Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins by Garry Kasparov – review
A book review published in The Guardian on June 4, 2017
The grandmaster’s account of his 1997 battle with Deep Blue is both thrilling and thoughtful
Garry Kasparov is arguably the greatest chess player of all time. From 1986 until his retirement in 2005, he was ranked world No 1. He is also a leading human rights activist and is probably close to the top of Vladimir Putin’s hitlist, not least because he tried to run against him for the Russian presidency in 2007. But for people who are interested only in technology, Kasparov is probably best known as the first world champion to be beaten by a machine. In 1997, in a famous six-game match with the IBM supercomputer Deep Blue, he lost 3½-2½.
In the grand scheme of things, losing by one game in a six-game match might not seem much, but at the time it was seen as a major milestone in the long march towards “artificial” intelligence (AI). With the 20/20 vision of hindsight we can view it in a less apocalyptic light: the triumph of Deep Blue was really a victory of brute computing power, clever programming and the ruthless determination of a huge but struggling corporation to exploit the PR advantages of having one of its products do something that would impress the world’s media. But if you believe that AI has something to do with cognition, then Kasparov’s epochal defeat looks like a sideshow.
That it retains its fascination owes more to the popular view of proficiency at chess as a proxy for superintelligence rather than as possession of a very specialised skill. We’ve known for centuries that machines are much better at some things than we are. That’s why Google has become a memory prosthesis for humanity and why we use power drills to anchor bookshelves to walls. So the fact that machines now play better chess than even the greatest grandmasters or that DeepMind’s AlphaGo defeated the world Go champion at his particular speciality is interesting – and might even be useful in other areas, such as pattern-matching. But it’s just an incremental step on the same path that Deep Blue trod: the IBM machine used brute-force search; AlphaGo combined even more powerful brute-force search with a couple of neural networks. It’s technically sweet, certainly, but of less than cosmic significance.
Living, as we do, in a time when existential concern about “superintelligence” and robots taking away middle-class jobs, Kasparov has acquired a new significance as the highest-profile (and highest-status) human ever to have been defeated by a machine. (Interestingly, Deep Blue didn’t take away his job: he continued to hold the world chess championship until his defeat by Vladimir Kramnik in 2000. And he continued to win tournaments and maintain his world ranking until he retired in 2005.) So what makes his book fascinating is that he uses it to reflect on what it was like to have been defeated by a machine and on the more general implications of that experience.
The Kasparov v Deep Blue match has been endlessly discussed by chess aficionados in books and articles, but Deep Thinking gives us the inside story of what happened. Even for readers with only a passing interest in chess, it’s an absorbing, page-turning thriller that weaves a personal account of intellectual combat with the wider picture of what it’s like to come up against a powerful corporation that is determined to do whatever it takes to crush opposition. So this isn’t just a tale of human versus machine – it’s also a story about one man versus The Man.
What many people forget (certainly I had) is that the 1997 match was, in fact, a return match. In February 1996, Kasparov had played – and defeated 4-2 – Deep Blue in Philadelphia, in a match sponsored by the Association for Computing Machinery. The publicity surrounding the match had taken IBM, then run by Lou Gerstner, the CEO who was trying to turn around the ailing company, completely by surprise. Among other things, the machine’s performance had boosted the company’s share price, a development that is never lost on CEOs.
So from the moment when a date for a rematch was agreed, the technical, administrative and public-relations resources of a huge IT corporation were thrown behind the effort to ensure that Kasparov would lose. Deep Blue was massively improved with more and faster processing hardware; its software was likewise tuned and trained by a squad of chess grandmasters secretly hired by IBM.
Because the company was sponsoring the rematch (and putting up the $1.1m prize money), its staff were able to structure the venue in subtle ways, some of which had the effect of discomfiting Kasparov. (In contrast to standard tournament practice, for example, IBM did not provide a private “team room” where he could consult with his seconds.)
Even so, the rematch was a cliffhanger. It was marked by Kasparov’s increasing anger and frustration at the behaviour of IBM, which stonewalled against his requests for printouts of the machine’s logs of completed games. And, in true thriller style, it all came down to the last match, which Kasparov lost. And he is not, as he says himself, a good loser, so the resulting media coverage did not do him any favours. And of course IBM scooped the PR jackpot.
The passage of time has mellowed Kasparov and his reflections on the match and its outcome are more thoughtful, measured and insightful than I had expected from the opening chapters of the book. His initial thoughts about the implications of AI seemed banal and predictable. “Romanticising the loss of jobs to technology,” he writes on page 42, “is little better than complaining that antibiotics put too many gravediggers out of work.” The transfer of labour from humans to our inventions “is nothing less than the history of civilisation”. And the early Kasparov sounds like a technological determinist on steroids. “Even if it were possible to mandate slowing down the development and implementation of intelligent machines,” he writes, “it would only ease the pain for a few for a little while and make the situations worse for everyone in the long run.” And so on.
Yet by the end of the book, he has arrived at a more enlightened view of machine intelligence than most people in the tech industry, who are obsessed with machines that will replace people. Kasparov was an early enthusiast for chess-playing computers and indeed did much to foster the technology that enables every child nowadays to learn to play against a grandmaster-level virtual opponent. In the end, the technology he inspired defeated him. But the message he bears is that the really intelligent approach is not to rail against the machine for being better than we are at some things, but to celebrate its capacity to augment our human capabilities. And therein lies the beginning of wisdom in these matters.