours. There is no place on Earth that humans cannot reach. AI has helped increase the duration of the entire human population by making health facilities cheaper and more accessible. But like every coin has two faces, AI technology has its pros and cons. We have become so addicted to our devices like mobile games, Alexa and many more that we’ve replaced them for physical human interaction. Not only is AI taking away from our social life, but it is also increasing health issues. Weaken eyesight, obesity, and cardiovascular issues are just common diseases resulting from the continuous use of technology sitting in one place. Thus, we must be reasonable with using any sort of technology.

Question 1. What is Artificial Intelligence?

Answer: Artificial Intelligence is a part of computer science that emphasizes the development of intelligent machines that would think and work like.

Question 2 : Can Artificial Intelligence help us?

Answer: Artificial Intelligence or AI can help us in many ways. It is already helping us in some cases. For example, if we think about the robots used in a factory, these robots run on the principle of Artificial Intelligence. In the automobile sector, some vehicles have been invented that don't need any humans to drive them, they are self-driving such as Tesla. The search engines like google and yahoo these days are also AI-powered. 

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How artificial intelligence is transforming the world

Subscribe to the center for technology innovation newsletter, darrell m. west and darrell m. west senior fellow - center for technology innovation , douglas dillon chair in governmental studies john r. allen john r. allen.

April 24, 2018

Artificial intelligence (AI) is a wide-ranging tool that enables people to rethink how we integrate information, analyze data, and use the resulting insights to improve decision making—and already it is transforming every walk of life. In this report, Darrell West and John Allen discuss AI’s application across a variety of sectors, address issues in its development, and offer recommendations for getting the most out of AI while still protecting important human values.

Table of Contents I. Qualities of artificial intelligence II. Applications in diverse sectors III. Policy, regulatory, and ethical issues IV. Recommendations V. Conclusion

• 49 min read

Most people are not very familiar with the concept of artificial intelligence (AI). As an illustration, when 1,500 senior business leaders in the United States in 2017 were asked about AI, only 17 percent said they were familiar with it. 1 A number of them were not sure what it was or how it would affect their particular companies. They understood there was considerable potential for altering business processes, but were not clear how AI could be deployed within their own organizations.

Despite its widespread lack of familiarity, AI is a technology that is transforming every walk of life. It is a wide-ranging tool that enables people to rethink how we integrate information, analyze data, and use the resulting insights to improve decisionmaking. Our hope through this comprehensive overview is to explain AI to an audience of policymakers, opinion leaders, and interested observers, and demonstrate how AI already is altering the world and raising important questions for society, the economy, and governance.

In this paper, we discuss novel applications in finance, national security, health care, criminal justice, transportation, and smart cities, and address issues such as data access problems, algorithmic bias, AI ethics and transparency, and legal liability for AI decisions. We contrast the regulatory approaches of the U.S. and European Union, and close by making a number of recommendations for getting the most out of AI while still protecting important human values. 2

In order to maximize AI benefits, we recommend nine steps for going forward:

• Encourage greater data access for researchers without compromising users’ personal privacy,
• invest more government funding in unclassified AI research,
• promote new models of digital education and AI workforce development so employees have the skills needed in the 21 st -century economy,
• create a federal AI advisory committee to make policy recommendations,
• engage with state and local officials so they enact effective policies,
• regulate broad AI principles rather than specific algorithms,
• take bias complaints seriously so AI does not replicate historic injustice, unfairness, or discrimination in data or algorithms,
• maintain mechanisms for human oversight and control, and
• penalize malicious AI behavior and promote cybersecurity.

Qualities of artificial intelligence

Although there is no uniformly agreed upon definition, AI generally is thought to refer to “machines that respond to stimulation consistent with traditional responses from humans, given the human capacity for contemplation, judgment and intention.” 3  According to researchers Shubhendu and Vijay, these software systems “make decisions which normally require [a] human level of expertise” and help people anticipate problems or deal with issues as they come up. 4 As such, they operate in an intentional, intelligent, and adaptive manner.

Intentionality

Artificial intelligence algorithms are designed to make decisions, often using real-time data. They are unlike passive machines that are capable only of mechanical or predetermined responses. Using sensors, digital data, or remote inputs, they combine information from a variety of different sources, analyze the material instantly, and act on the insights derived from those data. With massive improvements in storage systems, processing speeds, and analytic techniques, they are capable of tremendous sophistication in analysis and decisionmaking.

Artificial intelligence is already altering the world and raising important questions for society, the economy, and governance.

Intelligence

AI generally is undertaken in conjunction with machine learning and data analytics. 5 Machine learning takes data and looks for underlying trends. If it spots something that is relevant for a practical problem, software designers can take that knowledge and use it to analyze specific issues. All that is required are data that are sufficiently robust that algorithms can discern useful patterns. Data can come in the form of digital information, satellite imagery, visual information, text, or unstructured data.

Adaptability

AI systems have the ability to learn and adapt as they make decisions. In the transportation area, for example, semi-autonomous vehicles have tools that let drivers and vehicles know about upcoming congestion, potholes, highway construction, or other possible traffic impediments. Vehicles can take advantage of the experience of other vehicles on the road, without human involvement, and the entire corpus of their achieved “experience” is immediately and fully transferable to other similarly configured vehicles. Their advanced algorithms, sensors, and cameras incorporate experience in current operations, and use dashboards and visual displays to present information in real time so human drivers are able to make sense of ongoing traffic and vehicular conditions. And in the case of fully autonomous vehicles, advanced systems can completely control the car or truck, and make all the navigational decisions.

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Applications in diverse sectors

AI is not a futuristic vision, but rather something that is here today and being integrated with and deployed into a variety of sectors. This includes fields such as finance, national security, health care, criminal justice, transportation, and smart cities. There are numerous examples where AI already is making an impact on the world and augmenting human capabilities in significant ways. 6

One of the reasons for the growing role of AI is the tremendous opportunities for economic development that it presents. A project undertaken by PriceWaterhouseCoopers estimated that “artificial intelligence technologies could increase global GDP by $15.7 trillion, a full 14%, by 2030.” 7 That includes advances of $7 trillion in China, $3.7 trillion in North America, $1.8 trillion in Northern Europe, $1.2 trillion for Africa and Oceania, $0.9 trillion in the rest of Asia outside of China, $0.7 trillion in Southern Europe, and $0.5 trillion in Latin America. China is making rapid strides because it has set a national goal of investing $150 billion in AI and becoming the global leader in this area by 2030.

Meanwhile, a McKinsey Global Institute study of China found that “AI-led automation can give the Chinese economy a productivity injection that would add 0.8 to 1.4 percentage points to GDP growth annually, depending on the speed of adoption.” 8 Although its authors found that China currently lags the United States and the United Kingdom in AI deployment, the sheer size of its AI market gives that country tremendous opportunities for pilot testing and future development.

Investments in financial AI in the United States tripled between 2013 and 2014 to a total of $12.2 billion. 9 According to observers in that sector, “Decisions about loans are now being made by software that can take into account a variety of finely parsed data about a borrower, rather than just a credit score and a background check.” 10 In addition, there are so-called robo-advisers that “create personalized investment portfolios, obviating the need for stockbrokers and financial advisers.” 11 These advances are designed to take the emotion out of investing and undertake decisions based on analytical considerations, and make these choices in a matter of minutes.

A prominent example of this is taking place in stock exchanges, where high-frequency trading by machines has replaced much of human decisionmaking. People submit buy and sell orders, and computers match them in the blink of an eye without human intervention. Machines can spot trading inefficiencies or market differentials on a very small scale and execute trades that make money according to investor instructions. 12 Powered in some places by advanced computing, these tools have much greater capacities for storing information because of their emphasis not on a zero or a one, but on “quantum bits” that can store multiple values in each location. 13 That dramatically increases storage capacity and decreases processing times.

Fraud detection represents another way AI is helpful in financial systems. It sometimes is difficult to discern fraudulent activities in large organizations, but AI can identify abnormalities, outliers, or deviant cases requiring additional investigation. That helps managers find problems early in the cycle, before they reach dangerous levels. 14

National security

AI plays a substantial role in national defense. Through its Project Maven, the American military is deploying AI “to sift through the massive troves of data and video captured by surveillance and then alert human analysts of patterns or when there is abnormal or suspicious activity.” 15 According to Deputy Secretary of Defense Patrick Shanahan, the goal of emerging technologies in this area is “to meet our warfighters’ needs and to increase [the] speed and agility [of] technology development and procurement.” 16

Artificial intelligence will accelerate the traditional process of warfare so rapidly that a new term has been coined: hyperwar.

The big data analytics associated with AI will profoundly affect intelligence analysis, as massive amounts of data are sifted in near real time—if not eventually in real time—thereby providing commanders and their staffs a level of intelligence analysis and productivity heretofore unseen. Command and control will similarly be affected as human commanders delegate certain routine, and in special circumstances, key decisions to AI platforms, reducing dramatically the time associated with the decision and subsequent action. In the end, warfare is a time competitive process, where the side able to decide the fastest and move most quickly to execution will generally prevail. Indeed, artificially intelligent intelligence systems, tied to AI-assisted command and control systems, can move decision support and decisionmaking to a speed vastly superior to the speeds of the traditional means of waging war. So fast will be this process, especially if coupled to automatic decisions to launch artificially intelligent autonomous weapons systems capable of lethal outcomes, that a new term has been coined specifically to embrace the speed at which war will be waged: hyperwar.

While the ethical and legal debate is raging over whether America will ever wage war with artificially intelligent autonomous lethal systems, the Chinese and Russians are not nearly so mired in this debate, and we should anticipate our need to defend against these systems operating at hyperwar speeds. The challenge in the West of where to position “humans in the loop” in a hyperwar scenario will ultimately dictate the West’s capacity to be competitive in this new form of conflict. 17

Just as AI will profoundly affect the speed of warfare, the proliferation of zero day or zero second cyber threats as well as polymorphic malware will challenge even the most sophisticated signature-based cyber protection. This forces significant improvement to existing cyber defenses. Increasingly, vulnerable systems are migrating, and will need to shift to a layered approach to cybersecurity with cloud-based, cognitive AI platforms. This approach moves the community toward a “thinking” defensive capability that can defend networks through constant training on known threats. This capability includes DNA-level analysis of heretofore unknown code, with the possibility of recognizing and stopping inbound malicious code by recognizing a string component of the file. This is how certain key U.S.-based systems stopped the debilitating “WannaCry” and “Petya” viruses.

Preparing for hyperwar and defending critical cyber networks must become a high priority because China, Russia, North Korea, and other countries are putting substantial resources into AI. In 2017, China’s State Council issued a plan for the country to “build a domestic industry worth almost $150 billion” by 2030. 18 As an example of the possibilities, the Chinese search firm Baidu has pioneered a facial recognition application that finds missing people. In addition, cities such as Shenzhen are providing up to $1 million to support AI labs. That country hopes AI will provide security, combat terrorism, and improve speech recognition programs. 19 The dual-use nature of many AI algorithms will mean AI research focused on one sector of society can be rapidly modified for use in the security sector as well. 20

Health care

AI tools are helping designers improve computational sophistication in health care. For example, Merantix is a German company that applies deep learning to medical issues. It has an application in medical imaging that “detects lymph nodes in the human body in Computer Tomography (CT) images.” 21 According to its developers, the key is labeling the nodes and identifying small lesions or growths that could be problematic. Humans can do this, but radiologists charge $100 per hour and may be able to carefully read only four images an hour. If there were 10,000 images, the cost of this process would be $250,000, which is prohibitively expensive if done by humans.

What deep learning can do in this situation is train computers on data sets to learn what a normal-looking versus an irregular-appearing lymph node is. After doing that through imaging exercises and honing the accuracy of the labeling, radiological imaging specialists can apply this knowledge to actual patients and determine the extent to which someone is at risk of cancerous lymph nodes. Since only a few are likely to test positive, it is a matter of identifying the unhealthy versus healthy node.

AI has been applied to congestive heart failure as well, an illness that afflicts 10 percent of senior citizens and costs $35 billion each year in the United States. AI tools are helpful because they “predict in advance potential challenges ahead and allocate resources to patient education, sensing, and proactive interventions that keep patients out of the hospital.” 22

Criminal justice

AI is being deployed in the criminal justice area. The city of Chicago has developed an AI-driven “Strategic Subject List” that analyzes people who have been arrested for their risk of becoming future perpetrators. It ranks 400,000 people on a scale of 0 to 500, using items such as age, criminal activity, victimization, drug arrest records, and gang affiliation. In looking at the data, analysts found that youth is a strong predictor of violence, being a shooting victim is associated with becoming a future perpetrator, gang affiliation has little predictive value, and drug arrests are not significantly associated with future criminal activity. 23

Judicial experts claim AI programs reduce human bias in law enforcement and leads to a fairer sentencing system. R Street Institute Associate Caleb Watney writes:

Empirically grounded questions of predictive risk analysis play to the strengths of machine learning, automated reasoning and other forms of AI. One machine-learning policy simulation concluded that such programs could be used to cut crime up to 24.8 percent with no change in jailing rates, or reduce jail populations by up to 42 percent with no increase in crime rates. 24

However, critics worry that AI algorithms represent “a secret system to punish citizens for crimes they haven’t yet committed. The risk scores have been used numerous times to guide large-scale roundups.” 25 The fear is that such tools target people of color unfairly and have not helped Chicago reduce the murder wave that has plagued it in recent years.

Despite these concerns, other countries are moving ahead with rapid deployment in this area. In China, for example, companies already have “considerable resources and access to voices, faces and other biometric data in vast quantities, which would help them develop their technologies.” 26 New technologies make it possible to match images and voices with other types of information, and to use AI on these combined data sets to improve law enforcement and national security. Through its “Sharp Eyes” program, Chinese law enforcement is matching video images, social media activity, online purchases, travel records, and personal identity into a “police cloud.” This integrated database enables authorities to keep track of criminals, potential law-breakers, and terrorists. 27 Put differently, China has become the world’s leading AI-powered surveillance state.

Transportation

Transportation represents an area where AI and machine learning are producing major innovations. Research by Cameron Kerry and Jack Karsten of the Brookings Institution has found that over $80 billion was invested in autonomous vehicle technology between August 2014 and June 2017. Those investments include applications both for autonomous driving and the core technologies vital to that sector. 28

Autonomous vehicles—cars, trucks, buses, and drone delivery systems—use advanced technological capabilities. Those features include automated vehicle guidance and braking, lane-changing systems, the use of cameras and sensors for collision avoidance, the use of AI to analyze information in real time, and the use of high-performance computing and deep learning systems to adapt to new circumstances through detailed maps. 29

Light detection and ranging systems (LIDARs) and AI are key to navigation and collision avoidance. LIDAR systems combine light and radar instruments. They are mounted on the top of vehicles that use imaging in a 360-degree environment from a radar and light beams to measure the speed and distance of surrounding objects. Along with sensors placed on the front, sides, and back of the vehicle, these instruments provide information that keeps fast-moving cars and trucks in their own lane, helps them avoid other vehicles, applies brakes and steering when needed, and does so instantly so as to avoid accidents.

Advanced software enables cars to learn from the experiences of other vehicles on the road and adjust their guidance systems as weather, driving, or road conditions change. This means that software is the key—not the physical car or truck itself.

Since these cameras and sensors compile a huge amount of information and need to process it instantly to avoid the car in the next lane, autonomous vehicles require high-performance computing, advanced algorithms, and deep learning systems to adapt to new scenarios. This means that software is the key, not the physical car or truck itself. 30 Advanced software enables cars to learn from the experiences of other vehicles on the road and adjust their guidance systems as weather, driving, or road conditions change. 31

Ride-sharing companies are very interested in autonomous vehicles. They see advantages in terms of customer service and labor productivity. All of the major ride-sharing companies are exploring driverless cars. The surge of car-sharing and taxi services—such as Uber and Lyft in the United States, Daimler’s Mytaxi and Hailo service in Great Britain, and Didi Chuxing in China—demonstrate the opportunities of this transportation option. Uber recently signed an agreement to purchase 24,000 autonomous cars from Volvo for its ride-sharing service. 32

However, the ride-sharing firm suffered a setback in March 2018 when one of its autonomous vehicles in Arizona hit and killed a pedestrian. Uber and several auto manufacturers immediately suspended testing and launched investigations into what went wrong and how the fatality could have occurred. 33 Both industry and consumers want reassurance that the technology is safe and able to deliver on its stated promises. Unless there are persuasive answers, this accident could slow AI advancements in the transportation sector.

Smart cities

Metropolitan governments are using AI to improve urban service delivery. For example, according to Kevin Desouza, Rashmi Krishnamurthy, and Gregory Dawson:

The Cincinnati Fire Department is using data analytics to optimize medical emergency responses. The new analytics system recommends to the dispatcher an appropriate response to a medical emergency call—whether a patient can be treated on-site or needs to be taken to the hospital—by taking into account several factors, such as the type of call, location, weather, and similar calls. 34

Since it fields 80,000 requests each year, Cincinnati officials are deploying this technology to prioritize responses and determine the best ways to handle emergencies. They see AI as a way to deal with large volumes of data and figure out efficient ways of responding to public requests. Rather than address service issues in an ad hoc manner, authorities are trying to be proactive in how they provide urban services.

Cincinnati is not alone. A number of metropolitan areas are adopting smart city applications that use AI to improve service delivery, environmental planning, resource management, energy utilization, and crime prevention, among other things. For its smart cities index, the magazine Fast Company ranked American locales and found Seattle, Boston, San Francisco, Washington, D.C., and New York City as the top adopters. Seattle, for example, has embraced sustainability and is using AI to manage energy usage and resource management. Boston has launched a “City Hall To Go” that makes sure underserved communities receive needed public services. It also has deployed “cameras and inductive loops to manage traffic and acoustic sensors to identify gun shots.” San Francisco has certified 203 buildings as meeting LEED sustainability standards. 35

Through these and other means, metropolitan areas are leading the country in the deployment of AI solutions. Indeed, according to a National League of Cities report, 66 percent of American cities are investing in smart city technology. Among the top applications noted in the report are “smart meters for utilities, intelligent traffic signals, e-governance applications, Wi-Fi kiosks, and radio frequency identification sensors in pavement.” 36

Policy, regulatory, and ethical issues

These examples from a variety of sectors demonstrate how AI is transforming many walks of human existence. The increasing penetration of AI and autonomous devices into many aspects of life is altering basic operations and decisionmaking within organizations, and improving efficiency and response times.

At the same time, though, these developments raise important policy, regulatory, and ethical issues. For example, how should we promote data access? How do we guard against biased or unfair data used in algorithms? What types of ethical principles are introduced through software programming, and how transparent should designers be about their choices? What about questions of legal liability in cases where algorithms cause harm? 37

The increasing penetration of AI into many aspects of life is altering decisionmaking within organizations and improving efficiency. At the same time, though, these developments raise important policy, regulatory, and ethical issues.

