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Stephen Wolfram thinks we need philosophers working on big questions around AI

Mathematician and scientist Stephen Wolfram grew up in a household where his mother was a philosophy professor at Oxford University. As such, his younger self didn’t want anything to do with the subject, but an older and perhaps wiser Wolfram sees value in thinking deeply about things. Now he wants to bring some of that deep philosophical rigor to AI research to help us better understand the issues we encounter as AI becomes more capable.

Wolfram was something of a child prodigy, publishing his first scientific paper at 15 and graduating from Caltech with a doctorate at 20. His impressive body of work crosses science, math and computing: He developed Mathematica, Wolfram Alpha and the Wolfram Language, a powerful computational programming language.

“My main life work, along with basic science, has been building our Wolfram language computational language for the purpose of having a way to express things computationally that's useful to both humans and computers,” Wolfram told TechCrunch.

As AI developers and others start to think more deeply about how computers and people intersect, Wolfram says it is becoming much more of a philosophical exercise, involving thinking in the pure sense about the implications this kind of technology may have on humanity. That kind of complex thinking is linked to classical philosophy.

“The question is what do you think about, and that's a different kind of question, and it's a question that's found more in traditional philosophy than it is in the traditional STEM,” he said.

For example, when you start talking about how to put guardrails on AI, these are essentially philosophical questions. “Sometimes in the tech industry, when people talk about how we should set up this or that thing with AI, some may say, ‘Well, let's just get AI to do the right thing.’ And that leads to, ‘Well, what is the right thing?’” And determining moral choices is a philosophical exercise.

He says he has had “horrifying discussions” with companies that are putting AI out into the world, clearly without thinking about this. “The attempted Socratic discussion about how you think about these kinds of issues, you would be shocked at the extent to which people are not thinking clearly about these issues. Now, I don't know how to resolve these issues. That's the challenge, but it's a place where these kinds of philosophical questions, I think, are of current importance.”

He says scientists in general have a hard time thinking about things in philosophical terms. “One thing I've noticed that's really kind of striking is that when you talk to scientists, and you talk about big, new ideas, they find that kind of disorienting because in science, that is not typically what happens,” he said. “Science is an incremental field where you're not expecting that you're going to be confronted with a major different way of thinking about things.”

If the main work of philosophy is to answer big existential questions, he sees us coming into a golden age of philosophy due to the growing influence of AI and all of the questions that it's raising. In his view, a lot of the questions that we're now being confronted with by AI are actually at their core of traditional philosophical questions.

“I find that the groups of philosophers that I talk to are actually much more agile when they think paradigmatically about different kinds of things,” he said.

One such meeting on his journey was with a group of masters’ philosophy students at Ralston College in Savannah, Georgia. Wolfram spoke to students there about the coming collision of liberal arts and philosophy with technology. In fact, Wolfram says he has reread Plato’s "Republic" because he wants to return to the roots of Western philosophy in his own thinking.

“And this question of ‘if the AIs run the world, how do we want them to do that? How do we think about that process? What's the kind of modernization of political philosophy in the time of AI?’ These kinds of things, this goes right back to foundational questions that Plato talked about,” he told students.

Rumi Allbert, a student in the Ralston program, who has spent his career working in data science and also participated in Wolfram Summer School, an annual program designed to help students understand Wolfram’s approach to applying science to business ideas, was fascinated with Wolfram’s thinking.

“It’s very, very interesting that a guy like Dr. Wolfram has such an interest in philosophy, and I think that speaks to the volume of importance of philosophy and the humanistic approach to life. Because it seems to me, he has gotten so developed in his own field, [it has evolved] to more of a philosophical question,” Allbert said.

That Wolfram, who has been involved on the forefront of computer science for a half century, is seeing the connections between philosophy and technology, could be a signal that it’s time to start addressing these questions around AI usage in a much broader way than purely as a math problem. And perhaps bringing philosophers into the discussion is a good way to achieve that.

Wolfram Science ™.

Using the basic science of the computational universe to create a new kind of technology

Often known as "NKS" after the title of Stephen Wolfram's 2002 book A New Kind of Science , Wolfram Science is a branch of basic science concerned with understanding the computational universe of possible programs: their behavior, general properties and applications.

Wolfram Science opens up a new way of thinking about computation, and a new approach to creating computational—and other—technology.

Mining the computational universe of possible programs using the ideas of Wolfram Science has become a key approach for creating algorithms used in Wolfram products . And as a company committed to a long-term vision , Wolfram Research continues to support Wolfram Science and its intellectual development.

Simple Programs May Not Do Simple Things

A core discovery in Wolfram Science is that even extremely short programs—say less than a line of Wolfram Language code—can behave in irreducibly rich and complex ways.

Stephen Wolfram 's favorite discovery: an incredibly simple program that produces behavior so complex that many aspects of it seem random—and they're random enough to make a great pseudorandom generator.

