My other SIAM News contributions are necessarily math-focused. This one is a bit different: a review of a very good and funny popular-science book about machine learning and its failures.
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The Threat of AI Comes from Inside the House
For SIAM News:
Artificial intelligence (AI) will either destroy us or save us, depending on who you ask. Self-driving cars might soon be everywhere, if we can prevent them from running over pedestrians. Public cameras with automated face recognition technology will either avert crime or create inescapable police states. Some tech billionaires are even investing in projects that aim to determine if we are enslaved by computers in some type of Matrix-style simulation.
In reality, the truest dangers of AI arise from the people creating it. In her new book, You Look Like a Thing and I Love You, Janelle Shane describes how machine learning is often good at narrowly-defined tasks but usually fails for open-ended problems.
Shane—who holds degrees in physics and electrical engineering—observes that we expect computers to be better than humans in areas where the latter often fail. This seems unreasonable, considering that we are the ones teaching the machines how to do their jobs. Problems in AI often stem from these very human failings.
[Read the rest at SIAM News…]
I’m in a magazine!
Physics is largely a matter of finding patterns in natural processes and translating that to mathematical expression. That’s a horribly oversimplified view, of course, but there’s no question that physics (and other branches of science) seeks to find symmetries. The huge successes of modern particle physics have largely arisen from identifying symmetries — and when those symmetries break down. To cite just one: physicists understand the weak force, which governs neutrinos and processes like nuclear beta decay, using a mathematical symmetry. That symmetry isn’t perfect, however, and one outward manifestation of that imperfection is the Higgs boson.
This pattern-seeking behavior among physicists is the theme of Dave Goldberg’s book The Universe in the Rearview Mirror: How Hidden Symmetries Shape Reality. I reviewed the book for Physics World, which marks my first publication in a print magazine. (It also may be the first time The Decemberists were quoted in Physics World.) You can read my review online, though the site requires a free registration to do so. In brief, I enjoyed the book, but found a few problems with it as well.
Inevitably, Goldberg’s explanations vary in quality. I found his discussion of the Casimir and Unruh effects (weird quantum phenomena in the vacuum) to be very good introductions for non-specialists. He also provides an excellent summary of the problems facing attempts to unify the different forces of nature, and specifically the question of pro- ton decay. On the other hand, his explanation of Lagrangians and the principle of least action (both essential topics in a mathematical sense) falls short, since it requires him to define a lot of new terminology in just a few pages, most of it barely mentioned again. The book also misses an opportunity to explain how specific symmetries shaped the development of the Standard Model; while it outlines a few of the important symmetries (including parity or reflection symmetry, time-reversal, time-translation, and exchange of matter and antimatter) early on, it fails to bring them back into the picture when the Standard Model is discussed. [Read more…]