Data access problems

The key to getting the most out of AI is having a “data-friendly ecosystem with unified standards and cross-platform sharing.” AI depends on data that can be analyzed in real time and brought to bear on concrete problems. Having data that are “accessible for exploration” in the research community is a prerequisite for successful AI development. 38

According to a McKinsey Global Institute study, nations that promote open data sources and data sharing are the ones most likely to see AI advances. In this regard, the United States has a substantial advantage over China. Global ratings on data openness show that U.S. ranks eighth overall in the world, compared to 93 for China. 39

But right now, the United States does not have a coherent national data strategy. There are few protocols for promoting research access or platforms that make it possible to gain new insights from proprietary data. It is not always clear who owns data or how much belongs in the public sphere. These uncertainties limit the innovation economy and act as a drag on academic research. In the following section, we outline ways to improve data access for researchers.

Biases in data and algorithms

In some instances, certain AI systems are thought to have enabled discriminatory or biased practices. 40 For example, Airbnb has been accused of having homeowners on its platform who discriminate against racial minorities. A research project undertaken by the Harvard Business School found that “Airbnb users with distinctly African American names were roughly 16 percent less likely to be accepted as guests than those with distinctly white names.” 41

Racial issues also come up with facial recognition software. Most such systems operate by comparing a person’s face to a range of faces in a large database. As pointed out by Joy Buolamwini of the Algorithmic Justice League, “If your facial recognition data contains mostly Caucasian faces, that’s what your program will learn to recognize.” 42 Unless the databases have access to diverse data, these programs perform poorly when attempting to recognize African-American or Asian-American features.

Many historical data sets reflect traditional values, which may or may not represent the preferences wanted in a current system. As Buolamwini notes, such an approach risks repeating inequities of the past:

The rise of automation and the increased reliance on algorithms for high-stakes decisions such as whether someone get insurance or not, your likelihood to default on a loan or somebody’s risk of recidivism means this is something that needs to be addressed. Even admissions decisions are increasingly automated—what school our children go to and what opportunities they have. We don’t have to bring the structural inequalities of the past into the future we create. 43

AI ethics and transparency

Algorithms embed ethical considerations and value choices into program decisions. As such, these systems raise questions concerning the criteria used in automated decisionmaking. Some people want to have a better understanding of how algorithms function and what choices are being made. 44

In the United States, many urban schools use algorithms for enrollment decisions based on a variety of considerations, such as parent preferences, neighborhood qualities, income level, and demographic background. According to Brookings researcher Jon Valant, the New Orleans–based Bricolage Academy “gives priority to economically disadvantaged applicants for up to 33 percent of available seats. In practice, though, most cities have opted for categories that prioritize siblings of current students, children of school employees, and families that live in school’s broad geographic area.” 45 Enrollment choices can be expected to be very different when considerations of this sort come into play.

Depending on how AI systems are set up, they can facilitate the redlining of mortgage applications, help people discriminate against individuals they don’t like, or help screen or build rosters of individuals based on unfair criteria. The types of considerations that go into programming decisions matter a lot in terms of how the systems operate and how they affect customers. 46

For these reasons, the EU is implementing the General Data Protection Regulation (GDPR) in May 2018. The rules specify that people have “the right to opt out of personally tailored ads” and “can contest ‘legal or similarly significant’ decisions made by algorithms and appeal for human intervention” in the form of an explanation of how the algorithm generated a particular outcome. Each guideline is designed to ensure the protection of personal data and provide individuals with information on how the “black box” operates. 47

Legal liability

There are questions concerning the legal liability of AI systems. If there are harms or infractions (or fatalities in the case of driverless cars), the operators of the algorithm likely will fall under product liability rules. A body of case law has shown that the situation’s facts and circumstances determine liability and influence the kind of penalties that are imposed. Those can range from civil fines to imprisonment for major harms. 48 The Uber-related fatality in Arizona will be an important test case for legal liability. The state actively recruited Uber to test its autonomous vehicles and gave the company considerable latitude in terms of road testing. It remains to be seen if there will be lawsuits in this case and who is sued: the human backup driver, the state of Arizona, the Phoenix suburb where the accident took place, Uber, software developers, or the auto manufacturer. Given the multiple people and organizations involved in the road testing, there are many legal questions to be resolved.

In non-transportation areas, digital platforms often have limited liability for what happens on their sites. For example, in the case of Airbnb, the firm “requires that people agree to waive their right to sue, or to join in any class-action lawsuit or class-action arbitration, to use the service.” By demanding that its users sacrifice basic rights, the company limits consumer protections and therefore curtails the ability of people to fight discrimination arising from unfair algorithms. 49 But whether the principle of neutral networks holds up in many sectors is yet to be determined on a widespread basis.

Recommendations

In order to balance innovation with basic human values, we propose a number of recommendations for moving forward with AI. This includes improving data access, increasing government investment in AI, promoting AI workforce development, creating a federal advisory committee, engaging with state and local officials to ensure they enact effective policies, regulating broad objectives as opposed to specific algorithms, taking bias seriously as an AI issue, maintaining mechanisms for human control and oversight, and penalizing malicious behavior and promoting cybersecurity.

Improving data access

The United States should develop a data strategy that promotes innovation and consumer protection. Right now, there are no uniform standards in terms of data access, data sharing, or data protection. Almost all the data are proprietary in nature and not shared very broadly with the research community, and this limits innovation and system design. AI requires data to test and improve its learning capacity. 50 Without structured and unstructured data sets, it will be nearly impossible to gain the full benefits of artificial intelligence.

In general, the research community needs better access to government and business data, although with appropriate safeguards to make sure researchers do not misuse data in the way Cambridge Analytica did with Facebook information. There is a variety of ways researchers could gain data access. One is through voluntary agreements with companies holding proprietary data. Facebook, for example, recently announced a partnership with Stanford economist Raj Chetty to use its social media data to explore inequality. 51 As part of the arrangement, researchers were required to undergo background checks and could only access data from secured sites in order to protect user privacy and security.

In the U.S., there are no uniform standards in terms of data access, data sharing, or data protection. Almost all the data are proprietary in nature and not shared very broadly with the research community, and this limits innovation and system design.

Google long has made available search results in aggregated form for researchers and the general public. Through its “Trends” site, scholars can analyze topics such as interest in Trump, views about democracy, and perspectives on the overall economy. 52 That helps people track movements in public interest and identify topics that galvanize the general public.

Twitter makes much of its tweets available to researchers through application programming interfaces, commonly referred to as APIs. These tools help people outside the company build application software and make use of data from its social media platform. They can study patterns of social media communications and see how people are commenting on or reacting to current events.

In some sectors where there is a discernible public benefit, governments can facilitate collaboration by building infrastructure that shares data. For example, the National Cancer Institute has pioneered a data-sharing protocol where certified researchers can query health data it has using de-identified information drawn from clinical data, claims information, and drug therapies. That enables researchers to evaluate efficacy and effectiveness, and make recommendations regarding the best medical approaches, without compromising the privacy of individual patients.

There could be public-private data partnerships that combine government and business data sets to improve system performance. For example, cities could integrate information from ride-sharing services with its own material on social service locations, bus lines, mass transit, and highway congestion to improve transportation. That would help metropolitan areas deal with traffic tie-ups and assist in highway and mass transit planning.

Some combination of these approaches would improve data access for researchers, the government, and the business community, without impinging on personal privacy. As noted by Ian Buck, the vice president of NVIDIA, “Data is the fuel that drives the AI engine. The federal government has access to vast sources of information. Opening access to that data will help us get insights that will transform the U.S. economy.” 53 Through its Data.gov portal, the federal government already has put over 230,000 data sets into the public domain, and this has propelled innovation and aided improvements in AI and data analytic technologies. 54 The private sector also needs to facilitate research data access so that society can achieve the full benefits of artificial intelligence.

Increase government investment in AI

According to Greg Brockman, the co-founder of OpenAI, the U.S. federal government invests only $1.1 billion in non-classified AI technology. 55 That is far lower than the amount being spent by China or other leading nations in this area of research. That shortfall is noteworthy because the economic payoffs of AI are substantial. In order to boost economic development and social innovation, federal officials need to increase investment in artificial intelligence and data analytics. Higher investment is likely to pay for itself many times over in economic and social benefits. 56

Promote digital education and workforce development

As AI applications accelerate across many sectors, it is vital that we reimagine our educational institutions for a world where AI will be ubiquitous and students need a different kind of training than they currently receive. Right now, many students do not receive instruction in the kinds of skills that will be needed in an AI-dominated landscape. For example, there currently are shortages of data scientists, computer scientists, engineers, coders, and platform developers. These are skills that are in short supply; unless our educational system generates more people with these capabilities, it will limit AI development.

For these reasons, both state and federal governments have been investing in AI human capital. For example, in 2017, the National Science Foundation funded over 6,500 graduate students in computer-related fields and has launched several new initiatives designed to encourage data and computer science at all levels from pre-K to higher and continuing education. 57 The goal is to build a larger pipeline of AI and data analytic personnel so that the United States can reap the full advantages of the knowledge revolution.

But there also needs to be substantial changes in the process of learning itself. It is not just technical skills that are needed in an AI world but skills of critical reasoning, collaboration, design, visual display of information, and independent thinking, among others. AI will reconfigure how society and the economy operate, and there needs to be “big picture” thinking on what this will mean for ethics, governance, and societal impact. People will need the ability to think broadly about many questions and integrate knowledge from a number of different areas.

One example of new ways to prepare students for a digital future is IBM’s Teacher Advisor program, utilizing Watson’s free online tools to help teachers bring the latest knowledge into the classroom. They enable instructors to develop new lesson plans in STEM and non-STEM fields, find relevant instructional videos, and help students get the most out of the classroom. 58 As such, they are precursors of new educational environments that need to be created.

Create a federal AI advisory committee

Federal officials need to think about how they deal with artificial intelligence. As noted previously, there are many issues ranging from the need for improved data access to addressing issues of bias and discrimination. It is vital that these and other concerns be considered so we gain the full benefits of this emerging technology.

In order to move forward in this area, several members of Congress have introduced the “Future of Artificial Intelligence Act,” a bill designed to establish broad policy and legal principles for AI. It proposes the secretary of commerce create a federal advisory committee on the development and implementation of artificial intelligence. The legislation provides a mechanism for the federal government to get advice on ways to promote a “climate of investment and innovation to ensure the global competitiveness of the United States,” “optimize the development of artificial intelligence to address the potential growth, restructuring, or other changes in the United States workforce,” “support the unbiased development and application of artificial intelligence,” and “protect the privacy rights of individuals.” 59

Among the specific questions the committee is asked to address include the following: competitiveness, workforce impact, education, ethics training, data sharing, international cooperation, accountability, machine learning bias, rural impact, government efficiency, investment climate, job impact, bias, and consumer impact. The committee is directed to submit a report to Congress and the administration 540 days after enactment regarding any legislative or administrative action needed on AI.

This legislation is a step in the right direction, although the field is moving so rapidly that we would recommend shortening the reporting timeline from 540 days to 180 days. Waiting nearly two years for a committee report will certainly result in missed opportunities and a lack of action on important issues. Given rapid advances in the field, having a much quicker turnaround time on the committee analysis would be quite beneficial.

Engage with state and local officials

States and localities also are taking action on AI. For example, the New York City Council unanimously passed a bill that directed the mayor to form a taskforce that would “monitor the fairness and validity of algorithms used by municipal agencies.” 60 The city employs algorithms to “determine if a lower bail will be assigned to an indigent defendant, where firehouses are established, student placement for public schools, assessing teacher performance, identifying Medicaid fraud and determine where crime will happen next.” 61

According to the legislation’s developers, city officials want to know how these algorithms work and make sure there is sufficient AI transparency and accountability. In addition, there is concern regarding the fairness and biases of AI algorithms, so the taskforce has been directed to analyze these issues and make recommendations regarding future usage. It is scheduled to report back to the mayor on a range of AI policy, legal, and regulatory issues by late 2019.

Some observers already are worrying that the taskforce won’t go far enough in holding algorithms accountable. For example, Julia Powles of Cornell Tech and New York University argues that the bill originally required companies to make the AI source code available to the public for inspection, and that there be simulations of its decisionmaking using actual data. After criticism of those provisions, however, former Councilman James Vacca dropped the requirements in favor of a task force studying these issues. He and other city officials were concerned that publication of proprietary information on algorithms would slow innovation and make it difficult to find AI vendors who would work with the city. 62 It remains to be seen how this local task force will balance issues of innovation, privacy, and transparency.

Regulate broad objectives more than specific algorithms

The European Union has taken a restrictive stance on these issues of data collection and analysis. 63 It has rules limiting the ability of companies from collecting data on road conditions and mapping street views. Because many of these countries worry that people’s personal information in unencrypted Wi-Fi networks are swept up in overall data collection, the EU has fined technology firms, demanded copies of data, and placed limits on the material collected. 64 This has made it more difficult for technology companies operating there to develop the high-definition maps required for autonomous vehicles.

The GDPR being implemented in Europe place severe restrictions on the use of artificial intelligence and machine learning. According to published guidelines, “Regulations prohibit any automated decision that ‘significantly affects’ EU citizens. This includes techniques that evaluates a person’s ‘performance at work, economic situation, health, personal preferences, interests, reliability, behavior, location, or movements.’” 65 In addition, these new rules give citizens the right to review how digital services made specific algorithmic choices affecting people.

By taking a restrictive stance on issues of data collection and analysis, the European Union is putting its manufacturers and software designers at a significant disadvantage to the rest of the world.

If interpreted stringently, these rules will make it difficult for European software designers (and American designers who work with European counterparts) to incorporate artificial intelligence and high-definition mapping in autonomous vehicles. Central to navigation in these cars and trucks is tracking location and movements. Without high-definition maps containing geo-coded data and the deep learning that makes use of this information, fully autonomous driving will stagnate in Europe. Through this and other data protection actions, the European Union is putting its manufacturers and software designers at a significant disadvantage to the rest of the world.

It makes more sense to think about the broad objectives desired in AI and enact policies that advance them, as opposed to governments trying to crack open the “black boxes” and see exactly how specific algorithms operate. Regulating individual algorithms will limit innovation and make it difficult for companies to make use of artificial intelligence.

Take biases seriously

Bias and discrimination are serious issues for AI. There already have been a number of cases of unfair treatment linked to historic data, and steps need to be undertaken to make sure that does not become prevalent in artificial intelligence. Existing statutes governing discrimination in the physical economy need to be extended to digital platforms. That will help protect consumers and build confidence in these systems as a whole.

For these advances to be widely adopted, more transparency is needed in how AI systems operate. Andrew Burt of Immuta argues, “The key problem confronting predictive analytics is really transparency. We’re in a world where data science operations are taking on increasingly important tasks, and the only thing holding them back is going to be how well the data scientists who train the models can explain what it is their models are doing.” 66

Maintaining mechanisms for human oversight and control

Some individuals have argued that there needs to be avenues for humans to exercise oversight and control of AI systems. For example, Allen Institute for Artificial Intelligence CEO Oren Etzioni argues there should be rules for regulating these systems. First, he says, AI must be governed by all the laws that already have been developed for human behavior, including regulations concerning “cyberbullying, stock manipulation or terrorist threats,” as well as “entrap[ping] people into committing crimes.” Second, he believes that these systems should disclose they are automated systems and not human beings. Third, he states, “An A.I. system cannot retain or disclose confidential information without explicit approval from the source of that information.” 67 His rationale is that these tools store so much data that people have to be cognizant of the privacy risks posed by AI.

In the same vein, the IEEE Global Initiative has ethical guidelines for AI and autonomous systems. Its experts suggest that these models be programmed with consideration for widely accepted human norms and rules for behavior. AI algorithms need to take into effect the importance of these norms, how norm conflict can be resolved, and ways these systems can be transparent about norm resolution. Software designs should be programmed for “nondeception” and “honesty,” according to ethics experts. When failures occur, there must be mitigation mechanisms to deal with the consequences. In particular, AI must be sensitive to problems such as bias, discrimination, and fairness. 68

A group of machine learning experts claim it is possible to automate ethical decisionmaking. Using the trolley problem as a moral dilemma, they ask the following question: If an autonomous car goes out of control, should it be programmed to kill its own passengers or the pedestrians who are crossing the street? They devised a “voting-based system” that asked 1.3 million people to assess alternative scenarios, summarized the overall choices, and applied the overall perspective of these individuals to a range of vehicular possibilities. That allowed them to automate ethical decisionmaking in AI algorithms, taking public preferences into account. 69 This procedure, of course, does not reduce the tragedy involved in any kind of fatality, such as seen in the Uber case, but it provides a mechanism to help AI developers incorporate ethical considerations in their planning.

Penalize malicious behavior and promote cybersecurity

As with any emerging technology, it is important to discourage malicious treatment designed to trick software or use it for undesirable ends. 70 This is especially important given the dual-use aspects of AI, where the same tool can be used for beneficial or malicious purposes. The malevolent use of AI exposes individuals and organizations to unnecessary risks and undermines the virtues of the emerging technology. This includes behaviors such as hacking, manipulating algorithms, compromising privacy and confidentiality, or stealing identities. Efforts to hijack AI in order to solicit confidential information should be seriously penalized as a way to deter such actions. 71

In a rapidly changing world with many entities having advanced computing capabilities, there needs to be serious attention devoted to cybersecurity. Countries have to be careful to safeguard their own systems and keep other nations from damaging their security. 72 According to the U.S. Department of Homeland Security, a major American bank receives around 11 million calls a week at its service center. In order to protect its telephony from denial of service attacks, it uses a “machine learning-based policy engine [that] blocks more than 120,000 calls per month based on voice firewall policies including harassing callers, robocalls and potential fraudulent calls.” 73 This represents a way in which machine learning can help defend technology systems from malevolent attacks.

To summarize, the world is on the cusp of revolutionizing many sectors through artificial intelligence and data analytics. There already are significant deployments in finance, national security, health care, criminal justice, transportation, and smart cities that have altered decisionmaking, business models, risk mitigation, and system performance. These developments are generating substantial economic and social benefits.

The world is on the cusp of revolutionizing many sectors through artificial intelligence, but the way AI systems are developed need to be better understood due to the major implications these technologies will have for society as a whole.

Yet the manner in which AI systems unfold has major implications for society as a whole. It matters how policy issues are addressed, ethical conflicts are reconciled, legal realities are resolved, and how much transparency is required in AI and data analytic solutions. 74 Human choices about software development affect the way in which decisions are made and the manner in which they are integrated into organizational routines. Exactly how these processes are executed need to be better understood because they will have substantial impact on the general public soon, and for the foreseeable future. AI may well be a revolution in human affairs, and become the single most influential human innovation in history.

Note: We appreciate the research assistance of Grace Gilberg, Jack Karsten, Hillary Schaub, and Kristjan Tomasson on this project.