Exploring the Computational Universe

Like the telescope enabled modern astronomy and led to modern physics, the Wolfram Language and its precursors enabled exploration of the computational universe, and led to Wolfram Science.

The Principle of Computational Equivalence

Stephen Wolfram's central principle, inferred from years of studying the computational universe—with deep implications for science, technology and our ways of thinking about the world.

The Space of All Possible Mathematics

Today's mathematics—as captured in many functions in Mathematica —is based on specific axioms. Wolfram Science highlights the rich space of other possible axioms that yield uninvented branches of mathematics.

Computational Models of Nature

Following extensive work by Stephen Wolfram and many others, simple programs are beginning to overtake mathematical equations as the favored modeling approach for a wide range of systems, especially where complex behavior is seen.

The Threshold of Universality

What does it take to make a universal computer? A key result in Wolfram Science is that even incredibly simple systems can serve as universal computers capable of being programmed to compute anything.

A Paradigm for Biology?

Just as the concept of digital information led us to genomics, so ideas about the computational universe may lead us to an understanding of diverse biological processes—and the complexity that makes medicine difficult.

Hunting for Physics

If simple programs can yield infinitely complex behavior, perhaps our whole universe can be represented as just a simple program. Stephen Wolfram has long explored this idea, generating a rich set of results, but not yet finding our universe...

Automating Creativity

Each program in the computational universe is like a new idea, with its own consequences—that can surprise and amaze us with their unexpectedness, cleverness, usefulness or beauty.

Generalizing the Beauty of Nature

Nature creates complex and beautiful forms by following specific simple programs—but with all the programs in the computational universe, we have an inexhaustible supply of nature-like beauty to explore.

WolframTones : "A New Kind of Music"

Built in 2005 at the height of the ringtone craze, WolframTones creates short musical pieces by mining them from the computational universe.

The Creativity of Biology

The idea of searching simple programs isn't new: in fact, it's probably a major force in biology, alongside natural selection, that leads to the endlessly creative and complex forms we see in biology.

The Art of Wolfram Science

Simple programs—especially cellular automata—have been widely used to produce decorative art, with forms evoking different styles found by searching the computational universe of programs.

Architectural Form

When an architectural project calls for a form with inner logic but rich and complex structure, it's become common to turn to Wolfram Science to find simple programs that can generate it.

Mining for Algorithms

We've been mining the physical universe for technology for millennia. Now it's time to mine the computational universe—and discover algorithms we'd never imagine. Wolfram Research has been doing it for years.

Building the Wolfram Algorithmbase

An increasing number of Wolfram Language algorithms—for image analysis, function evaluation, randomness generation, machine learning, and much more—were found by mining the computational universe.

The Best Is Often Surprising

Most traditional algorithms have very regular iterative (periodic) or recursive (nested) structures. Wolfram Science searches often yield more optimal algorithms that do not have any such recognizable structure.

The Algorithm Discovery Process

Like drug discovery in the chemical universe, algorithm discovery in the computational universe needs targets—often defined as Wolfram Language programs to compare with or test potential algorithms.

Non-Incremental Engineering

Traditional methodology involves building up algorithms in incremental steps. The Wolfram Science methodology involves large-scale searches that, if successful, immediately give the final result.

Searching Trillions of Programs

Wolfram Research often searches trillions of programs to find the best algorithm for a particular purpose, typically avoiding incremental and evolutionary methods that tend not to reach the truly unexpected.

Programs We Can't Understand

In the computational universe, it's common to find optimal programs whose operation is at best difficult to understand—necessitating automated methods for assessing performance or proving correctness.

The Secret Sauce of Wolfram|Alpha

Wolfram|Alpha is in many ways the first "killer app" of Wolfram Science—made possible both by the conceptual discoveries of the science, and by the practical methods it introduces.

It's All Just Computation

Stephen Wolfram often credits the Principle of Computational Equivalence for convincing him that computational knowledge doesn't require human-like AI—and that the Wolfram|Alpha project might be doable.

Automated Judgement & Aesthetics

Wolfram|Alpha is full of heuristics that effectively automate human judgment and aesthetic choice. Many of these heuristics were either found or deeply informed by Wolfram Science methods.

Breakthroughs in Language Understanding

The Wolfram|Alpha language understanding system relies heavily on ideas from Wolfram Science, in effect setting up collections of interacting simple programs that represent primitive linguistic processes.

Visualizing Computational Process

Research in Wolfram Science tends to involve extensive visualization of computational processes—a technique widely used in the development of Wolfram|Alpha.

A Foundation for Computation-Related Education

Like mathematics, Wolfram Science provides an introduction to abstract thinking—while also giving students an important theoretical and conceptual foundation for their life in today's world of ubiquitous computation.

