I'm trying to explain to Arthur I. Miller why artworks generated by computers don't quite do it for me. The works aren't a portal into another person's mind, where you can wander in a warren of intention, emotion, and perception, feeling life being shaped into form. What's more, it often seems, people just ain't no good, so it's transcendent to be reminded they can be. Art is one of the few human creations that can do that. No matter how engaging the songs or poems that a computer generates may be, they ultimately feel empty.
On a warm day in April 2013, I was sitting in a friend's kitchen in Paris, trying to engineer serendipity. I was trying to get my computer to write music on its own. I wanted to be able to turn it on and have it spit out not just any goofy little algorithmic tune but beautiful, compelling, mysterious music; something I'd be proud to have written myself. The kitchen window was open, and as I listened to the sounds of children playing in the courtyard below, I thought about how the melodies of their voices made serendipitous counterpoint with the songs of nearby birds and the intermittent drone of traffic on the rue d'Alésia. In response to these daydreams, I was making a few tweaks to my software--a chaotic, seat-of-the-pants affair that betrayed my intuitive, self-taught approach to programming--when I saw that Bill Seaman had just uploaded a new batch of audio files to our shared Dropbox folder. I had been collaborating with Bill, a media artist, on various aspects of computational creativity over the past few years.
Ross Goodwin has had an extraordinary career. After playing about with computers as a child, he studied economics, then became a speech writer for President Obama, writing presidential proclamations, then took a variety of freelance writing jobs. One of these involved churning out business letters--he calls it freelance ghostwriting. The letters were all pretty much the same, so he figured out an algorithm that would generate form letters, using a few samples as a database. The algorithm jumbled up paragraphs and lines following certain templates, then reassembled them to produce business letters, similar but each varying in style, saving him the job of starting anew each time.
The 20 words defined in this lexicon reflect the ways in which light irradiates the atmosphere, the universe, and our perception of the world. Because no single system--scientific, religious, philosophical, or cultural--can possibly encompass every meaning of light, this lexicon is systematically unsystematic, exploring each of these realms through words that serve as synecdoches for ways in which we understand light and its myriad effects. Each of Earth's poles has an aurora, which can occasionally grow large enough to be seen near the equator, inspiring visions of apocalypse. For the Inuit, who are more accustomed to it, the aurora is perceived as a football game played by spirits in the heavens. The scientific explanation is no less astounding.
Thanks to advances in machine learning over the last two decades, it's no longer in question whether humans can beat computers at games like chess; we'd have about as much chance winning a bench-press contest against a forklift. But ask the current computer champion, Google's AlphaZero, for advice on chess theory, like whether a bishop or a knight is more valuable in the Ruy Lopez opening, and all you'll get is a blank stare from a blinking cursor. Theory is a human construct the algorithm has no need for. The computer knows only how to find the best move in any given position because it's trained extensively--very extensively--by practicing against itself and learning what works. Even with a lead time of 18 months, the neural network was able to see El Niño events coming.
Can AI teach itself the laws of physics? Will classical computers soon be replaced by deep neural networks? Sure looks like it, if you've been following the news, which lately has been filled with headlines like, "A neural net solves the three-body problem 100 million times faster: Machine learning provides an entirely new way to tackle one of the classic problems of applied mathematics," and "Who needs Copernicus if you have machine learning?". The latter was described by another journalist, in an article called "AI Teaches Itself Laws of Physics," as a "monumental moment in both AI and physics," which "could be critical in solving quantum mechanics problems." The trouble is, the authors have given no compelling reason to think that they could actually do this.
Shaun Patel has such a tranquil voice that it's easy to see how he convinces patients to let him experiment in the depth of their brains. On the phone, in his office at Massachusetts General Hospital (he is also on faculty at Harvard Medical School), the neuroscientist spoke about gray matter almost as if he were guiding me in meditation. Or perhaps that was just the heady effect of him detailing a paper he had just published in Brain, showing how, using implants on his patients, he could enhance learning by stimulating the caudate nucleus, which lies near the center of the brain.1 You have to time the electric pulse just right, he told me, based on the activity of certain neurons firing during an active learning phase of a game. A perfectly timed pulse could speed up how quickly his patients made the right associations. Using similar methods, he said he has induced people to make more financially conservative bets.
During the last months of my mother's life, as she ventured further from lucidity, she was visited by music. In collusion with her dementia, her hearing loss filled her consciousness with musical hallucinations. Sometimes welcome, more often not, her musical visitations were vivid, yet segmented and tattered. She would occasionally comment on the singers. On rare occasions she would identify the performer. Mitch Miller, who wrote oppressively cheerful arrangements of popular songs from the 1950s, seemed to command a prominent role in her hallucinations.
Consider a forest: One notices the trunks, of course, and the canopy. If a few roots project artfully above the soil and fallen leaves, one notices those too, but with little thought for a matrix that may spread as deep and wide as the branches above. Fungi don't register at all except for a sprinkling of mushrooms; those are regarded in isolation, rather than as the fruiting tips of a vast underground lattice intertwined with those roots. The world beneath the earth is as rich as the one above. For the past two decades, Suzanne Simard, a professor in the Department of Forest & Conservation at the University of British Columbia, has studied that unappreciated underworld. Her specialty is mycorrhizae: the symbiotic unions of fungi and root long known to help plants absorb nutrients from soil. Beginning with landmark experiments describing how carbon flowed between paper birch and Douglas fir trees, Simard found that mycorrhizae didn't just connect trees to the earth, but to each other as well. Simard went on to show how mycorrhizae-linked trees form networks, with individuals she dubbed Mother Trees at the center of communities that are in turn linked to one another, exchanging nutrients and water in a literally pulsing web that includes not only trees but all of a forest's life.
In wondering what can be done to steer civilization away from the abyss, I confess to being increasingly puzzled by the central enigma of contemporary cognitive psychology: To what degree are we consciously capable of changing our minds? I don't mean changing our minds as to who is the best NFL quarterback, but changing our convictions about major personal and social issues that should unite but invariably divide us. As a senior neurologist whose career began before CAT and MRI scans, I have come to feel that conscious reasoning, the commonly believed remedy for our social ills, is an illusion, an epiphenomenon supported by age-old mythology rather than convincing scientific evidence. If so, it's time for us to consider alternate ways of thinking about thinking that are more consistent with what little we do understand about brain function. I'm no apologist for artificial intelligence, but if we are going to solve the world's greatest problems, there are several major advantages in abandoning the notion of conscious reason in favor of seeing humans as having an AI-like "black-box" intelligence.