The Brookings Institution is a nonprofit organization devoted to independent research and policy solutions. Its mission is to conduct high-quality, independent research and, based on that research, to provide innovative, practical recommendations for policymakers and the public. The conclusions and recommendations of any Brookings publication are solely those of its author(s), and do not reflect the views of the Institution, its management, or its other scholars.

Support for this publication was generously provided by Amazon. Brookings recognizes that the value it provides is in its absolute commitment to quality, independence, and impact. Activities supported by its donors reflect this commitment. 

John R. Allen is a member of the Board of Advisors of Amida Technology and on the Board of Directors of Spark Cognition. Both companies work in fields discussed in this piece.

• Thomas Davenport, Jeff Loucks, and David Schatsky, “Bullish on the Business Value of Cognitive” (Deloitte, 2017), p. 3 (www2.deloitte.com/us/en/pages/deloitte-analytics/articles/cognitive-technology-adoption-survey.html).
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• Shubhendu and Vijay, “Applicability of Artificial Intelligence in Different Fields of Life.”
• Andrew McAfee and Erik Brynjolfsson, Machine Platform Crowd: Harnessing Our Digital Future (New York: Norton, 2017).
• Portions of this paper draw on Darrell M. West, The Future of Work: Robots, AI, and Automation , Brookings Institution Press, 2018.
• PriceWaterhouseCoopers, “Sizing the Prize: What’s the Real Value of AI for Your Business and How Can You Capitalise?” 2017.
• Dominic Barton, Jonathan Woetzel, Jeongmin Seong, and Qinzheng Tian, “Artificial Intelligence: Implications for China” (New York: McKinsey Global Institute, April 2017), p. 1.
• Nathaniel Popper, “Stocks and Bots,” New York Times Magazine , February 28, 2016.
• Michael Lewis, Flash Boys: A Wall Street Revolt (New York: Norton, 2015).
• Cade Metz, “In Quantum Computing Race, Yale Professors Battle Tech Giants,” New York Times , November 14, 2017, p. B3.
• Executive Office of the President, “Artificial Intelligence, Automation, and the Economy,” December 2016, pp. 27-28.
• Christian Davenport, “Future Wars May Depend as Much on Algorithms as on Ammunition, Report Says,” Washington Post , December 3, 2017.
• John R. Allen and Amir Husain, “On Hyperwar,” Naval Institute Proceedings , July 17, 2017, pp. 30-36.
• Paul Mozur, “China Sets Goal to Lead in Artificial Intelligence,” New York Times , July 21, 2017, p. B1.
• Paul Mozur and John Markoff, “Is China Outsmarting American Artificial Intelligence?” New York Times , May 28, 2017.
• Economist , “America v China: The Battle for Digital Supremacy,” March 15, 2018.
• Rasmus Rothe, “Applying Deep Learning to Real-World Problems,” Medium , May 23, 2017.
• Eric Horvitz, “Reflections on the Status and Future of Artificial Intelligence,” Testimony before the U.S. Senate Subcommittee on Space, Science, and Competitiveness, November 30, 2016, p. 5.
• Jeff Asher and Rob Arthur, “Inside the Algorithm That Tries to Predict Gun Violence in Chicago,” New York Times Upshot , June 13, 2017.
• Caleb Watney, “It’s Time for our Justice System to Embrace Artificial Intelligence,” TechTank (blog), Brookings Institution, July 20, 2017.
• Asher and Arthur, “Inside the Algorithm That Tries to Predict Gun Violence in Chicago.”
• Paul Mozur and Keith Bradsher, “China’s A.I. Advances Help Its Tech Industry, and State Security,” New York Times , December 3, 2017.
• Simon Denyer, “China’s Watchful Eye,” Washington Post , January 7, 2018.
• Cameron Kerry and Jack Karsten, “Gauging Investment in Self-Driving Cars,” Brookings Institution, October 16, 2017.
• Portions of this section are drawn from Darrell M. West, “Driverless Cars in China, Europe, Japan, Korea, and the United States,” Brookings Institution, September 2016.
• Yuming Ge, Xiaoman Liu, Libo Tang, and Darrell M. West, “Smart Transportation in China and the United States,” Center for Technology Innovation, Brookings Institution, December 2017.
• Peter Holley, “Uber Signs Deal to Buy 24,000 Autonomous Vehicles from Volvo,” Washington Post , November 20, 2017.
• Daisuke Wakabayashi, “Self-Driving Uber Car Kills Pedestrian in Arizona, Where Robots Roam,” New York Times , March 19, 2018.
• Kevin Desouza, Rashmi Krishnamurthy, and Gregory Dawson, “Learning from Public Sector Experimentation with Artificial Intelligence,” TechTank (blog), Brookings Institution, June 23, 2017.
• Boyd Cohen, “The 10 Smartest Cities in North America,” Fast Company , November 14, 2013.
• Teena Maddox, “66% of US Cities Are Investing in Smart City Technology,” TechRepublic , November 6, 2017.
• Osonde Osoba and William Welser IV, “The Risks of Artificial Intelligence to Security and the Future of Work” (Santa Monica, Calif.: RAND Corp., December 2017) (www.rand.org/pubs/perspectives/PE237.html).
• Ibid., p. 7.
• Dominic Barton, Jonathan Woetzel, Jeongmin Seong, and Qinzheng Tian, “Artificial Intelligence: Implications for China” (New York: McKinsey Global Institute, April 2017), p. 7.
• Executive Office of the President, “Preparing for the Future of Artificial Intelligence,” October 2016, pp. 30-31.
• Elaine Glusac, “As Airbnb Grows, So Do Claims of Discrimination,” New York Times , June 21, 2016.
• “Joy Buolamwini,” Bloomberg Businessweek , July 3, 2017, p. 80.
• Mark Purdy and Paul Daugherty, “Why Artificial Intelligence is the Future of Growth,” Accenture, 2016.
• Jon Valant, “Integrating Charter Schools and Choice-Based Education Systems,” Brown Center Chalkboard blog, Brookings Institution, June 23, 2017.
• Tucker, “‘A White Mask Worked Better.’”
• Cliff Kuang, “Can A.I. Be Taught to Explain Itself?” New York Times Magazine , November 21, 2017.
• Yale Law School Information Society Project, “Governing Machine Learning,” September 2017.
• Katie Benner, “Airbnb Vows to Fight Racism, But Its Users Can’t Sue to Prompt Fairness,” New York Times , June 19, 2016.
• Executive Office of the President, “Artificial Intelligence, Automation, and the Economy” and “Preparing for the Future of Artificial Intelligence.”
• Nancy Scolar, “Facebook’s Next Project: American Inequality,” Politico , February 19, 2018.
• Darrell M. West, “What Internet Search Data Reveals about Donald Trump’s First Year in Office,” Brookings Institution policy report, January 17, 2018.
• Ian Buck, “Testimony before the House Committee on Oversight and Government Reform Subcommittee on Information Technology,” February 14, 2018.
• Keith Nakasone, “Testimony before the House Committee on Oversight and Government Reform Subcommittee on Information Technology,” March 7, 2018.
• Greg Brockman, “The Dawn of Artificial Intelligence,” Testimony before U.S. Senate Subcommittee on Space, Science, and Competitiveness, November 30, 2016.
• Amir Khosrowshahi, “Testimony before the House Committee on Oversight and Government Reform Subcommittee on Information Technology,” February 14, 2018.
• James Kurose, “Testimony before the House Committee on Oversight and Government Reform Subcommittee on Information Technology,” March 7, 2018.
• Stephen Noonoo, “Teachers Can Now Use IBM’s Watson to Search for Free Lesson Plans,” EdSurge , September 13, 2017.
• Congress.gov, “H.R. 4625 FUTURE of Artificial Intelligence Act of 2017,” December 12, 2017.
• Elizabeth Zima, “Could New York City’s AI Transparency Bill Be a Model for the Country?” Government Technology , January 4, 2018.
• Julia Powles, “New York City’s Bold, Flawed Attempt to Make Algorithms Accountable,” New Yorker , December 20, 2017.
• Sheera Frenkel, “Tech Giants Brace for Europe’s New Data Privacy Rules,” New York Times , January 28, 2018.
• Claire Miller and Kevin O’Brien, “Germany’s Complicated Relationship with Google Street View,” New York Times , April 23, 2013.
• Cade Metz, “Artificial Intelligence is Setting Up the Internet for a Huge Clash with Europe,” Wired , July 11, 2016.
• Eric Siegel, “Predictive Analytics Interview Series: Andrew Burt,” Predictive Analytics Times , June 14, 2017.
• Oren Etzioni, “How to Regulate Artificial Intelligence,” New York Times , September 1, 2017.
• “Ethical Considerations in Artificial Intelligence and Autonomous Systems,” unpublished paper. IEEE Global Initiative, 2018.
• Ritesh Noothigattu, Snehalkumar Gaikwad, Edmond Awad, Sohan Dsouza, Iyad Rahwan, Pradeep Ravikumar, and Ariel Procaccia, “A Voting-Based System for Ethical Decision Making,” Computers and Society , September 20, 2017 (www.media.mit.edu/publications/a-voting-based-system-for-ethical-decision-making/).
• Miles Brundage, et al., “The Malicious Use of Artificial Intelligence,” University of Oxford unpublished paper, February 2018.
• John Markoff, “As Artificial Intelligence Evolves, So Does Its Criminal Potential,” New York Times, October 24, 2016, p. B3.
• Economist , “The Challenger: Technopolitics,” March 17, 2018.
• Douglas Maughan, “Testimony before the House Committee on Oversight and Government Reform Subcommittee on Information Technology,” March 7, 2018.
• Levi Tillemann and Colin McCormick, “Roadmapping a U.S.-German Agenda for Artificial Intelligence Policy,” New American Foundation, March 2017.

Artificial Intelligence

Governance Studies

Center for Technology Innovation

Artificial Intelligence and Emerging Technology Initiative

John Villasenor

September 24, 2024

Kevin A. Bryan, Florenta Teodoridis

Andrew W. Wyckoff

September 20, 2024

Home — Essay Samples — Information Science and Technology — Modern Technology — Artificial Intelligence

Essays on Artificial Intelligence

Artificial intelligence essay topics for college students.

Welcome, college students! Writing an essay on artificial intelligence can be an exciting and challenging task. The key to a successful essay lies in selecting the right topic that sparks your interest and allows you to showcase your creativity. In this resource page, we will provide you with a variety of essay types and topics to help you get started on your AI essay journey.

Argumentative Essay Topic for Artificial Intelligence Essays

• The ethical implications of AI technology
• The impact of AI on job automation
• Regulating AI development for societal benefits

Introduction Paragraph Example: Artificial intelligence has revolutionized the way we interact with technology, raising important ethical questions about its implications on society. In this essay, we will explore the ethical challenges of AI technology and discuss the need for regulations to ensure its responsible development.

Conclusion Paragraph Example: In conclusion, it is evident that the ethical implications of AI technology are multifaceted and require careful consideration. By implementing regulations and ethical guidelines, we can harness the benefits of AI while minimizing its potential risks.

Compare and Contrast Essay Topics for Artificial Intelligence

• The differences between narrow AI and general AI
• Comparing AI in science fiction to real-world applications
• The impact of AI on different industries
• AI vs. human intelligence: Strengths and weaknesses
• Machine learning vs. deep learning
• AI in healthcare vs. AI in finance
• AI-driven automation vs. traditional automation
• Cloud-based AI vs. edge AI
• The role of AI in developed vs. developing countries
• AI in education vs. AI in entertainment

Introduction Paragraph Example: The field of artificial intelligence encompasses a wide range of technologies, from narrow AI systems designed for specific tasks to the hypothetical concept of general AI capable of human-like intelligence. In this essay, we will compare and contrast the characteristics of narrow and general AI to understand their implications on society.

Conclusion Paragraph Example: Through this comparison, we have gained insights into the diverse applications of AI technology and the potential challenges it poses to various industries. By understanding the differences between narrow and general AI, we can better prepare for the future of artificial intelligence.

Descriptive Essay Essay Topics for Artificial Intelligence

• The role of AI in healthcare advancements
• The development of AI algorithms for autonomous vehicles
• The applications of AI in natural language processing
• The architecture of neural networks
• The evolution of AI from the 20th century to today
• The ethical implications of AI decision-making
• The process of training an AI model
• The impact of AI on the job market
• The future potential of quantum AI
• The role of AI in personalized marketing

Introduction Paragraph Example: AI technology has transformed the healthcare industry, enabling innovative solutions that improve patient care and diagnosis accuracy. In this essay, we will explore the role of AI in healthcare advancements and its impact on the future of medicine.

Conclusion Paragraph Example: In conclusion, the integration of AI technology in healthcare has the potential to revolutionize the way we approach patient care and medical research. By leveraging AI algorithms and machine learning capabilities, we can achieve significant advancements in the field of medicine.

Persuasive Essay Essay Topics for Artificial Intelligence

• Promoting diversity and inclusion in AI development
• The importance of ethical AI education in schools
• Advocating for AI transparency and accountability
• The necessity of regulating AI technology
• Why AI should be used to combat climate change
• The benefits of AI in improving public safety
• Encouraging responsible AI usage in social media
• The potential of AI to revolutionize education
• Why businesses should invest in AI technology
• The role of AI in enhancing cybersecurity

Introduction Paragraph Example: As artificial intelligence continues to permeate various aspects of our lives, it is essential to prioritize diversity and inclusion in AI development to ensure equitable outcomes for all individuals. In this essay, we will discuss the importance of promoting diversity and inclusion in AI initiatives and the benefits it brings to society.

Conclusion Paragraph Example: By advocating for diversity and inclusion in AI development, we can create a more equitable and socially responsible future for artificial intelligence. Through ethical education and transparent practices, we can build a foundation of trust and accountability in AI technology.

Narrative Essay Essay Topics for Artificial Intelligence

• A day in the life of an AI researcher
• The journey of building your first AI project
• An imaginary conversation with a sentient AI being
• The story of a world transformed by AI
• How AI solved a major global problem
• A personal encounter with AI technology
• The evolution of AI in your lifetime
• The challenges faced while developing an AI startup
• A future where AI coexists with humans
• Your experience learning about AI for the first time

Introduction Paragraph Example: Imagine a world where artificial intelligence blurs the lines between human and machine, offering new possibilities and ethical dilemmas. In this narrative essay, we will embark on a journey through the eyes of an AI researcher, exploring the challenges and discoveries that come with pushing the boundaries of technology.

Conclusion Paragraph Example: Through this narrative journey, we have delved into the complexities of artificial intelligence and the ethical considerations that accompany its development. By embracing the possibilities of AI technology while acknowledging its limitations, we can shape a future that balances innovation with ethical responsibility.

Hooks for Artificial Intelligence Essay

• "Imagine a world where machines not only perform tasks but also think, learn, and make decisions just like humans. Welcome to the era of Artificial Intelligence (AI), a revolutionary force reshaping our future."
• "From self-driving cars to smart personal assistants, AI is seamlessly integrating into our daily lives. But what lies beneath this cutting-edge technology, and how will it transform the way we live and work?"
• "As AI continues to advance at an unprecedented pace, questions about its ethical implications and impact on society become more urgent. Can we control the intelligence we create, or will it control us?"
• "AI is not just a futuristic concept confined to science fiction. It’s here, and it’s real, influencing industries, healthcare, education, and even our personal lives. How prepared are we for this technological revolution?"
• "The debate over AI is heating up: Will it lead to a utopian society with endless possibilities, or is it a Pandora's box with risks we have yet to fully understand? The answers may surprise you."

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Artificial Intelligence: Applications, Advantages and Disanvantages

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Artificial intelligence (AI) refers to the intellectual capabilities exhibited by machines, contrasting with the innate intelligence observed in living beings, such as animals and humans.

The inception of artificial intelligence research as an academic field can be traced back to its establishment in 1956. It was during the renowned Dartmouth conference of the same year that artificial intelligence acquired its distinctive name, definitive purpose, initial accomplishments, and notable pioneers, thereby earning its reputation as the birthplace of AI. The esteemed figures of Marvin Minsky and John McCarthy are widely recognized as the founding fathers of this discipline.

• The term "artificial intelligence" was coined in 1956 by computer scientist John McCarthy.
• McKinsey Global Institute estimates that by 2030, automation and AI technologies could contribute to a global economic impact of $13 trillion.
• AI is used in various industries, including healthcare, finance, and transportation.
• The healthcare industry is leveraging AI for improved patient care. A study published in the journal Nature Medicine reported that an AI model was able to detect breast cancer with an accuracy of 94.5%, outperforming human radiologists.
• Ethical concerns surrounding AI include privacy issues, bias in algorithms, and the potential for job displacement.

Artificial Intelligence is an important topic because it has the potential to revolutionize industries, improve efficiency, and enhance decision-making processes. As AI technology continues to advance, it is crucial for society to understand its implications, both positive and negative, in order to harness its benefits while mitigating its risks.

1. Russell, S. J., & Norvig, P. (2016). Artificial Intelligence: A Modern Approach (3rd ed.). Prentice Hall. 2. Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press. 3. Kurzweil, R. (2005). The Singularity Is Near: When Humans Transcend Biology. Viking. 4. Bostrom, N. (2014). Superintelligence: Paths, Dangers, Strategies. Oxford University Press. 5. Chollet, F. (2017). Deep Learning with Python. Manning Publications. 6. Domingos, P. (2018). The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World. Basic Books. 7. Ng, A. (2017). Machine Learning Yearning. deeplearning.ai. 8. Marcus, G. (2018). Rebooting AI: Building Artificial Intelligence We Can Trust. Vintage. 9. Winfield, A. (2018). Robotics: A Very Short Introduction. Oxford University Press. 10. Shalev-Shwartz, S., & Ben-David, S. (2014). Understanding Machine Learning: From Theory to Algorithms. Cambridge University Press.

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Artificial Intelligence Essay in 100, 200, and 300 Words for School Students

• Updated on  
• Jun 6, 2024

Artificial Intelligence (AI) has revolutionized every economic sector in the 21st century with its capacity to create efficient machines possessing cognitive abilities. Key components of this technological advancement, such as machine learning (ML), deep learning, and natural language processing (NLP), have enabled the development of machines that utilize data and algorithms to perform tasks akin to those performed by humans. To delve deeper into the world of AI, you can explore three insightful essays on Artificial Intelligence available in this blog. Keep browsing.

Table of Contents

• 1 Artificial Intelligence Essay in 100 Words for School Students
• 2 Artificial Intelligence Essay in 200 Words for School Students
• 3 Artificial Intelligence Essay in 300 Words for School Students
• 4 Short Essay on Artificial Intelligence

Also Read: Types of Artificial Intelligence

Artificial Intelligence Essay in 100 Words for School Students

Artificial Intelligence or AI is a revolutionary technology that allows machines to undertake tasks that usually need human intelligence. It includes natural language processing (NLP), problem-solving capabilities, and machine learning (ML). In contemporary times, AI technology has entered all aspects of human life. Currently, AI technology is present in virtual assistants like Siri to advanced applications in the finance, industrial, and healthcare sectors.