Kindergarten On

Following the rules to create a cellular automaton pattern is an activity accessible to kindergartners, already teaching the concept of an algorithm and the importance of precision, and showing connections to the real world.

Accessible Math-Like Thinking

Particularly at lower levels, Wolfram Science teaches the same kind of abstract and rigorous thinking as math—but is often more concrete and accessible, and has immediate surprising connections to the real world.

An Inclusive Science

Art. Technology. Nature. Programming. Exploration. Abstract thinking. Wolfram Science has components that appeal to a remarkably wide range of students.

Live Experiments

Wolfram Science offers teachers a unique opportunity to show the process of discovery in action by doing live classroom computer experiments with unscripted results.

Pre-Computer Science

Without requiring any math, Wolfram Science introduces the concepts of computation, and gives students a strong framework for later education in traditional computer science.

One Science, Many Methodologies

Wolfram Science involves computer experiments and experimental observation, theoretical abstract thinking, creating and assessing models—as well as visual thinking, with connections to aesthetics.

Everyone Is At the Frontier

Partly because it's so new, and partly because of its methodologies, research in Wolfram Science is uniquely accessible to students—so even young students can potentially make their own discoveries.

Wolfram Summer School

Since 2003, the annual Wolfram Summer School has served as a highly successful model for project-based education in Wolfram Science.

The Role of the Wolfram Language

Precursors of the Wolfram Language are what made Wolfram Science possible—and the Wolfram Language now provides a highly optimized environment for Wolfram Science work.

Represent the Breadth of Computation

The symbolic primitives—and pattern-matching capabilities—of the Wolfram Language make it ideally suited to represent a broad range of models of computations and types of simple program.

Built-In Wolfram Science Functions

The Wolfram Language has a variety of built-in functions for doing common operations in Wolfram Science—such as running cellular automata, Turing machines, and so on.

Scale Up to Production

Once a Wolfram Science discovery is made in the Wolfram Language, it's easy to take the algorithm, model, etc. and scale it up for production use.

Just Try an Experiment

The interactive and highly automated character of the Wolfram Language makes it uniquely suitable for doing computer experiments as soon as one thinks of them.

Computational Lab Notebooks

Wolfram Notebooks are ideal for recording computer experiments, showing the sequence of steps taken, and inserting text with relevant observations.

History & Context

Wolfram Science is an outgrowth of many people's work, with core contributions made since 1980 by Stephen Wolfram—culminating in his 2002 book A New Kind of Science .

Generalizing Science

Since the 1600s, most of exact science has been based on constructing mathematical equations for the world. Wolfram Science is about generalizing this by using programs instead of equations to model the world.

The Science of Complexity

Spawned in some ways by Stephen Wolfram's work in the early 1980s, Complexity Theory studies systems with complex behavior, but doesn't take the same kind of global view of the computational universe as Wolfram Science.

A Classic Paradigm Shift

When Stephen Wolfram's book appeared in 2002, it encountered the same kind of turbulence seen in many historical scientific paradigm shifts, but soon began the long process of widespread acceptance.

More Evidence Comes In

Concepts like the Principle of Computational Equivalence are long-term scientific ideas that require progressive validation—like the 2007 Wolfram-sponsored proof of the simplest universal Turing machine.

Cellular Automata and Beyond

Stephen Wolfram's discoveries in the early 1980s were made in a class of simple programs known as cellular automata. It took his 2002 book to show how broad the discoveries in fact are.

"I Need Mathematica"

Stephen Wolfram started building Mathematica in 1986 so that he could have a tool to continue his work in basic science—and from 1991 to 2002 he used it to make the discoveries in A New Kind of Science .

Tens of Thousands of Academic Papers

Large numbers of academic papers have used Wolfram Science methodologies to create models and make discoveries across an amazing diversity of natural, social and mathematical sciences—and beyond.

The Proof Is In the Results

The ultimate test of a science is whether it's useful—and Wolfram Science has firmly established itself as a major source of scientific, technological, artistic, philosophical and other results.

Wolfram Language

Revolutionary programming language with built-in algorithms.

Complex Systems

The original journal devoted to the science, mathematics, and engineering of systems with simple components but complex overall behavior.

Unique education and career opportunity at the frontiers of science and technology.

Wolfram Science & A New Kind of Science

Explore the computational universe with free online access to Stephen Wolfram's classic 1200-page breakthrough book.

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Brjuno Number

Explore with Wolfram|Alpha

More things to try:

• continued fractions
• adjugate {{8,7,7},{6,9,2},{-6,9,-2}}
• distinct permutations of {1, 2, 2, 3, 3, 3}

Referenced on Wolfram|Alpha

Cite this as:.

Weisstein, Eric W. "Brjuno Number." From MathWorld --A Wolfram Web Resource. https://mathworld.wolfram.com/BrjunoNumber.html

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