The new book, The Creativity Code: Art and Innovation in the Age of AI, by Marcus du Sautoy, a celebrated mathematician at Oxford University, is quite a fascinating work all the way through, as he attempts to answer the question, “Can a well-programmed machine do anything a human can—only better?”
And one of the most intriguing narratives in the book takes up most of its third chapter, “Ready Steady Go.” As du Sautoy writes in that chapter, “People often compare mathematics to playing chess, and certainly there are connections. But when [IBM’s] Deep Blue beat the best chess master the human race could offer, in 1997, it did not lead to the closures of mathematics departments. Although chess is a good analogy for the formal effort of constructing a proof, there is another game that mathematicians have regarded as much closer to their work, because it also features a creative and intuitive side. That is the Chinese game of Go.”
As du Sautoy writes, “I first discovered Go when I visited the mathematics department at Cambridge as an undergraduate to explore whether to do my PhD with the amazing group that had helped complete the Classification of Finite Simple Groups, a sort of Periodic Table of Symmetry. As I sat talking about the future of mathematics with John Conway and Simon Norton, two of the architects of this great project, I kept being distracted by students at the next table furiously slamming black and white stones onto a grid carved into a large, wooden board. Eventually I asked Conway what they were doing. ‘That’s Go,’ he explained. ‘It’s the oldest game that is still being played to this day.’ In contrast to chess, with its warlike quality, Go is a game of territory capture,” he notes.
Further, what intrigued him, du Sautoy writes, was that, given that “The American Go Association estimates that it would take a number with 300 digits to count the number of games of Go that are legally possible,” compared to a 120-digit number for chess, that, “At the beginning of 2016 it was announced that a program had been created to play Go that its developers were confident could hold its own against the best human competition.” And he spends most of the rest of the chapter narrating the story of how Demis Hassabis, an international chess champion, after entering the world of machine learning, determined to create a program that could beat humans at Go.
Hassadis assembled a team of programmers at his London-based AI startup, DeepMind, and that team created a program called AlphaGo, which ultimately, in March 2016 in Seoul, beat Lee Sedol, the 18-time international Go champion. After defeating Sedol, the Go team at DeepMind retired from competitive play. Instead, “DeepMind has now set its heights on other goals: healthcare, climate change, energy efficiency, speech recognition and generation, computer vision. It’s all getting very serious,” du Sautoy emphasizes.
In 2019, this is the world we live in, one in which mathematical and computing geniuses are exploring ways to make machines ever smarter. Could they end up making contributions that could ultimately improve patient care delivery? That is in fact the subject of one of the Top Ten Tech Trends this year, our annual cover story package that looks at the top healthcare system trends helping to reshape the landscape for U.S. providers.
With a spectrum of trend areas ranging from the “One Foot in the Boat” dilemma to the social determinants of health to EHR optimization, we believe you’ll find much to ponder in this package of articles, which offer insights and analysis from industry leaders and observers. Enjoy!