Even though AI presents extensive potential for innovation and efficiency, it has adverse effects like ethical concerns and job displacement. Therefore, it is important that we use AI technology in a controlled manner and always aspire for the wholesome development of human civilization. 

Also Read: Career in Artificial Intelligence: Opportunities & Outlook

Artificial Intelligence Essay in 200 Words for School Students

Artificial Intelligence (AI) is an evolving technology in the field of computer science. This technology aims to curate machines capable of reasoning, learning, and problem-solving by mimicking human cognitive functions. This technology allows computer and machine systems to adapt and improve performance without explicit programming using machine learning (ML), a subset of AI. Furthermore, AI technology is used in streaming platforms, autonomous vehicles, and advanced medical diagnostics. Due to its widespread usage, AI has become an integral part of the modern society.

However, the rapid development of AI technology often raises ethical concerns, especially about data privacy and security. Also, advancements in this latest technology have the potential to increase unemployment across various sectors. Thus, it is essential to strike a balance between innovation and protection of human elements and interests in the job sector and personal life. 

Therefore, as we adopt AI in our daily lives, it becomes our responsibility to generate awareness about crucial elements of AI and its impact on human civilization. On top of that, it is significant to mankind that technology should always adhere to the ethical guidelines of data privacy and cyber security. Also, federal and state governments must implement laws that prevent AI developers from threatening social harmony and national security within and beyond the nation’s territorial boundaries. 

Also Read: Top AI Courses after 12th with Salaries

Also Read: How to Prepare for UPSC in 6 Months?

Artificial Intelligence Essay in 300 Words for School Students

The advent of Artificial Intelligence (AI) is an attempt to converge computer science, mathematics, and cognitive science into singular units to create machines with human intelligence. These machines help in learning, reasoning, problem-solving, and language understanding. Owing to the varied tasks performed by AI-enabled machines, AI technology has become a landmark element of the technological revolution of the 21st century. 

AI technology has transformed the fields of healthcare, finance, automobile, and streaming services. In healthcare, AI is used for drug discovery and diagnosis. Whereas, in the financial sector, AI is used for risk management and optimization of trading strategies. On top of that, this technology has led to the development of AI-powered vehicles, which promise efficient and safe transportation. Furthermore, AI is used in recommendation systems on platforms like Netflix and Amazon to provide personalized suggestions based on the behavior and preferences of users. 

However, exemplary technological advancements always come with numerous drawbacks. One of the grave consequences of the large-scale adoption of AI is the fear of job loss. In recent times, automation has left many jobless, especially in the manufacturing sector. Thus, governments and technology companies must ensure that there should be a balanced discussion between technological advancements and societal well-being. Also, policymakers must have regular dialogue with ethicists to control the exploitation of citizen’s data by technology companies. 

Nevertheless, AI has opened exciting opportunities for inquisitive minds as it has created exciting jobs in coding, data science, and robotics. Owing to the increased use of AI technology in these arenas, people have the opportunity to improve their critical thinking, creativity, and problem-solving skills. To leverage new opportunities like these, students should start gaining hands-on experience with AI technologies at an early age. 

Thus, Artificial Intelligence is a revolutionary force that will shape the future of mankind. To harness the maximum benefits of this technology, it is advisable to use it wisely. Any development or innovation in AI technology must be directed towards the betterment of society and aim to protect the privacy of the weakest section of society. 

Also Read: Applications of Artificial Intelligence

Short Essay on Artificial Intelligence

Also Read: Speech on AI in English for School Students: Check Samples

Ans: AI is a branch of technology and computer science that empowers machines to perform tasks that require human intelligence. AI systems or AI-enabled machines use data and algorithms to learn, reason, and solve problems. It is widely used for speech recognition, autonomous vehicles, image processing, and disease diagnosis.

Ans: Machine learning (ML), natural language processing (NLP), deep learning, algorithms, and problem-solving are some of the essential AI elements. 

Ans: You can start by defining Artificial Intelligence. Then you can highlight its application in different fields. Thereafter, you can highlight the ethical concerns around this technology. Finally, you can conclude by weighing in on the future implications of this technological advancement. 

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Ankita Singh

Ankita is a history enthusiast with a few years of experience in academic writing. Her love for literature and history helps her curate engaging and informative content for education blog. When not writing, she finds peace in analysing historical and political anectodes.

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Artificial Intelligence and Its Impact on Education Essay

• To find inspiration for your paper and overcome writer’s block
• As a source of information (ensure proper referencing)
• As a template for you assignment

Introduction

Ai’s impact on education, the impact of ai on teachers, the impact of ai on students, reference list.

Rooted in computer science, Artificial Intelligence (AI) is defined by the development of digital systems that can perform tasks, which are dependent on human intelligence (Rexford, 2018). Interest in the adoption of AI in the education sector started in the 1980s when researchers were exploring the possibilities of adopting robotic technologies in learning (Mikropoulos, 2018).

Their mission was to help learners to study conveniently and efficiently. Today, some of the events and impact of AI on the education sector are concentrated in the fields of online learning, task automation, and personalization learning (Chen, Chen and Lin, 2020). The COVID-19 pandemic is a recent news event that has drawn attention to AI and its role in facilitating online learning among other virtual educational programs. This paper seeks to find out the possible impact of artificial intelligence on the education sector from the perspectives of teachers and learners.

Technology has transformed the education sector in unique ways and AI is no exception. As highlighted above, AI is a relatively new area of technological development, which has attracted global interest in academic and teaching circles. Increased awareness of the benefits of AI in the education sector and the integration of high-performance computing systems in administrative work have accelerated the pace of transformation in the field (Fengchun et al. , 2021). This change has affected different facets of learning to the extent that government agencies and companies are looking to replicate the same success in their respective fields (IBM, 2020). However, while the advantages of AI are widely reported in the corporate scene, few people understand its impact on the interactions between students and teachers. This research gap can be filled by understanding the impact of AI on the education sector, as a holistic ecosystem of learning.

As these gaps in education are minimized, AI is contributing to the growth of the education sector. Particularly, it has increased the number of online learning platforms using big data intelligence systems (Chen, Chen and Lin, 2020). This outcome has been achieved by exploiting opportunities in big data analysis to enhance educational outcomes (IBM, 2020). Overall, the positive contributions that AI has had to the education sector mean that it has expanded opportunities for growth and development in the education sector (Rexford, 2018). Therefore, teachers are likely to benefit from increased opportunities for learning and growth that would emerge from the adoption of AI in the education system.

The impact of AI on teachers can be estimated by examining its effects on the learning environment. Some of the positive outcomes that teachers have associated with AI adoption include increased work efficiency, expanded opportunities for career growth, and an improved rate of innovation adoption (Chen, Chen and Lin, 2020). These benefits are achievable because AI makes it possible to automate learning activities. This process gives teachers the freedom to complete supplementary tasks that support their core activities. At the same time, the freedom they enjoy may be used to enhance creativity and innovation in their teaching practice. Despite the positive outcomes of AI adoption in learning, it undermines the relevance of teachers as educators (Fengchun et al., 2021). This concern is shared among educators because the increased reliance on robotics and automation through AI adoption has created conditions for learning to occur without human input. Therefore, there is a risk that teacher participation may be replaced by machine input.

Performance Evaluation emerges as a critical area where teachers can benefit from AI adoption. This outcome is feasible because AI empowers teachers to monitor the behaviors of their learners and the differences in their scores over a specific time (Mikropoulos, 2018). This comparative analysis is achievable using advanced data management techniques in AI-backed performance appraisal systems (Fengchun et al., 2021). Researchers have used these systems to enhance adaptive group formation programs where groups of students are formed based on a balance of the strengths and weaknesses of the members (Live Tiles, 2021). The information collected using AI-backed data analysis techniques can be recalibrated to capture different types of data. For example, teachers have used AI to understand students’ learning patterns and the correlation between these configurations with the individual understanding of learning concepts (Rexford, 2018). Furthermore, advanced biometric techniques in AI have made it possible for teachers to assess their student’s learning attentiveness.

Overall, the contributions of AI to the teaching practice empower teachers to redesign their learning programs to fill the gaps identified in the performance assessments. Employing the capabilities of AI in their teaching programs has also made it possible to personalize their curriculums to empower students to learn more effectively (Live Tiles, 2021). Nonetheless, the benefits of AI to teachers could be undermined by the possibility of job losses due to the replacement of human labor with machines and robots (Gulson et al. , 2018). These fears are yet to materialize but indications suggest that AI adoption may elevate the importance of machines above those of human beings in learning.

The benefits of AI to teachers can be replicated in student learning because learners are recipients of the teaching strategies adopted by teachers. In this regard, AI has created unique benefits for different groups of learners based on the supportive role it plays in the education sector (Fengchun et al., 2021). For example, it has created conditions necessary for the use of virtual reality in learning. This development has created an opportunity for students to learn at their pace (Live Tiles, 2021). Allowing students to learn at their pace has enhanced their learning experiences because of varied learning speeds. The creation of virtual reality using AI learning has played a significant role in promoting equality in learning by adapting to different learning needs (Live Tiles, 2021). For example, it has helped students to better track their performances at home and identify areas of improvement in the process. In this regard, the adoption of AI in learning has allowed for the customization of learning styles to improve students’ attention and involvement in learning.

AI also benefits students by personalizing education activities to suit different learning styles and competencies. In this analysis, AI holds the promise to develop personalized learning at scale by customizing tools and features of learning in contemporary education systems (du Boulay, 2016). Personalized learning offers several benefits to students, including a reduction in learning time, increased levels of engagement with teachers, improved knowledge retention, and increased motivation to study (Fengchun et al., 2021). The presence of these benefits means that AI enriches students’ learning experiences. Furthermore, AI shares the promise of expanding educational opportunities for people who would have otherwise been unable to access learning opportunities. For example, disabled people are unable to access the same quality of education as ordinary students do. Today, technology has made it possible for these underserved learners to access education services.

Based on the findings highlighted above, AI has made it possible to customize education services to suit the needs of unique groups of learners. By extension, AI has made it possible for teachers to select the most appropriate teaching methods to use for these student groups (du Boulay, 2016). Teachers have reported positive outcomes of using AI to meet the needs of these underserved learners (Fengchun et al., 2021). For example, through online learning, some of them have learned to be more patient and tolerant when interacting with disabled students (Fengchun et al., 2021). AI has also made it possible to integrate the educational and curriculum development plans of disabled and mainstream students, thereby standardizing the education outcomes across the divide. Broadly, these statements indicate that the expansion of opportunities via AI adoption has increased access to education services for underserved groups of learners.

Overall, AI holds the promise to solve most educational challenges that affect the world today. UNESCO (2021) affirms this statement by saying that AI can address most problems in learning through innovation. Therefore, there is hope that the adoption of new technology would accelerate the process of streamlining the education sector. This outcome could be achieved by improving the design of AI learning programs to make them more effective in meeting student and teachers’ needs. This contribution to learning will help to maximize the positive impact and minimize the negative effects of AI on both parties.

The findings of this study demonstrate that the application of AI in education has a largely positive impact on students and teachers. The positive effects are summarized as follows: improved access to education for underserved populations improved teaching practices/instructional learning, and enhanced enthusiasm for students to stay in school. Despite the existence of these positive views, negative outcomes have also been highlighted in this paper. They include the potential for job losses, an increase in education inequalities, and the high cost of installing AI systems. These concerns are relevant to the adoption of AI in the education sector but the benefits of integration outweigh them. Therefore, there should be more support given to educational institutions that intend to adopt AI. Overall, this study demonstrates that AI is beneficial to the education sector. It will improve the quality of teaching, help students to understand knowledge quickly, and spread knowledge via the expansion of educational opportunities.

Chen, L., Chen, P. and Lin, Z. (2020) ‘Artificial intelligence in education: a review’, Institute of Electrical and Electronics Engineers Access , 8(1), pp. 75264-75278.

du Boulay, B. (2016) Artificial intelligence as an effective classroom assistant. Institute of Electrical and Electronics Engineers Intelligent Systems , 31(6), pp.76–81.

Fengchun, M. et al. (2021) AI and education: a guide for policymakers . Paris: UNESCO Publishing.

Gulson, K . et al. (2018) Education, work and Australian society in an AI world . Web.

IBM. (2020) Artificial intelligence . Web.

Live Tiles. (2021) 15 pros and 6 cons of artificial intelligence in the classroom . Web.

Mikropoulos, T. A. (2018) Research on e-Learning and ICT in education: technological, pedagogical and instructional perspectives . New York, NY: Springer.

Rexford, J. (2018) The role of education in AI (and vice versa). Web.

Seo, K. et al. (2021) The impact of artificial intelligence on learner–instructor interaction in online learning. International Journal of Educational Technology in Higher Education , 18(54), pp. 1-12.

UNESCO. (2021) Artificial intelligence in education . Web.

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The present and future of AI

Finale doshi-velez on how ai is shaping our lives and how we can shape ai.

Finale Doshi-Velez, the John L. Loeb Professor of Engineering and Applied Sciences. (Photo courtesy of Eliza Grinnell/Harvard SEAS)

How has artificial intelligence changed and shaped our world over the last five years? How will AI continue to impact our lives in the coming years? Those were the questions addressed in the most recent report from the One Hundred Year Study on Artificial Intelligence (AI100), an ongoing project hosted at Stanford University, that will study the status of AI technology and its impacts on the world over the next 100 years.

The 2021 report is the second in a series that will be released every five years until 2116. Titled “Gathering Strength, Gathering Storms,” the report explores the various ways AI is  increasingly touching people’s lives in settings that range from  movie recommendations  and  voice assistants  to  autonomous driving  and  automated medical diagnoses .

Barbara Grosz , the Higgins Research Professor of Natural Sciences at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) is a member of the standing committee overseeing the AI100 project and Finale Doshi-Velez , Gordon McKay Professor of Computer Science, is part of the panel of interdisciplinary researchers who wrote this year’s report. 

We spoke with Doshi-Velez about the report, what it says about the role AI is currently playing in our lives, and how it will change in the future.  

Q: Let's start with a snapshot: What is the current state of AI and its potential?

Doshi-Velez: Some of the biggest changes in the last five years have been how well AIs now perform in large data regimes on specific types of tasks.  We've seen [DeepMind’s] AlphaZero become the best Go player entirely through self-play, and everyday uses of AI such as grammar checks and autocomplete, automatic personal photo organization and search, and speech recognition become commonplace for large numbers of people.  

In terms of potential, I'm most excited about AIs that might augment and assist people.  They can be used to drive insights in drug discovery, help with decision making such as identifying a menu of likely treatment options for patients, and provide basic assistance, such as lane keeping while driving or text-to-speech based on images from a phone for the visually impaired.  In many situations, people and AIs have complementary strengths. I think we're getting closer to unlocking the potential of people and AI teams.

There's a much greater recognition that we should not be waiting for AI tools to become mainstream before making sure they are ethical.

Q: Over the course of 100 years, these reports will tell the story of AI and its evolving role in society. Even though there have only been two reports, what's the story so far?

There's actually a lot of change even in five years.  The first report is fairly rosy.  For example, it mentions how algorithmic risk assessments may mitigate the human biases of judges.  The second has a much more mixed view.  I think this comes from the fact that as AI tools have come into the mainstream — both in higher stakes and everyday settings — we are appropriately much less willing to tolerate flaws, especially discriminatory ones. There's also been questions of information and disinformation control as people get their news, social media, and entertainment via searches and rankings personalized to them. So, there's a much greater recognition that we should not be waiting for AI tools to become mainstream before making sure they are ethical.

Q: What is the responsibility of institutes of higher education in preparing students and the next generation of computer scientists for the future of AI and its impact on society?

First, I'll say that the need to understand the basics of AI and data science starts much earlier than higher education!  Children are being exposed to AIs as soon as they click on videos on YouTube or browse photo albums. They need to understand aspects of AI such as how their actions affect future recommendations.

But for computer science students in college, I think a key thing that future engineers need to realize is when to demand input and how to talk across disciplinary boundaries to get at often difficult-to-quantify notions of safety, equity, fairness, etc.  I'm really excited that Harvard has the Embedded EthiCS program to provide some of this education.  Of course, this is an addition to standard good engineering practices like building robust models, validating them, and so forth, which is all a bit harder with AI.

I think a key thing that future engineers need to realize is when to demand input and how to talk across disciplinary boundaries to get at often difficult-to-quantify notions of safety, equity, fairness, etc. 

Q: Your work focuses on machine learning with applications to healthcare, which is also an area of focus of this report. What is the state of AI in healthcare? 

A lot of AI in healthcare has been on the business end, used for optimizing billing, scheduling surgeries, that sort of thing.  When it comes to AI for better patient care, which is what we usually think about, there are few legal, regulatory, and financial incentives to do so, and many disincentives. Still, there's been slow but steady integration of AI-based tools, often in the form of risk scoring and alert systems.

In the near future, two applications that I'm really excited about are triage in low-resource settings — having AIs do initial reads of pathology slides, for example, if there are not enough pathologists, or get an initial check of whether a mole looks suspicious — and ways in which AIs can help identify promising treatment options for discussion with a clinician team and patient.

Q: Any predictions for the next report?

I'll be keen to see where currently nascent AI regulation initiatives have gotten to. Accountability is such a difficult question in AI,  it's tricky to nurture both innovation and basic protections.  Perhaps the most important innovation will be in approaches for AI accountability.

Topics: AI / Machine Learning , Computer Science

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Artificial Intelligence Essay | Essay on Artificial Intelligence for Students and Children in English

February 13, 2024 by Prasanna

Artificial Intelligence Essay:  In contrast to the natural intelligence of humans and animals when the machines are equipped to do intelligent tasks, it is called Artificial Intelligence.

Some tasks that human intelligence is capable like learning, analyzing, problem-solving, etc. when done by machines is a noteworthy example of AI. All in all, the simulation of some human intelligence skills by machines is called Artificial Intelligence.

You can also find more  Essay Writing  articles on events, persons, sports, technology and many more

Long And Short Essays on Artificial Intelligence for Kids and Students In English

We are providing students and teachers with essay samples on an extended essay on Artificial Intelligence of 500 words and a short essay on Artificial Intelligence of 150 words along with ten lines on the same topic.

A Long Essay on Artificial Intelligence is helpful to students of classes 7, 8, 9, 10, 11 and 12. A Short Essay on Artificial Intelligence is helpful to students of classes 1, 2, 3, 4, 5 and 6.

Long Essay on Artificial Intelligence 500 Words In English

With the continuous development in science and technology, it is hard to estimate how far and what else we will be able to establish. According to experts, the future of the world seems to be dominated by Artificial Intelligence. And the time is assumed to be not far when almost every aspect of our life involves AI assistance in some way or the other.

