As machine learning and AI mature and adapt to the humans that created them, it's important we think carefully about not only what is creativity, but what is uniquely human about creativity.

Marcus du Sautoy is the Charles Simonyi Professor for the Public Understanding of Science at the Oxford University, a chair he holds jointly at the Department of Continuing Education and the Mathematical Institute, as well as a Professor of Mathematics and a Fellow of New College.

His many books dive deep into the world of machines and creativity, and include “Thinking Better: the Art of the Shortcut,” and “The Creativity Code.”

He sits down for this stimulating conversation with Greg covering generative adversarial networks, Ada Lovelace and machine generated music, crediting the code or the coder, and what the future holds for art & AI.

Two kinds of algorithm we need at work:

You need a sort of two algorithms at work. One is the creator coming up with babbling new ideas. And then the second is like, oh, the judgments. No, that's no good. That doesn't work because of this. And you know in my own research, I often pair up with another mathematician and we play these two roles, the creator and the discriminator.

So, I think some of the most interesting algorithms that we're seeing that are beginning to look like they're making something genuinely new are capturing that element that we take advantage of as humans.

Machines still need humans

Machines might be able to do things at speed or at depth that a human could never achieve. But ultimately, we should credit the creativity with the human that told the machine what to do.

The Emotional Resonance to Mathematics

Ada Lovelace went to see, you know, Charles Babbage making a machine do math, but, no, it wasn't doing math. It was doing arithmetic and that's the kind of bread and butter. But mathematics is something much more creative. And, we use this word creativity as a kind of protective shield about, against why a computer can't do what we're doing, because we're making lots of leaps into the unknown, lots of choices, things we choose proofs, which kind of move us emotionally because they got “Aha” moment in them.

Resources:

• The Continuator
• The Turing Test
• Forget Turing, the Lovelace Test Has a Better Shot at Spotting AI
• Ada Lovelace
• AlphaGo
• GPT3 algorithm
• Anish Kapoor
• Library of Babel
• Deep Dream Generator

Guest Profile:

• Faculty Profile at University of Oxford
• Professional Profile at the Royal Society
• Marcus du Sautoy Website
• Marcus du Sautoy on Twitter
• Marcus du Sautoy on Facebook
• Marcus du Sautoy on Youtube
• Marcus Sautoy on TEDTalk

His Work:

• The Creativity Code: Art and Innovation in the Age of AI
• Finding Moonshine Blog
• Thinking Better: The Art of the Shortcut in Math and Life
• I is a Strange Loop
• How to Count to Infinity (Little Ways to Live a Big Life Book 1)
• The Great Unknown: Seven Journeys to the Frontiers of Science
• What We Cannot Know: From consciousness to the cosmos, the cutting edge of science explained
• The Music of the Primes: Searching to Solve the Greatest Mystery in Mathematics 
• The Number Mysteries: A Mathematical Odyssey through Everyday Life (MacSci)
• Symmetry: A Mathematical Journey 
• Finding Moonshine: A Mathematician's Journey Through Symmetry