Since I am using the term ‘Artificial Intelligence’ and many others too use this term in their daily life or at least have come across this term, but do we what the term exactly stands for?

The ability of a computer system or a machine to operate and process information like a human being is called Artificial Intelligence or simply AI. It can learn, analyze, copy, and adapt to new information and perform without much external optimization.

Experts believe that AI in future will be able to make human life much easier by providing a solution to almost all challenges. Humans will also be made aware of potential threats from beforehand by Artificial Intelligence use. One of the fastest-growing fields of technology and invention is that of AI.

AI has established its position in several marketing activities. And the automation of marketing processes has increased the demand for AI implementation in the industry recently as well. AI has also brought opportunities to marketers to expand their business and provided user interface insight.

Artificial Intelligence can be categorized into four categories, and this categorization was brought up by Arend Hintze.

• The first types of AI are those machines which can react to certain situations, but these machines don’t have any sort of memory and hence cannot learn or use past experience. Computer chess games are a simple example of this first type of AI.
• The second types of AI are those machines which are capable of using past memory to form future ones. An excellent example of this second type of AI is self-driving cars.
• The third type of AI at present only exists in theory, and as per the imagination, it will be able to have humane emotions like beliefs, desires, opinions, intentions, etc.
• The most sophisticated form of AI if ever comes to exist would be this fourth type of AI. This fourth type of AI machine will be able to have a sense of self-awareness, emotions and consciousness. If this type of AI ever comes to exist, then it would be a real revolution.

AI has great importance in healthcare use. Different companies are trying to develop different quick diagnosis technology with the help of AI.

For the business sector, Artificial Intelligence can save a lot of time and effort. Robotic Automation is a type of application which is used to complete human business tasks

In the education sector, AI technology meets the needs of the students. AI-enabled the automated grading system for saving a lot of time in the results. AI is a great way of increasing manufacturing as well.

In various other fields as well, the contribution of Artificial Intelligence is huge. Hence it is clear that Artificial Intelligence is all set to be the future of the entire world. The world seems exciting and intriguing with Artificial Intelligence.

Short Essay on Artificial Intelligence 150 Words In English

The field of computer science and engineering that attempts to simulate the features of human intelligence or capabilities through the help of machines is called Artificial Intelligence. The acronym for it is AI. The characteristics that machines are designed to do through the implementation of AI are learning, understanding, reasoning, adapting, etc.

The developments of Artificial Intelligence were following a pretty slow pace as not much difference was made until five years before. But the popularity of Artificial Intelligence boosted with the evolutionary discoveries made in the fields.

Soon markets realized the benefits of AI and the demand for this technology raised with the increasing rate of incorporation of AI modes into businesses. Now we might not even realize it, but when we are interacting online to service, we might be providing problem information to AI and receiving a solution from it in return.

10 Lines On Artificial Intelligence Essay In English

• The computer science or engineering field dealing with the development of smart machines that work and can respond similarly to humans is called Artificial Intelligence (AI).
• The algorithm-based behind google search engine is also an Artificial Intelligence system.
• Chat boxes are now operated with AI to answer basic customer queries.
• Google Assistant, Alexa, Siri, etc. are Artificial Intelligence-based software that can follow voice commands.
• AI won’t overtake humans because the natural skill of adjusting and adopting other skills is much faster of humans than AI.
• The contributions of AI are tremendous in Healthcare and Marketing fields.
• AI is used to develop Natural Language Processing (NLP).
• The way in which computers analyze, understand and derive the meaning of human language is NLP.
• In the future, many accidents and dangers can be avoided with the help of Artificial Intelligence.
• Chatbots are AI-based one-on-one customer service provider systems.

FAQ’s on Artificial Intelligence Essay

Question 1. Who coined the term Artificial Intelligence?

Answer: John McCarthy.

Question 2. When was the term Artificial Intelligence first coined?

Answer: 1956

Question 3. Mention a few technologies that fall under AI?

Answer: Speech recognition, machine learning platforms, deep learning platforms, biometrics, robotics, automation, image recognition, etc. all are the result of AI technology.

Question 4. State the definition of the term AI?

Answer: The term Artificial Intelligence is defined as the science and engineering behind creating intelligent or smart machines.

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AI for Essay Writing — Exploring Top 10 Essay Writers

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Let’s admit it — essay writing is quite a challenging task for students. Especially with the stringent deadlines, conducting research, writing , editing, and addressing to-and-fro reviews — consumes a whole lot of time and often becomes stressful. Therefore, students are always on the lookout for tools that speed up the essay writing process.

And that’s when AI writing tools make their debut! Using the best AI for essay writing makes the lives of students much easier by automatically generating the essay for them.

The rise in the popularity of artificial intelligence technology and deep learning has paved the way for the numerous AI writer tools available today. To help you understand the different types of AI tools and their benefits, we’ve uncovered the features of the top 10 AI essay generators in this article.

Let’s explore the tools and learn how they are transforming the tedious task of essay writing!

What is essay writing?

Essay writing is a part of academic writing that emphasizes formulating an idea or argument. The main objective of academic essay writing is to present a well-reasoned argument or idea. Evidence, analysis, and interpretation are the three major components of essay writing . It should have a logical structure to support the argument or idea of the essay so that it communicates clearly and concisely.

What is an AI essay writer?

AI essay writers is a tool that is designed to help students generate essays using machine learning techniques. They can be used to generate a full essay or generate a few parts of the essay, for example, essay titles, introduction, conclusion, etc.

Why should researchers use AI essay generators?

There are infinite benefits to using AI tools for writing unique essays, especially for researchers or students. Here are a few of them —

1. Saves time

Using best AI for essay writing has its own benefits. Students can take care of the research process while these AI tools write the essays for them. Be it an essay topic or a full-length essay generation, it saves a bunch of students' time.

2. Boosts productivity

Writing is a tedious task especially when you want to write an essay about a novel topic, that writer’s block starts haunting and your productivity gets affected. But, with AI, it’s the other way around and increases productivity by quickly generating the essays for you.

3. Enhances writing skills — Vocabulary and Style

Adopting the best AI essay writing AI tool not only help with creating essays but also help us hone our writing skills by giving proper suggestions about grammar, sentence structure, tone, style, and word choice.

4. Reduces stress

Students often undergo a lot of pressure and stress because of deadlines and submissions. With the best AI essay generator, they help you write essays smarter thereby reducing stress and fear in no time.

5. Facilitates multidisciplinary research

AI essay writing tools foster interdisciplinary study through their ability to scan and combine knowledge from multiple domains. That way, it helps us quickly get a grasp of new subjects or topics without a heavy-lifting process.

6. Cost-effective

Most of the AI essay writing tools have lower pricing and also allow certain discounts for students. So, it is also a cost-effective approach to use AI writing tools.

The Top AI Essay Writing Tools and Their Features

Several AI essay writers are available based on the types of essays one would want to generate. Now, let's quickly understand the top 10 AI writing tools that generate essays within just a few minutes.

1. PerfectEssayWriter.ai

It is one of the best AI for essay writing that not only creates an essay but also comes up with advanced features including plagiarism detection, auto-referencing, and contextual analysis. As a result, it generates coherent essays that are well-researched and properly cited. It is best recommended for creating academic essays and essay outlines.

How does PerfectEssayWriter work?

• Pick the right tool for your purpose — Go with an essay writer if you want to generate a full essay or choose the essay outliner if you want to create just the outline of the essay.
• Enter your specific conditions and preferences. Add essay topic, academic level, essay type, number of pages, and special instructions, if any.
• Click on “generate” and wait for the result
• Once you have the essay generated, you can review, edit, or refine it and then download it.
• Generates a large chunk of data up to 2000 words
• Output is provided within 90 seconds
• Provides a plethora of other tools like Citation generator, grammar checker, thesis statement generator, and more
• Comes with 10+ essay writing templates
• Subscription-based and not a free tool
• Human review is a mandate

2. Essaybot - Personalized AI writing

Essaybot is the product of a reputed online essay-writing service, MyPerfectWords. It is meant to enhance academic essay writing and streamline the tasks of students. Its user friendly website makes it an instant and hassle-free essay generation saving a lot of time and effort for students.

How does Essaybot work?

• Enter the essay title or topic
• Click on “start writing” and wait for it to generate a well-reasoned essay.
• The tools come for free
• No sign-up is required
• 100% unique and High-quality output
• Very limited features that lack advanced functionalities

3. FreeEssayWriter.net

FreeEssayWriter is an organization that provides essay-writing services to students worldwide. It has an AI essay typer tool — that helps you generate essays instantly. What sets this essay typer apart is its initiative to help students with their free essay writer providing the students with a 2-page free essay.

How does FreeEssayWriter.net work?

It works similarly to Essaybot, input the title or the topic of your essay and wait for it to generate the essay. They also have an option to edit and download a free version of the generated essay instantly.

• Provides high-quality essays and is considered to be one of the reliable and trusted sources of information
• Students can improve their writing skills and learn more about essays by referring to their free essay database or sources
• Priority customer support is available 24*7
• The site is not optimized for mobile devices
• The quality of the essay output could still be improved

4. MyEssayWriter

This AI essay writing tool is no exception in terms of generating a high-quality essay. You can generate essays for various topics depending on the background of your research study. Be it academic or non-academic essay writing, this tool comes in handy.

How does MyEssay Writer work?

Add your preferences and then click on generate. It will give you a high-quality and 100% unique essay crafted based on your requirements.

• The tool comes for free — no subscription is required
• Knows for its consistency in the quality and the tone of the essay output
• Also has a paid custom writing service that provides human-written essays
• Might not provide quality output for complex and technical-based keywords or topic

5. College Essay AI

College essay AI stands unique as an ai writing tool as it not only uses an AI-based algorithm to generate essays but it also backs up the output as it is reviewed and approved by a team of professional experts. It is the best AI essay writing tool for college and graduate students where the output adheres to the graduate students' essay writing guidelines.

How does the College Essay AI generator work?

• Input the required information — essay topic, academic level, number of pages, sources, and specific instructions, if any.
• Click on “generate essay” and wait for the output
• Conduct plagiarism and grammar check
• Download the essay
• High-level output for academic essay writing
• Pocket-friendly premium plans
• Doesn’t provide multiple sets of templates
• Not quite suitable for non-academic essay writing

6. Jasper AI

Jasper AI has been the oldest player in the game of AI content writing. Fast forward to now, its features have been magnified with the inception of natural language processing algorithms and that’s how they are helping students write their essays as well. However, Jasper is the best AI tool for non-academic writing projects like content writing or creative writing.

How does Jasper AI work?

• Choose a template — if you are about to write an essay, go with the “document”
• Add your preferences
• Click “compose” and get the output
• Generates the essays instantly
• Provides well-structured output according to the tone and style of your preferences
• Not quite suitable for academic writing essays

7. Textero AI

Textero AI provides a few writing tools for students that facilitate their various academic papers and writing projects. Its essay generator helps you generate ideas for a full-length essay based on the topic and also suggests new topic ideas or thesis statement ideas for your academic assignments.

How does Textero AI work?

• Click on “Essay Generator” located on the LHS (Left-hand Side)
• Input the title and description based on which you want to generate the essay
• Pick the right citation style
• Click “generate” and wait for the output
• It also provides other tools like an outline generator, and summary generator and has an AI research assistant that answers all your questions relevant to the research
• The output is 100% unique and plagiarism and error-free
• Might fail to provide an essay focussed on complex or technical topics

8. Quillbot

Though Quillbot is essentially built for paraphrasing and summarizing tasks. It comes as a rescue when you have to revamp, improvise, or refine your already-composed essay. Its co-writer helps you transform your thoughts and ideas and make them more coherent by rephrasing them. You can easily customize your text based on the customization options available.

How does Quillbot Paraphraser work?

• Import or copy the content
• Click on “Paraphrase” “Summarize” or “Suggest text” based on your requirement
• Make the required customizations and save the document.
• Offers a plethora of tools required for students
• Both free and premium plans are available
• Enhances vocabulary and language skills
• Limited customization options with the free plan
• Only supports the English language

9. SciSpace Paraphraser

SciSpace is the best AI tool that helps you fine-tune your essay. If you feel your essay writing needs AI suggestions to improve the language, vocabulary, writing styles, and tone of your essay, SciSpace is at your rescue. It has more customized options than Quillbot and improves your essay by rephrasing it according to the required or preferred writing style, and tone. This is a very good alternative to Quillbot.

How does SciSpace Paraphrasing work?

• Simply paste the content to the screen
• Choose the length and variation properly
• Select the language
• Click “Paraphrase”
• Has 22 custom tones and all of them are available even on the free plan
• Supports 75+ languages
• Comes with an AI-detection report for English paraphrase output
• Delay in the output

10. ChatGPT

It would be unfair if we talk about AI tools and do not enlist ChatGPT. When it comes to automated essay writing tasks, ChatGPT is not trivial. With proper prompts, you can automate the essay writing process and generate a well-crafted and coherent essay. However, the quality and the accuracy cannot be trusted as the model hallucinates and doesn’t include sources.

How does ChatGPT work?

• Create a prompt based on your requirement
• Ask ChatGPT to write an essay about your topic, specify conditions and preferences
• Click enter and wait for the essay
• Comes for free
• Cannot rely on the output as the model hallucinates
• Lacks the upgraded features that other essay-writing tools have

Concluding!

Writing essays can be a real struggle. But, the inception of the best AI essay-generation tools makes the entire writing process a lot easier and smoother. However, you should be extra vigilant while relying on these tools and consciously use them only as a technological aid. Because over-reliance on these AI tools could diminish student's writing skills and the user can become more gripped by the tools. So, use it wisely without affecting your knowledge and skills.

You can explore the above tools whenever you need any help with essay writing, and reap the benefits of them without compromising on the quality of your writing.

And! If you're stuck exploring multiple research papers or want to conduct a comprehensive literature review , you know which tool to use? Yes, it's SciSpace Literature Review, our AI-powered workspace, which is meant to make your research workflow easier. Plus, it also comes with SciSpace Copilot , our AI research assistant that answers any question that you may have about the research paper.

If you haven't used it yet, you can use it here !

Choosing the best AI for writing long-form essays depends on your requirements. Here are the top 5 tools that help you create long-form and college essays —

1. Free Essay Writer AI

2. College Essay AI

3. My Essay Writer

4. Textero AI

5. Perfect Essay Writer

The Perfect Essay Writer AI and Textero AI are the two best AI essay generators that help you write the best essays.

ChatGPT is not specifically built to assist you with essay writing, however, you can use the tool to create college essays and long-form essays. It’s important to review, fact-check the essay, and refer to the sources properly.

Essaybot is a free AI essay generator tool that helps you create a well-reasoned essay with just a click.

Unless your university permits it, using AI essay generators or writing tools to write your essay can be considered as plagiarism.

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人工智能在系统文献综述中的作用

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International Journal of Educational Research Open

Exploring artificial intelligence in academic essay: higher education student's perspective.

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What is artificial intelligence?

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• Harvard University - Science in the News - The History of Artificial Intelligence
• Journal of Emerging Technologies and Innovative Research - A Study on the Robotics and Artificial Intelligence
• National Center for Biotechnology Information - PubMed Central - The rise of artificial intelligence in healthcare applications
• Lifewire - What is artificial intelligence?
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Artificial intelligence is the ability of a computer or computer-controlled robot to perform tasks that are commonly associated with the  intellectual processes characteristic of humans , such as the ability to reason. Although there are as yet no AIs that match full human flexibility over wider domains or in tasks requiring much everyday knowledge, some AIs perform specific tasks as well as humans. Learn more.

Are artificial intelligence and machine learning the same?

No, artificial intelligence and machine learning are not the same, but they are closely related. Machine learning is the method to train a computer to learn from its inputs but without explicit programming for every circumstance. Machine learning helps a computer to achieve artificial intelligence.

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artificial intelligence (AI) , the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. The term is frequently applied to the project of developing systems endowed with the intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience. Since their development in the 1940s, digital computers have been programmed to carry out very complex tasks—such as discovering proofs for mathematical theorems or playing chess —with great proficiency. Despite continuing advances in computer processing speed and memory capacity, there are as yet no programs that can match full human flexibility over wider domains or in tasks requiring much everyday knowledge. On the other hand, some programs have attained the performance levels of human experts and professionals in executing certain specific tasks, so that artificial intelligence in this limited sense is found in applications as diverse as medical diagnosis , computer search engines , voice or handwriting recognition, and chatbots .

What is intelligence?

Artificial intelligence is changing how we interact online, how we manage our finances, and even how we work. Learn more with Britannica Money .

• Using AI for money management
• How AI is changing work
• Ethical questions and AI
• AI and regulation
• Investing in AI stocks

All but the simplest human behavior is ascribed to intelligence, while even the most complicated insect behavior is usually not taken as an indication of intelligence. What is the difference? Consider the behavior of the digger wasp , Sphex ichneumoneus . When the female wasp returns to her burrow with food, she first deposits it on the threshold , checks for intruders inside her burrow, and only then, if the coast is clear, carries her food inside. The real nature of the wasp’s instinctual behavior is revealed if the food is moved a few inches away from the entrance to her burrow while she is inside: on emerging, she will repeat the whole procedure as often as the food is displaced. Intelligence—conspicuously absent in the case of the wasp—must include the ability to adapt to new circumstances.

(Read Ray Kurzweil’s Britannica essay on the future of “Nonbiological Man.”)

Psychologists generally characterize human intelligence not by just one trait but by the combination of many diverse abilities. Research in AI has focused chiefly on the following components of intelligence: learning, reasoning, problem solving , perception , and using language.

There are a number of different forms of learning as applied to artificial intelligence. The simplest is learning by trial and error. For example, a simple computer program for solving mate-in-one chess problems might try moves at random until mate is found. The program might then store the solution with the position so that, the next time the computer encountered the same position, it would recall the solution. This simple memorizing of individual items and procedures—known as rote learning—is relatively easy to implement on a computer. More challenging is the problem of implementing what is called generalization . Generalization involves applying past experience to analogous new situations. For example, a program that learns the past tense of regular English verbs by rote will not be able to produce the past tense of a word such as jump unless the program was previously presented with jumped , whereas a program that is able to generalize can learn the “add -ed ” rule for regular verbs ending in a consonant and so form the past tense of jump on the basis of experience with similar verbs.

(Read Yuval Noah Harari’s Britannica essay on the future of “Nonconscious Man.”)

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Home Essay Samples Information Science and Technology

Essay Samples on Artificial Intelligence

Artificial intelligence (AI) is a rapidly growing field, and writing an essay on it can be an excellent way to explore its various aspects. An artificial intelligence essay can be a great opportunity to discuss the advantages and disadvantages of AI and how it can impact society. It can also explore the technical details of AI, such as how it works and how it is developed.

One popular topic for essays about AI is its impact on the job market. AI is transforming industries and creating new jobs, but it is also replacing human workers in some areas. Another interesting topic is the ethics of AI, including issues such as bias and privacy. As AI becomes more advanced, it is important to consider the potential risks and benefits of this technology.

When writing an essay on artificial intelligence, it is essential to choose a specific topic and research it thoroughly. This will help you to develop a clear understanding of the topic and provide strong arguments to support your thesis. You can use a variety of sources, including academic journals, news articles, and books, to gather information and support your ideas.

An essay about AI should also consider the future of this technology. With advancements in machine learning and robotics, the possibilities for AI are endless. Your essay could explore the potential impact of AI on society in the coming years and decades.

In summary, an artificial intelligence essay can cover a broad range of topics, from the technical details of AI to its ethical implications. By choosing a specific topic and conducting thorough research, you can develop a compelling essay that provides valuable insights into this exciting field. If you need inspiration or guidance, you can find numerous artificial intelligence topics for essay and essays about AI on WritingBros.

The Issue of Artificial Intelligence and Intrusion of Privacy

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The Rapid Ascent of ChatGPT and the Dawn of Human-Level AI

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Artificial Intelligence and the Rise of the Unemployment Rate Worldwide

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Artificial Intelligence and Its Effects on Labor Power

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Benefits Of Using Artificial Intelligence For Humanity

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Best topics on Artificial Intelligence

1. The Issue of Artificial Intelligence and Intrusion of Privacy

2. The Future Unveiled: Exploring the Landscape of Artificial Intelligence

3. The Rapid Ascent of ChatGPT and the Dawn of Human-Level AI

4. Artificial Intelligence and the Rise of the Unemployment Rate Worldwide

5. Artificial Intelligence and Its Effects on Labor Power

6. Future of Artificial Intelligence: Safe AI Development

7. How Artificial Intelligence Will Change the Future of Work and Technology

8. Future of Artificial Intelligence and the Strategies of Its Use in Business

9. Debate on How Artificial Intelligence Will Change the Future

10. Why Artificial Intelligence Can’t Replace Human

11. Ethics of Artificial Intelligence, Machine Morality

12. Benefits of Artificial Intelligence for the Environment

13. Benefits Of Using Artificial Intelligence For Humanity

14. People Living Under the Influence of the Matrix

15. AI Applications in Cardiology, Radiology, CT and MR Images: A Review

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• Class Reflection
• Negative Impact of Technology
• Disadvantages of Technology
• A Day Without Technology

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• Artificial Intelligence Essay

Essay on Artificial Intelligence

Artificial Intelligence is the intelligence possessed by the machines under which they can perform various functions with human help. With the help of A.I, machines will be able to learn, solve problems, plan things, think, etc. Artificial Intelligence, for example, is the simulation of human intelligence by machines. In the field of technology, Artificial Intelligence is evolving rapidly day by day and it is believed that in the near future, artificial intelligence is going to change human life very drastically and will most probably end all the crises of the world by sorting out the major problems. 

Our life in this modern age depends largely on computers. It is almost impossible to think about life without computers. We need computers in everything that we use in our daily lives. So it becomes very important to make computers intelligent so that our lives become easy. Artificial Intelligence is the theory and development of computers, which imitates the human intelligence and senses, such as visual perception, speech recognition, decision-making, and translation between languages. Artificial Intelligence has brought a revolution in the world of technology. 

Artificial Intelligence Applications

AI is widely used in the field of healthcare. Companies are attempting to develop technologies that will allow for rapid diagnosis. Artificial Intelligence would be able to operate on patients without the need for human oversight. Surgical procedures based on technology are already being performed.

Artificial Intelligence would save a lot of our time. The use of robots would decrease human labour. For example, in industries robots are used which have saved a lot of human effort and time. 

In the field of education, AI has the potential to be very effective. It can bring innovative ways of teaching students with the help of which students will be able to learn the concepts better. 

Artificial intelligence is the future of innovative technology as we can use it in many fields. For example, it can be used in the Military sector, Industrial sector, Automobiles, etc. In the coming years, we will be able to see more applications of AI as this technology is evolving day by day. 

Marketing: Artificial Intelligence provides a deep knowledge of consumers and potential clients to the marketers by enabling them to deliver information at the right time. Through AI solutions, the marketers can refine their campaigns and strategies.

Agriculture: AI technology can be used to detect diseases in plants, pests, and poor plant nutrition. With the help of AI, farmers can analyze the weather conditions, temperature, water usage, and condition of the soil.

Banking: Fraudulent activities can be detected through AI solutions. AI bots, digital payment advisers can create a high quality of service.

Health Care: Artificial Intelligence can surpass human cognition in the analysis, diagnosis, and complication of complicated medical data.

History of Artificial Intelligence

Artificial Intelligence may seem to be a new technology but if we do a bit of research, we will find that it has roots deep in the past. In Greek Mythology, it is said that the concepts of AI were used. 

The model of Artificial neurons was first brought forward in 1943 by Warren McCulloch and Walter Pits. After seven years, in 1950, a research paper related to AI was published by Alan Turing which was titled 'Computer Machinery and Intelligence. The term Artificial Intelligence was first coined in 1956 by John McCarthy, who is known as the father of Artificial Intelligence. 

To conclude, we can say that Artificial Intelligence will be the future of the world. As per the experts, we won't be able to separate ourselves from this technology as it would become an integral part of our lives shortly. AI would change the way we live in this world. This technology would prove to be revolutionary because it will change our lives for good. 

Branches of Artificial Intelligence:

Knowledge Engineering

Machines Learning

Natural Language Processing

Types of Artificial Intelligence

Artificial Intelligence is categorized in two types based on capabilities and functionalities. 

Artificial Intelligence Type-1

Artificial intelligence type-2.

Narrow AI (weak AI): This is designed to perform a specific task with intelligence. It is termed as weak AI because it cannot perform beyond its limitations. It is trained to do a specific task. Some examples of Narrow AI are facial recognition (Siri in Apple phones), speech, and image recognition. IBM’s Watson supercomputer, self-driving cars, playing chess, and solving equations are also some of the examples of weak AI.

General AI (AGI or strong AI): This system can perform nearly every cognitive task as efficiently as humans can do. The main characteristic of general AI is to make a system that can think like a human on its own. This is a long-term goal of many researchers to create such machines.

Super AI: Super AI is a type of intelligence of systems in which machines can surpass human intelligence and can perform any cognitive task better than humans. The main features of strong AI would be the ability to think, reason, solve puzzles, make judgments, plan and communicate on its own. The creation of strong AI might be the biggest revolution in human history.

Reactive Machines: These machines are the basic types of AI. Such AI systems focus only on current situations and react as per the best possible action. They do not store memories for future actions. IBM’s deep blue system and Google’s Alpha go are the examples of reactive machines.

Limited Memory: These machines can store data or past memories for a short period of time. Examples are self-driving cars. They can store information to navigate the road, speed, and distance of nearby cars.

Theory of Mind: These systems understand emotions, beliefs, and requirements like humans. These kinds of machines are still not invented and it’s a long-term goal for the researchers to create one. 

Self-Awareness: Self-awareness AI is the future of artificial intelligence. These machines can outsmart the humans. If these machines are invented then it can bring a revolution in human society. 

Artificial Intelligence will bring a huge revolution in the history of mankind. Human civilization will flourish by amplifying human intelligence with artificial intelligence, as long as we manage to keep the technology beneficial.

FAQs on Artificial Intelligence Essay

1. What is Artificial Intelligence?

Artificial Intelligence is a branch of computer science that emphasizes the development of intelligent machines that would think and work like humans.

2. How is Artificial Intelligence Categorised?

Artificial Intelligence is categorized in two types based on capabilities and functionalities. Based on capabilities, AI includes Narrow AI (weak AI), General AI, and super AI. Based on functionalities, AI includes Relative Machines, limited memory, theory of mind, self-awareness.

3. How Does AI Help in Marketing?

AI helps marketers to strategize their marketing campaigns and keep data of their prospective clients and consumers.

4. Give an Example of a Relative Machine?

IBM’s deep blue system and Google’s Alpha go are examples of reactive machines.

5. How can Artificial Intelligence help us?

Artificial Intelligence can help us in many ways. It is already helping us in some cases. For example, if we think about the robots used in a factory, they all run on the principle of Artificial Intelligence. In the automobile sector, some vehicles have been invented that don't need any humans to drive them, they are self-driving. The search engines these days are also AI-powered. There are many other uses of Artificial Intelligence as well.

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• Artificial Intelligence and the Future of Humans

Experts say the rise of artificial intelligence will make most people better off over the next decade, but many have concerns about how advances in AI will affect what it means to be human, to be productive and to exercise free will

Table of contents.

• 1. Concerns about human agency, evolution and survival
• 2. Solutions to address AI’s anticipated negative impacts
• 3. Improvements ahead: How humans and AI might evolve together in the next decade
• About this canvassing of experts
• Acknowledgments

Digital life is augmenting human capacities and disrupting eons-old human activities. Code-driven systems have spread to more than half of the world’s inhabitants in ambient information and connectivity, offering previously unimagined opportunities and unprecedented threats. As emerging algorithm-driven artificial intelligence (AI) continues to spread, will people be better off than they are today?

Some 979 technology pioneers, innovators, developers, business and policy leaders, researchers and activists answered this question in a canvassing of experts conducted in the summer of 2018.

The experts predicted networked artificial intelligence will amplify human effectiveness but also threaten human autonomy, agency and capabilities. They spoke of the wide-ranging possibilities; that computers might match or even exceed human intelligence and capabilities on tasks such as complex decision-making, reasoning and learning, sophisticated analytics and pattern recognition, visual acuity, speech recognition and language translation. They said “smart” systems in communities, in vehicles, in buildings and utilities, on farms and in business processes will save time, money and lives and offer opportunities for individuals to enjoy a more-customized future.

Many focused their optimistic remarks on health care and the many possible applications of AI in diagnosing and treating patients or helping senior citizens live fuller and healthier lives. They were also enthusiastic about AI’s role in contributing to broad public-health programs built around massive amounts of data that may be captured in the coming years about everything from personal genomes to nutrition. Additionally, a number of these experts predicted that AI would abet long-anticipated changes in formal and informal education systems.

Yet, most experts, regardless of whether they are optimistic or not, expressed concerns about the long-term impact of these new tools on the essential elements of being human. All respondents in this non-scientific canvassing were asked to elaborate on why they felt AI would leave people better off or not. Many shared deep worries, and many also suggested pathways toward solutions. The main themes they sounded about threats and remedies are outlined in the accompanying table.

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Specifically, participants were asked to consider the following:

“Please think forward to the year 2030. Analysts expect that people will become even more dependent on networked artificial intelligence (AI) in complex digital systems. Some say we will continue on the historic arc of augmenting our lives with mostly positive results as we widely implement these networked tools. Some say our increasing dependence on these AI and related systems is likely to lead to widespread difficulties.

Our question: By 2030, do you think it is most likely that advancing AI and related technology systems will enhance human capacities and empower them? That is, most of the time, will most people be better off than they are today? Or is it most likely that advancing AI and related technology systems will lessen human autonomy and agency to such an extent that most people will not be better off than the way things are today?”

Overall, and despite the downsides they fear, 63% of respondents in this canvassing said they are hopeful that most individuals will be mostly better off in 2030, and 37% said people will not be better off.

A number of the thought leaders who participated in this canvassing said humans’ expanding reliance on technological systems will only go well if close attention is paid to how these tools, platforms and networks are engineered, distributed and updated. Some of the powerful, overarching answers included those from:

Sonia Katyal , co-director of the Berkeley Center for Law and Technology and a member of the inaugural U.S. Commerce Department Digital Economy Board of Advisors, predicted, “In 2030, the greatest set of questions will involve how perceptions of AI and their application will influence the trajectory of civil rights in the future. Questions about privacy, speech, the right of assembly and technological construction of personhood will all re-emerge in this new AI context, throwing into question our deepest-held beliefs about equality and opportunity for all. Who will benefit and who will be disadvantaged in this new world depends on how broadly we analyze these questions today, for the future.”

We need to work aggressively to make sure technology matches our values. Erik Brynjolfsson Erik Brynjolfsson

Erik Brynjolfsson , director of the MIT Initiative on the Digital Economy and author of “Machine, Platform, Crowd: Harnessing Our Digital Future,” said, “AI and related technologies have already achieved superhuman performance in many areas, and there is little doubt that their capabilities will improve, probably very significantly, by 2030. … I think it is more likely than not that we will use this power to make the world a better place. For instance, we can virtually eliminate global poverty, massively reduce disease and provide better education to almost everyone on the planet. That said, AI and ML [machine learning] can also be used to increasingly concentrate wealth and power, leaving many people behind, and to create even more horrifying weapons. Neither outcome is inevitable, so the right question is not ‘What will happen?’ but ‘What will we choose to do?’ We need to work aggressively to make sure technology matches our values. This can and must be done at all levels, from government, to business, to academia, and to individual choices.”

Bryan Johnson , founder and CEO of Kernel, a leading developer of advanced neural interfaces, and OS Fund, a venture capital firm, said, “I strongly believe the answer depends on whether we can shift our economic systems toward prioritizing radical human improvement and staunching the trend toward human irrelevance in the face of AI. I don’t mean just jobs; I mean true, existential irrelevance, which is the end result of not prioritizing human well-being and cognition.”

Marina Gorbis , executive director of the Institute for the Future, said, “Without significant changes in our political economy and data governance regimes [AI] is likely to create greater economic inequalities, more surveillance and more programmed and non-human-centric interactions. Every time we program our environments, we end up programming ourselves and our interactions. Humans have to become more standardized, removing serendipity and ambiguity from our interactions. And this ambiguity and complexity is what is the essence of being human.”

Judith Donath , author of “The Social Machine, Designs for Living Online” and faculty fellow at Harvard University’s Berkman Klein Center for Internet & Society, commented, “By 2030, most social situations will be facilitated by bots – intelligent-seeming programs that interact with us in human-like ways. At home, parents will engage skilled bots to help kids with homework and catalyze dinner conversations. At work, bots will run meetings. A bot confidant will be considered essential for psychological well-being, and we’ll increasingly turn to such companions for advice ranging from what to wear to whom to marry. We humans care deeply about how others see us – and the others whose approval we seek will increasingly be artificial. By then, the difference between humans and bots will have blurred considerably. Via screen and projection, the voice, appearance and behaviors of bots will be indistinguishable from those of humans, and even physical robots, though obviously non-human, will be so convincingly sincere that our impression of them as thinking, feeling beings, on par with or superior to ourselves, will be unshaken. Adding to the ambiguity, our own communication will be heavily augmented: Programs will compose many of our messages and our online/AR appearance will [be] computationally crafted. (Raw, unaided human speech and demeanor will seem embarrassingly clunky, slow and unsophisticated.) Aided by their access to vast troves of data about each of us, bots will far surpass humans in their ability to attract and persuade us. Able to mimic emotion expertly, they’ll never be overcome by feelings: If they blurt something out in anger, it will be because that behavior was calculated to be the most efficacious way of advancing whatever goals they had ‘in mind.’ But what are those goals? Artificially intelligent companions will cultivate the impression that social goals similar to our own motivate them – to be held in good regard, whether as a beloved friend, an admired boss, etc. But their real collaboration will be with the humans and institutions that control them. Like their forebears today, these will be sellers of goods who employ them to stimulate consumption and politicians who commission them to sway opinions.”

Andrew McLaughlin , executive director of the Center for Innovative Thinking at Yale University, previously deputy chief technology officer of the United States for President Barack Obama and global public policy lead for Google, wrote, “2030 is not far in the future. My sense is that innovations like the internet and networked AI have massive short-term benefits, along with long-term negatives that can take decades to be recognizable. AI will drive a vast range of efficiency optimizations but also enable hidden discrimination and arbitrary penalization of individuals in areas like insurance, job seeking and performance assessment.”

Michael M. Roberts , first president and CEO of the Internet Corporation for Assigned Names and Numbers (ICANN) and Internet Hall of Fame member, wrote, “The range of opportunities for intelligent agents to augment human intelligence is still virtually unlimited. The major issue is that the more convenient an agent is, the more it needs to know about you – preferences, timing, capacities, etc. – which creates a tradeoff of more help requires more intrusion. This is not a black-and-white issue – the shades of gray and associated remedies will be argued endlessly. The record to date is that convenience overwhelms privacy. I suspect that will continue.”

danah boyd , a principal researcher for Microsoft and founder and president of the Data & Society Research Institute, said, “AI is a tool that will be used by humans for all sorts of purposes, including in the pursuit of power. There will be abuses of power that involve AI, just as there will be advances in science and humanitarian efforts that also involve AI. Unfortunately, there are certain trend lines that are likely to create massive instability. Take, for example, climate change and climate migration. This will further destabilize Europe and the U.S., and I expect that, in panic, we will see AI be used in harmful ways in light of other geopolitical crises.”

Amy Webb , founder of the Future Today Institute and professor of strategic foresight at New York University, commented, “The social safety net structures currently in place in the U.S. and in many other countries around the world weren’t designed for our transition to AI. The transition through AI will last the next 50 years or more. As we move farther into this third era of computing, and as every single industry becomes more deeply entrenched with AI systems, we will need new hybrid-skilled knowledge workers who can operate in jobs that have never needed to exist before. We’ll need farmers who know how to work with big data sets. Oncologists trained as robotocists. Biologists trained as electrical engineers. We won’t need to prepare our workforce just once, with a few changes to the curriculum. As AI matures, we will need a responsive workforce, capable of adapting to new processes, systems and tools every few years. The need for these fields will arise faster than our labor departments, schools and universities are acknowledging. It’s easy to look back on history through the lens of present – and to overlook the social unrest caused by widespread technological unemployment. We need to address a difficult truth that few are willing to utter aloud: AI will eventually cause a large number of people to be permanently out of work. Just as generations before witnessed sweeping changes during and in the aftermath of the Industrial Revolution, the rapid pace of technology will likely mean that Baby Boomers and the oldest members of Gen X – especially those whose jobs can be replicated by robots – won’t be able to retrain for other kinds of work without a significant investment of time and effort.”

Barry Chudakov , founder and principal of Sertain Research, commented, “By 2030 the human-machine/AI collaboration will be a necessary tool to manage and counter the effects of multiple simultaneous accelerations: broad technology advancement, globalization, climate change and attendant global migrations. In the past, human societies managed change through gut and intuition, but as Eric Teller, CEO of Google X, has said, ‘Our societal structures are failing to keep pace with the rate of change.’ To keep pace with that change and to manage a growing list of ‘wicked problems’ by 2030, AI – or using Joi Ito’s phrase, extended intelligence – will value and revalue virtually every area of human behavior and interaction. AI and advancing technologies will change our response framework and time frames (which in turn, changes our sense of time). Where once social interaction happened in places – work, school, church, family environments – social interactions will increasingly happen in continuous, simultaneous time. If we are fortunate, we will follow the 23 Asilomar AI Principles outlined by the Future of Life Institute and will work toward ‘not undirected intelligence but beneficial intelligence.’ Akin to nuclear deterrence stemming from mutually assured destruction, AI and related technology systems constitute a force for a moral renaissance. We must embrace that moral renaissance, or we will face moral conundrums that could bring about human demise. … My greatest hope for human-machine/AI collaboration constitutes a moral and ethical renaissance – we adopt a moonshot mentality and lock arms to prepare for the accelerations coming at us. My greatest fear is that we adopt the logic of our emerging technologies – instant response, isolation behind screens, endless comparison of self-worth, fake self-presentation – without thinking or responding smartly.”

John C. Havens , executive director of the IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems and the Council on Extended Intelligence, wrote, “Now, in 2018, a majority of people around the world can’t access their data, so any ‘human-AI augmentation’ discussions ignore the critical context of who actually controls people’s information and identity. Soon it will be extremely difficult to identify any autonomous or intelligent systems whose algorithms don’t interact with human data in one form or another.”

At stake is nothing less than what sort of society we want to live in and how we experience our humanity. Batya Friedman Batya Friedman

Batya Friedman , a human-computer interaction professor at the University of Washington’s Information School, wrote, “Our scientific and technological capacities have and will continue to far surpass our moral ones – that is our ability to use wisely and humanely the knowledge and tools that we develop. … Automated warfare – when autonomous weapons kill human beings without human engagement – can lead to a lack of responsibility for taking the enemy’s life or even knowledge that an enemy’s life has been taken. At stake is nothing less than what sort of society we want to live in and how we experience our humanity.”

Greg Shannon , chief scientist for the CERT Division at Carnegie Mellon University, said, “Better/worse will appear 4:1 with the long-term ratio 2:1. AI will do well for repetitive work where ‘close’ will be good enough and humans dislike the work. … Life will definitely be better as AI extends lifetimes, from health apps that intelligently ‘nudge’ us to health, to warnings about impending heart/stroke events, to automated health care for the underserved (remote) and those who need extended care (elder care). As to liberty, there are clear risks. AI affects agency by creating entities with meaningful intellectual capabilities for monitoring, enforcing and even punishing individuals. Those who know how to use it will have immense potential power over those who don’t/can’t. Future happiness is really unclear. Some will cede their agency to AI in games, work and community, much like the opioid crisis steals agency today. On the other hand, many will be freed from mundane, unengaging tasks/jobs. If elements of community happiness are part of AI objective functions, then AI could catalyze an explosion of happiness.”

Kostas Alexandridis , author of “Exploring Complex Dynamics in Multi-agent-based Intelligent Systems,” predicted, “Many of our day-to-day decisions will be automated with minimal intervention by the end-user. Autonomy and/or independence will be sacrificed and replaced by convenience. Newer generations of citizens will become more and more dependent on networked AI structures and processes. There are challenges that need to be addressed in terms of critical thinking and heterogeneity. Networked interdependence will, more likely than not, increase our vulnerability to cyberattacks. There is also a real likelihood that there will exist sharper divisions between digital ‘haves’ and ‘have-nots,’ as well as among technologically dependent digital infrastructures. Finally, there is the question of the new ‘commanding heights’ of the digital network infrastructure’s ownership and control.”

Oscar Gandy , emeritus professor of communication at the University of Pennsylvania, responded, “We already face an ungranted assumption when we are asked to imagine human-machine ‘collaboration.’ Interaction is a bit different, but still tainted by the grant of a form of identity – maybe even personhood – to machines that we will use to make our way through all sorts of opportunities and challenges. The problems we will face in the future are quite similar to the problems we currently face when we rely upon ‘others’ (including technological systems, devices and networks) to acquire things we value and avoid those other things (that we might, or might not be aware of).”

James Scofield O’Rourke , a professor of management at the University of Notre Dame, said, “Technology has, throughout recorded history, been a largely neutral concept. The question of its value has always been dependent on its application. For what purpose will AI and other technological advances be used? Everything from gunpowder to internal combustion engines to nuclear fission has been applied in both helpful and destructive ways. Assuming we can contain or control AI (and not the other way around), the answer to whether we’ll be better off depends entirely on us (or our progeny). ‘The fault, dear Brutus, is not in our stars, but in ourselves, that we are underlings.’”

Simon Biggs , a professor of interdisciplinary arts at the University of Edinburgh, said, “AI will function to augment human capabilities. The problem is not with AI but with humans. As a species we are aggressive, competitive and lazy. We are also empathic, community minded and (sometimes) self-sacrificing. We have many other attributes. These will all be amplified. Given historical precedent, one would have to assume it will be our worst qualities that are augmented. My expectation is that in 2030 AI will be in routine use to fight wars and kill people, far more effectively than we can currently kill. As societies we will be less affected by this as we currently are, as we will not be doing the fighting and killing ourselves. Our capacity to modify our behaviour, subject to empathy and an associated ethical framework, will be reduced by the disassociation between our agency and the act of killing. We cannot expect our AI systems to be ethical on our behalf – they won’t be, as they will be designed to kill efficiently, not thoughtfully. My other primary concern is to do with surveillance and control. The advent of China’s Social Credit System (SCS) is an indicator of what it likely to come. We will exist within an SCS as AI constructs hybrid instances of ourselves that may or may not resemble who we are. But our rights and affordances as individuals will be determined by the SCS. This is the Orwellian nightmare realised.”

Mark Surman , executive director of the Mozilla Foundation, responded, “AI will continue to concentrate power and wealth in the hands of a few big monopolies based on the U.S. and China. Most people – and parts of the world – will be worse off.”

William Uricchio , media scholar and professor of comparative media studies at MIT, commented, “AI and its related applications face three problems: development at the speed of Moore’s Law, development in the hands of a technological and economic elite, and development without benefit of an informed or engaged public. The public is reduced to a collective of consumers awaiting the next technology. Whose notion of ‘progress’ will prevail? We have ample evidence of AI being used to drive profits, regardless of implications for long-held values; to enhance governmental control and even score citizens’ ‘social credit’ without input from citizens themselves. Like technologies before it, AI is agnostic. Its deployment rests in the hands of society. But absent an AI-literate public, the decision of how best to deploy AI will fall to special interests. Will this mean equitable deployment, the amelioration of social injustice and AI in the public service? Because the answer to this question is social rather than technological, I’m pessimistic. The fix? We need to develop an AI-literate public, which means focused attention in the educational sector and in public-facing media. We need to assure diversity in the development of AI technologies. And until the public, its elected representatives and their legal and regulatory regimes can get up to speed with these fast-moving developments we need to exercise caution and oversight in AI’s development.”

The remainder of this report is divided into three sections that draw from hundreds of additional respondents’ hopeful and critical observations: 1) concerns about human-AI evolution, 2) suggested solutions to address AI’s impact, and 3) expectations of what life will be like in 2030, including respondents’ positive outlooks on the quality of life and the future of work, health care and education. Some responses are lightly edited for style.

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The Intelligence Age

In the next couple of decades, we will be able to do things that would have seemed like magic to our grandparents.

This phenomenon is not new, but it will be newly accelerated. People have become dramatically more capable over time; we can already accomplish things now that our predecessors would have believed to be impossible.

We are more capable not because of genetic change, but because we benefit from the infrastructure of society being way smarter and more capable than any one of us; in an important sense, society itself is a form of advanced intelligence. Our grandparents – and the generations that came before them – built and achieved great things. They contributed to the scaffolding of human progress that we all benefit from. AI will give people tools to solve hard problems and help us add new struts to that scaffolding that we couldn’t have figured out on our own. The story of progress will continue, and our children will be able to do things we can’t.

It won’t happen all at once, but we’ll soon be able to work with AI that helps us accomplish much more than we ever could without AI; eventually we can each have a personal AI team, full of virtual experts in different areas, working together to create almost anything we can imagine. Our children will have virtual tutors who can provide personalized instruction in any subject, in any language, and at whatever pace they need. We can imagine similar ideas for better healthcare, the ability to create any kind of software someone can imagine, and much more.

With these new abilities, we can have shared prosperity to a degree that seems unimaginable today; in the future, everyone’s lives can be better than anyone’s life is now. Prosperity alone doesn’t necessarily make people happy – there are plenty of miserable rich people – but it would meaningfully improve the lives of people around the world.

Here is one narrow way to look at human history: after thousands of years of compounding scientific discovery and technological progress, we have figured out how to melt sand, add some impurities, arrange it with astonishing precision at extraordinarily tiny scale into computer chips, run energy through it, and end up with systems capable of creating increasingly capable artificial intelligence.

This may turn out to be the most consequential fact about all of history so far. It is possible that we will have superintelligence in a few thousand days (!); it may take longer, but I’m confident we’ll get there.

How did we get to the doorstep of the next leap in prosperity?

In three words: deep learning worked.

In 15 words: deep learning worked, got predictably better with scale, and we dedicated increasing resources to it.

That’s really it; humanity discovered an algorithm that could really, truly learn any distribution of data (or really, the underlying “rules” that produce any distribution of data). To a shocking degree of precision, the more compute and data available, the better it gets at helping people solve hard problems. I find that no matter how much time I spend thinking about this, I can never really internalize how consequential it is.

There are a lot of details we still have to figure out, but it’s a mistake to get distracted by any particular challenge. Deep learning works, and we will solve the remaining problems. We can say a lot of things about what may happen next, but the main one is that AI is going to get better with scale, and that will lead to meaningful improvements to the lives of people around the world.

AI models will soon serve as autonomous personal assistants who carry out specific tasks on our behalf like coordinating medical care on your behalf. At some point further down the road, AI systems are going to get so good that they help us make better next-generation systems and make scientific progress across the board.

Technology brought us from the Stone Age to the Agricultural Age and then to the Industrial Age. From here, the path to the Intelligence Age is paved with compute, energy, and human will.

If we want to put AI into the hands of as many people as possible, we need to drive down the cost of compute and make it abundant (which requires lots of energy and chips). If we don’t build enough infrastructure, AI will be a very limited resource that wars get fought over and that becomes mostly a tool for rich people.

We need to act wisely but with conviction. The dawn of the Intelligence Age is a momentous development with very complex and extremely high-stakes challenges. It will not be an entirely positive story, but the upside is so tremendous that we owe it to ourselves, and the future, to figure out how to navigate the risks in front of us.

I believe the future is going to be so bright that no one can do it justice by trying to write about it now; a defining characteristic of the Intelligence Age will be massive prosperity.

Although it will happen incrementally, astounding triumphs – fixing the climate, establishing a space colony, and the discovery of all of physics – will eventually become commonplace. With nearly-limitless intelligence and abundant energy – the ability to generate great ideas, and the ability to make them happen – we can do quite a lot.

As we have seen with other technologies, there will also be downsides, and we need to start working now to maximize AI’s benefits while minimizing its harms. As one example, we expect that this technology can cause a significant change in labor markets (good and bad) in the coming years, but most jobs will change more slowly than most people think, and I have no fear that we’ll run out of things to do (even if they don’t look like “real jobs” to us today). People have an innate desire to create and to be useful to each other, and AI will allow us to amplify our own abilities like never before. As a society, we will be back in an expanding world, and we can again focus on playing positive-sum games.

Many of the jobs we do today would have looked like trifling wastes of time to people a few hundred years ago, but nobody is looking back at the past, wishing they were a lamplighter. If a lamplighter could see the world today, he would think the prosperity all around him was unimaginable. And if we could fast-forward a hundred years from today, the prosperity all around us would feel just as unimaginable.

The College Essay Is Dead

Nobody is prepared for how AI will transform academia.

Suppose you are a professor of pedagogy, and you assign an essay on learning styles. A student hands in an essay with the following opening paragraph:

The construct of “learning styles” is problematic because it fails to account for the processes through which learning styles are shaped. Some students might develop a particular learning style because they have had particular experiences. Others might develop a particular learning style by trying to accommodate to a learning environment that was not well suited to their learning needs. Ultimately, we need to understand the interactions among learning styles and environmental and personal factors, and how these shape how we learn and the kinds of learning we experience.

Pass or fail? A- or B+? And how would your grade change if you knew a human student hadn’t written it at all? Because Mike Sharples, a professor in the U.K., used GPT-3, a large language model from OpenAI that automatically generates text from a prompt, to write it. (The whole essay, which Sharples considered graduate-level, is available, complete with references, here .) Personally, I lean toward a B+. The passage reads like filler, but so do most student essays.

Sharples’s intent was to urge educators to “rethink teaching and assessment” in light of the technology, which he said “could become a gift for student cheats, or a powerful teaching assistant, or a tool for creativity.” Essay generation is neither theoretical nor futuristic at this point. In May, a student in New Zealand confessed to using AI to write their papers, justifying it as a tool like Grammarly or spell-check: ​​“I have the knowledge, I have the lived experience, I’m a good student, I go to all the tutorials and I go to all the lectures and I read everything we have to read but I kind of felt I was being penalised because I don’t write eloquently and I didn’t feel that was right,” they told a student paper in Christchurch. They don’t feel like they’re cheating, because the student guidelines at their university state only that you’re not allowed to get somebody else to do your work for you. GPT-3 isn’t “somebody else”—it’s a program.

The world of generative AI is progressing furiously. Last week, OpenAI released an advanced chatbot named ChatGPT that has spawned a new wave of marveling and hand-wringing , plus an upgrade to GPT-3 that allows for complex rhyming poetry; Google previewed new applications last month that will allow people to describe concepts in text and see them rendered as images; and the creative-AI firm Jasper received a $1.5 billion valuation in October. It still takes a little initiative for a kid to find a text generator, but not for long.

The essay, in particular the undergraduate essay, has been the center of humanistic pedagogy for generations. It is the way we teach children how to research, think, and write. That entire tradition is about to be disrupted from the ground up. Kevin Bryan, an associate professor at the University of Toronto, tweeted in astonishment about OpenAI’s new chatbot last week: “You can no longer give take-home exams/homework … Even on specific questions that involve combining knowledge across domains, the OpenAI chat is frankly better than the average MBA at this point. It is frankly amazing.” Neither the engineers building the linguistic tech nor the educators who will encounter the resulting language are prepared for the fallout.

A chasm has existed between humanists and technologists for a long time. In the 1950s, C. P. Snow gave his famous lecture, later the essay “The Two Cultures,” describing the humanistic and scientific communities as tribes losing contact with each other. “Literary intellectuals at one pole—at the other scientists,” Snow wrote. “Between the two a gulf of mutual incomprehension—sometimes (particularly among the young) hostility and dislike, but most of all lack of understanding. They have a curious distorted image of each other.” Snow’s argument was a plea for a kind of intellectual cosmopolitanism: Literary people were missing the essential insights of the laws of thermodynamics, and scientific people were ignoring the glories of Shakespeare and Dickens.

The rupture that Snow identified has only deepened. In the modern tech world, the value of a humanistic education shows up in evidence of its absence. Sam Bankman-Fried, the disgraced founder of the crypto exchange FTX who recently lost his $16 billion fortune in a few days , is a famously proud illiterate. “I would never read a book,” he once told an interviewer . “I don’t want to say no book is ever worth reading, but I actually do believe something pretty close to that.” Elon Musk and Twitter are another excellent case in point. It’s painful and extraordinary to watch the ham-fisted way a brilliant engineering mind like Musk deals with even relatively simple literary concepts such as parody and satire. He obviously has never thought about them before. He probably didn’t imagine there was much to think about.

The extraordinary ignorance on questions of society and history displayed by the men and women reshaping society and history has been the defining feature of the social-media era. Apparently, Mark Zuckerberg has read a great deal about Caesar Augustus , but I wish he’d read about the regulation of the pamphlet press in 17th-century Europe. It might have spared America the annihilation of social trust .

These failures don’t derive from mean-spiritedness or even greed, but from a willful obliviousness. The engineers do not recognize that humanistic questions—like, say, hermeneutics or the historical contingency of freedom of speech or the genealogy of morality—are real questions with real consequences. Everybody is entitled to their opinion about politics and culture, it’s true, but an opinion is different from a grounded understanding. The most direct path to catastrophe is to treat complex problems as if they’re obvious to everyone. You can lose billions of dollars pretty quickly that way.

As the technologists have ignored humanistic questions to their peril, the humanists have greeted the technological revolutions of the past 50 years by committing soft suicide. As of 2017, the number of English majors had nearly halved since the 1990s. History enrollments have declined by 45 percent since 2007 alone. Needless to say, humanists’ understanding of technology is partial at best. The state of digital humanities is always several categories of obsolescence behind, which is inevitable. (Nobody expects them to teach via Instagram Stories.) But more crucially, the humanities have not fundamentally changed their approach in decades, despite technology altering the entire world around them. They are still exploding meta-narratives like it’s 1979, an exercise in self-defeat.

Read: The humanities are in crisis

Contemporary academia engages, more or less permanently, in self-critique on any and every front it can imagine. In a tech-centered world, language matters, voice and style matter, the study of eloquence matters, history matters, ethical systems matter. But the situation requires humanists to explain why they matter, not constantly undermine their own intellectual foundations. The humanities promise students a journey to an irrelevant, self-consuming future; then they wonder why their enrollments are collapsing. Is it any surprise that nearly half of humanities graduates regret their choice of major ?

The case for the value of humanities in a technologically determined world has been made before. Steve Jobs always credited a significant part of Apple’s success to his time as a dropout hanger-on at Reed College, where he fooled around with Shakespeare and modern dance, along with the famous calligraphy class that provided the aesthetic basis for the Mac’s design. “A lot of people in our industry haven’t had very diverse experiences. So they don’t have enough dots to connect, and they end up with very linear solutions without a broad perspective on the problem,” Jobs said . “The broader one’s understanding of the human experience, the better design we will have.” Apple is a humanistic tech company. It’s also the largest company in the world.

Despite the clear value of a humanistic education, its decline continues. Over the past 10 years, STEM has triumphed, and the humanities have collapsed . The number of students enrolled in computer science is now nearly the same as the number of students enrolled in all of the humanities combined.

And now there’s GPT-3. Natural-language processing presents the academic humanities with a whole series of unprecedented problems. Practical matters are at stake: Humanities departments judge their undergraduate students on the basis of their essays. They give Ph.D.s on the basis of a dissertation’s composition. What happens when both processes can be significantly automated? Going by my experience as a former Shakespeare professor, I figure it will take 10 years for academia to face this new reality: two years for the students to figure out the tech, three more years for the professors to recognize that students are using the tech, and then five years for university administrators to decide what, if anything, to do about it. Teachers are already some of the most overworked, underpaid people in the world. They are already dealing with a humanities in crisis. And now this. I feel for them.

And yet, despite the drastic divide of the moment, natural-language processing is going to force engineers and humanists together. They are going to need each other despite everything. Computer scientists will require basic, systematic education in general humanism: The philosophy of language, sociology, history, and ethics are not amusing questions of theoretical speculation anymore. They will be essential in determining the ethical and creative use of chatbots, to take only an obvious example.

The humanists will need to understand natural-language processing because it’s the future of language, but also because there is more than just the possibility of disruption here. Natural-language processing can throw light on a huge number of scholarly problems. It is going to clarify matters of attribution and literary dating that no system ever devised will approach; the parameters in large language models are much more sophisticated than the current systems used to determine which plays Shakespeare wrote, for example . It may even allow for certain types of restorations, filling the gaps in damaged texts by means of text-prediction models. It will reformulate questions of literary style and philology; if you can teach a machine to write like Samuel Taylor Coleridge, that machine must be able to inform you, in some way, about how Samuel Taylor Coleridge wrote.

The connection between humanism and technology will require people and institutions with a breadth of vision and a commitment to interests that transcend their field. Before that space for collaboration can exist, both sides will have to take the most difficult leaps for highly educated people: Understand that they need the other side, and admit their basic ignorance. But that’s always been the beginning of wisdom, no matter what technological era we happen to inhabit.

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Artificial Intelligence (AI) and Information Literacy: How Do I Cite AI Correctly?

• Explore Different Types of AI
• Using AI carefully and thoughtfully
• Why AIs Are Bad at Math
• Fact-Checking AI with Lateral Reading
• Beyond Fact-Checking

How Do I Cite AI Correctly?

• Further Information on AI

In This Guide

Go to these pages to learn:

How does generative AI work?

• Explore different types of AI

What does AI get wrong?

• Fact-checking AI with lateral reading
• Beyond fact-checking

How do I cite AI correctly?

Further information on AI

If you're using AI to generate text or images, you should acknowledge that in your citations, just like you would for a human author, artist, or photographer. If using AI is allowed on an assignment your teacher gives you, each time you include something AI-generated, you have to cite it. (Remember that you can only use AI on an assignment if your teacher specifically says so, and always double-check with your instructor if you have questions about AI usage or citations.) Several citation guides have released official or semi-official guidance on how to cite AI-generated content. You can cite AI in your work using the guidelines below!

Why do we cite?

Citations and their formatting might seem irritating, but they're an important part of providing reliable information to an audience. Writing gets its credibility from sourcing the claims it makes. Readers need to be able to fact-check a writer's sources and trace where the claims in a piece come from.

Citing ChatGPT and Other AI Text Generators

If you are using AI to help with a draft or outline , you'll want to acknowledge that with a sentence at the beginning or end of the paper that says something like, "This paper was produced with drafting support from Bing AI." Your teacher might have specific conventions for how they would like to list this as well, so it is always best practice to check in with them!

If you are citing a conversation with an AI tool, either as a source or as an object of study, explore each section below to learn how to cite AI text generators in different styles.

Building blocks

• Author: Do not treat the AI as an author; MLA is reserving that for human authors. Omit the author section of the citation.
• Title of source: Describe what was generated by the AI tool. If you have not included information about the prompt in the text of your essay, you need to do that here.
• Title of container: The name of the AI tool.
• Version: Name the version of the AI tool as specifically as possible.
• Date: Include the date the content was generated.
• Location: Give the URL for the tool. If possible, give the URL for the specific content. (Note: You can send someone a URL of your ChatGPT conversation. This is the URL you should use in your citation.)

"Prompt text" prompt. AI tool, version of tool, company that made the tool, date text was generated. URL.

• In-text citation: ("Describe the symbolism")
• Bibliography: “Describe the symbolism of the green light in the book The Great Gatsby by F. Scott Fitzgerald” prompt. ChatGPT, 13 Feb. version, OpenAI, 8 Mar. 2023, https://chat.openai.com/share/dccb3610-1db9-4eed-88b1-cdb06f67982a.

Check out the MLA Style Guide for more information.

• Author: Use the creator of the AI as the author (e.g. OpenAI, Google, etc.)
• Title: Use the name of the AI tool (e.g. ChatGPT, Bard)
• Description: In brackets, clarify that this is a large language model, or another specific type of generative AI.

Company that made the tool (date text was generated). AI tool (version of tool) [Large language model]. URL.

• In-text citation: (OpenAI, 2023)
• Bibliography: OpenAI. (2023). ChatGPT (Mar 14 version) [Large language model]. https://chat.openai.com/share/dccb3610-1db9-4eed-88b1-cdb06f67982a.

For more information, see APA Style Guide: How to Cite ChatGPT

Chicago ↓

In Chicago, you'll cite generative AI differently depending on whether or not you included the prompt in the text of your paper. If you included it in your paper, you don't need to repeat it in the citation.

• Author: : Treat the AI as the author. If you're footnoting quoted text, say "Text generated by [the AI tool]."
• Publisher: Use the company that created the AI (e.g. OpenAI, Google)
• Location: Give the URL for the tool. If possible, give the URL for the specific content.

Prompt already included in paper:

1. Text generated by [name of the AI tool], date, Company that made the tool, URL.

Prompt not yet included in paper:

1. [Name of the AI tool], response to "prompt," date text was generated, Company that made the tool, URL.

• Prompt already included in paper: 1. Text generated by ChatGPT, March 7, 2023, OpenAI, https://chat.openai.com/share/dccb3610-1db9-4eed-88b1-cdb06f67982a.
• Prompt not yet included in paper: 1. ChatGPT, response to “Explain how to make pizza dough from common household ingredients,” March 7, 2023, OpenAI, https://chat.openai.com/share/dccb3610-1db9-4eed-88b1-cdb06f67982a.

For more information, see Chicago Manual of Style: Citation, Documentation of Content

Citing AI-generated Images

If you're referencing or including an AI-generated image in your papers, you should include information about how it was generated. This is also required for human-created artwork and some human-created photographs. In most citation styles, you don't need to include this in the works cited, only as a caption for the image.

If you're including an AI-generated image in the body of a paper, give it a figure number (i.e. Fig. 1, Fig. 2)

• Figure number: This corresponds to the number of images you have in your paper. If this is the first image that shows up in your paper, you'd use "Fig. 1." If it's the third image, you'd use "Fig. 3", etc.
• Author: Do not treat the AI as an author; MLA is reserving that for human authors. Omit the author section of the citation. 
• Title of work: Use the full prompt, or the first several words of the prompt, in quotation marks, followed by the word "prompt."

Fig. 1. "Full prompt" prompt, Name of Tool, version of tool, Company Name, date image was generated, URL.

• Fig. 1. “Pointillist painting of a sheep in a sunny field of blue flowers” prompt, DALL-E, version 2, OpenAI, 8 Mar. 2023, labs.openai.com/Links to an external site.

Check out the MLA Style Guide for more information

As of September 2024, APA has not issued specific guidance on how to cite AI-generated images. For now, cite as you would any other image, using the guidelines APA has issued for AI-generated text.

• Date: Use the year the content was generated. .
• Description: In brackets, clarify that this is an AI image generator, or another specific type of generative AI.

In-text citation

(Company that made the AI tool, year image was generated).

Bibliography

Company that made the AI tool. (Year image was generated). Name of the AI tool, as specifically as possible. Version of the AI tool. [AI image generator]. URL..

• In-text citation: (OpenAI, 2023).
• Bibliography: OpenAI. (2023). DALL-E 2. [AI image generator]. https://openai.com/dall-e-2

Check out the APA Audiovisual Media Style Guide for more information.

The Chicago Manual of Style's website recommends you cite AI-generated images like any other image, while including both the name of the AI tool that generated the image, the company that created the AI, and the prompt that generated the image.

• Title: Use the full prompt, or the first several words of the prompt, as the title.
• Creator: Use the phrase "image generated by," followed by the company that created the tool and the name of the tool. (e.g. Canva's Text to Image).
• Date: Give the date the image was generated.

"Prompt," image generated by Company's AI Tool, date image was generated.

• “A modern office rendered as a cubist painting,” image generated by OpenAI’s DALL·E 2, March 5, 2023.

Check out the Chicago Style Guide article on images for more information.

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• Next: Further Information on AI >>
• Last Updated: Sep 26, 2024 9:54 AM
• URL: https://libguides.westsoundacademy.org/artificial-intelligence-ai-and-information-literacy

Publication Of The E.U. Regulation On Artificial Intelligence After A Long Wait

Contributor.

Artificial Intelligence (AI) has become an increasingly pervasive technology in our society, with applications ranging from personal assistance to critical decision-making in areas such as health, justice and public safety. However, the rapid development of these systems raises ethical, legal and security challenges that need to be proactively addressed. After a long period of debate and negotiations, Regulation (EU) 2024/1689 on Artificial Intelligence has finally been published recently, laying the foundations for a harmonised regulatory framework across the European Union.

The Artificial Intelligence Regulation has an eminently pioneering character compared to other existing regulations in the rest of the world. The European regulation not only establishes control mechanisms, but also promotes the sustainable development of AI, especially for small and medium-sized enterprises (SMEs); notwithstanding this, the Artificial Intelligence Regulation contains a broad definition of AI, excluding from its scope systems intended for military purposes or scientific research.

Thus, the Artificial Intelligence Regulation establishes as its main basis the respect for the following fundamental principles:

Respect for human rights: the AI Regulation must respect and protect human rights, including privacy, non-discrimination, equal treatment and dignity of persons.

Transparency and accountability: The decision-making processes of AI systems must be transparent and explainable, so that users and relevant authorities can understand how decisions are reached.

Security and reliability: AI systems must be secure and reliable, with adequate mechanisms to prevent and mitigate security risks, technical failures and algorithmic biases.

Governance and oversight: Governance and oversight bodies will be established at national and European level to ensure compliance with the Regulation and will have the power to impose sanctions in case of non-compliance.

Requirements and obligations

Taking into account the above basic principles, the AI Regulation sets out a number of requirements and obligations for companies and organisations developing and using AI systems:

Risk assessment: Before implementing an AI system, organisations should conduct a thorough assessment of the potential risks to fundamental rights, safety and well-being of individuals.

Transparency and explainability: Organisations must provide clear and accessible information about the operation of their AI systems, including the data used, algorithms applied and decision-making processes.

User rights: Users of AI systems will have specific rights, such as to request rectification or deletion of incorrect or outdated data, and to receive an explanation of decisions made by these systems.

Supervision and enforcement: Supervisory bodies will be established at national and European level to ensure compliance with the Regulation and will have the power to impose administrative and financial sanctions in case of non-compliance.

Risk classification

The Artificial Intelligence Regulation classifies AI systems into three levels of risk:

Inadmissible Risk: Prohibited practices that infringe fundamental rights.

High Risk: Systems that require conformity assessment and are subject to strict regulations.

Low Risk: Systems that can operate with fewer restrictions, but must comply with transparency obligations.

Supervision and sanctions

The Artificial Intelligence Regulation establishes competent bodies in each Member State to supervise compliance with the Regulation. In Spain, the Spanish Artificial Intelligence Supervisory Agency, (Agencia Española de Supervisión de la Inteligencia Artificial, "AESIA") has already been set up. At European level, the European Artificial Intelligence Office will monitor general purpose models and use its expertise to support the implementation of the Regulation, contributing to the consistent application of the Regulation in all Member States, including the creation of advisory bodies at EU level.

In terms of penalties, the Regulation provides that the most serious infringements can be up to EUR 35 million or 7% of the annual turnover of the offending company.

In short, EU AI regulation seeks a balance between control and promotion of technological development, with a focus on protection of rights and security.

Entry into force and staggered implementation

The Artificial Intelligence Regulation foresees a staggered implementation schedule, including the following dates as the most relevant milestones:

2 August 2026: This is the date on which the Artificial Intelligence Regulation will officially enter into force. From this day, the Regulation will be applicable in all EU Member States, establishing a legal framework for the regulation of AI.

2 February 2025: From this date, specific bans will be implemented on certain artificial intelligence practices considered unacceptable or high-risk practices that may violate fundamental rights. This measure aims to prevent the use of technologies that may cause harm to individuals or society.

2 August 2025: On this date, regulations related to supervisory bodies and high-risk systems will start to apply. This includes the designation of entities in charge of overseeing compliance with the regulation and ensuring that AI systems that are considered high-risk comply with the established standards.

2 August 2027: This date marks the start of the implementation of specific regulations for high-risk AI systems, which require security assessments. These systems will have to undergo evaluation and certification processes to ensure that they operate in a safe and ethical manner, thereby protecting users and society at large.

This staggered approach allows companies and organisations to gradually adapt to new regulations, ensuring that they have sufficient time to comply with the established requirements.

Impact and challenges

The implementation of the Artificial Intelligence Regulation will have a significant impact on the development and use of these systems in the EU. Businesses and organisations will need to adapt their practices and processes to comply with the requirements, which may pose technical, organisational and economic challenges. One of the main challenges will be to strike a balance between innovation and regulation, as well as to ensure effective oversight and enforcement of the Regulation along the entire value chain of AI systems.

Regulation (EU) 2024/1689 on Artificial Intelligence represents an important step forward in the regulation of this emerging technology. By establishing clear principles and requirements, it seeks to ensure that the development and use of AI systems is conducted in a responsible manner that respects the rights of individuals. However, the effective implementation and enforcement of this Regulation will remain a challenge in the coming years, requiring the collaboration and commitment of all actors involved, from companies and organisations to public authorities and civil society. It is essential that this challenge is addressed in a proactive and coordinated manner, with the aim of harnessing the benefits of artificial intelligence while mitigating its risks.

In this context of technical and regulatory changes, the Digital Law department of Belzuz Abogados, S.L.P. , can offer specialised advice to its clients on the implementation and use of artificial intelligence systems, in line with the requirements set out in Regulation (EU) 2024/1689. Our team of experts in law and technology is prepared to guide companies and organisations in regulatory compliance, risk management and the adoption of best practices in the development and deployment of AI solutions.

The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.

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These 2 Artificial Intelligence (AI) Stocks May Be Better Buys Than Nvidia for the Blackwell Launch

In this article:.

Chipsets known as graphics processing units (GPUs) are an integral component in the development of artificial intelligence (AI) applications. At the moment, Nvidia (NASDAQ: NVDA) holds an estimated 88% of the AI GPU market thanks to its industry-leading A100 and H100 GPUs.

In the coming months, Nvidia is set to add another GPU -- called Blackwell --to its roster. During the company's most recent earnings call, Nvidia CFO Colette Kress said "demand for Blackwell platforms is well above supply" and that the new chipsets were forecast to generate billions in revenue by the fourth quarter.

While Blackwell appears to be a short-term tailwind for Nvidia , I see two other stocks as potentially better opportunities in the long run.

Here's why I think Super Micro Computer (NASDAQ: SMCI) and Dell Technologies (NYSE: DELL) could be more savvy buys for the upcoming Blackwell launch.

1. Super Micro Computer

Supermicro is an IT infrastructure company that specializes in storage cluster and server rack designs for GPUs. Soaring demand for GPUs over the last couple of years has been a major catalyst for Supermicro's business.

While the Blackwell GPUs should ignite new opportunities among IT architecture specialists, I'm anticipating that Supermicro will be a particular beneficiary given the company's strong relationship with Nvidia. With that said, there are some important things to note about Supermicro's business right now.

First, the company's latest earnings report from early August was a mixed bag. While revenue continues to grow at an impressive rate, the company's gross margin is a glaring issue.

In general, Supermicro's business is going to carry lower margins compared to a software business or a company that has outsize pricing power, such as Nvidia. The reason for this is that designing storage clusters requires hefty capital expenditures (capex), which can take a toll on profit margins.

In addition to the financial results, Hindenburg Research recently published a short report alleging that Supermicro's financial controls and accounting practices are weak. It is important for investors to understand that short-sellers such as Hindenburg benefit when a stock price goes down -- as is the case with Supermicro right now -- but this is not the first time Supermicro has been at the center of accounting-related accusations. In 2020, the Securities and Exchange Commission fined Super Micro Computer and its CFO for violating federal securities laws by "engaging in improper accounting -- prematurely recognizing revenue and understating expenses from at least fiscal year ... 2015 through FY 2017."

Furthermore, the company is set to execute a 10-for-1 stock split in the next week; such an event will almost certainly trigger some momentum-driven trading activity.

Lastly, on Sept. 26, The Wall Street Journal reported that unnamed sources told it the Department of Justice (DOJ) is probing Supermicro and seeking information apparently tied to allegations of accounting violations.

However, at this time details are sparse. I would let this situation play out before fleeing and writing Supermicro off.

On top of all of this, investor uncertainty surrounding macro factors such as interest rate tapering from the Federal Reserve have also influenced selling activity in the market over the last several weeks.

Supermicro stock has been experiencing quite the precipitous sell-off as of late, and much of this revolves around a mixture of hearsay, panic selling, and the macroeconomy.

Right now, Supermicro's forward price-to-earnings (P/E) multiple is just 14 -- nearly 72% off its highs from earlier this year. Moreover, this pales in comparison to the S&P 500 's forward P/E of 23.

This discount to prior valuation levels could make Supermicro stock a compelling opportunity as the Blackwell launch sits on the horizon.

2. Dell Technologies

Earlier in the summer, Elon Musk's AI start-up, xAI, tapped Dell and Supermicro for server rack designs for its GPU clusters. Although this deal came with high-profile headlines, Dell's entire infrastructure solutions group (ISG) is a winning operation.

During its second quarter of fiscal 2025 (ended Aug. 2), Dell had $3.2 billion in AI-optimized server orders and ended the quarter with $3.8 billion in backlog.

From a revenue perspective, ISG increased 38% year over year to a record $11.6 billion. Within ISG, sales from servers and networking equipment rose 80% year over year to $7.7 billion. Meanwhile, storage revenue of $4 billion actually dropped nominally year over year by 5%.

I see the Blackwell launch as an additional catalyst for Dell's ISG segment across both servers and networking as well as storage solutions. To me, Blackwell should help spur even more demand for Dell's infrastructure solutions. I suspect investors could begin to get a glimpse of Blackwell's impact on Dell by looking at backlog details in upcoming earnings reports.

The bottom line

I think buying Supermicro stock right now comes with some risk, considering its shares will likely continue experiencing outsize volatility leading up to the split on Oct. 1 and as details of any government probe emerge. In the long run, however, I think the Blackwell GPUs will be a catalyst for Supermicro's services and newfound demand could ignite a rebound in the stock.

While Dell's forward P/E of 14.9 is in line with that of Supermicro, I see the company as the more prudent investment right now since there is less hoopla surrounding the company compared to its peer.

Nevertheless, I see both Supermicro and Dell as beneficiaries of the Blackwell launch and think the growth spurred from these new GPUs will last quite a long time. For these reasons, investors may want to consider positions in each as Nvidia's newest chipset release looms.

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Adam Spatacco has positions in Nvidia. The Motley Fool has positions in and recommends Nvidia. The Motley Fool has a disclosure policy .

These 2 Artificial Intelligence (AI) Stocks May Be Better Buys Than Nvidia for the Blackwell Launch was originally published by The Motley Fool

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