Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins

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From The Guardian:

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.

Link to the rest at The Guardian

10 thoughts on “Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins”

    • He was beaten by a machine, plus a large team of programmers, researchers, and chess nerds who (so I am informed) put enormous effort into optimizing the machine’s algorithms specifically to counter Kasparov’s style of play, as revealed in the transcripts of all his previous games. They had thousands of hours to prepare for the match, and tens or hundreds of thousands of man-hours. Kasparov had to make all his moves by himself, in real time.

        • lol – they used to say that it takes a village to raise a child, but apparently it takes a corporation to beat a chess champion. I’d be more impressed if a general purpose neural network achieved the same result.

          • Agreed. I never knew the machine had been programmed to beat Kasparov. I assumed — because this is what would make it newsworthy — that a machine had been taught to play chess in general, then calculated on the fly how to beat Kasparov’s moves as he made them. The truth seems way less impressive, even if it does stave off Skynet and HAL for another day 🙂

            If it’s the case that a corporation invested in programming the machine to know all of Kasparov’s moves, then I wonder what would have happened if Kasparov had stepped outside his own box. That’s usually my favorite moment in those type of scenes:

            “The Borg know everything we do by the book!”

            “Then throw out the book!”

            • lmao – easy for /him/ to say. 🙂

              Interesting though, isn’t it?

              Unexpected, unpredictable, lateral thinking is the holy grail for all creatives, yet it’s one of the hardest things to do.

          • I’d be more impressed if a general purpose neural network achieved the same result.

            I’d be even more impressed if my lawn mower beat him.

            And think of how many corporations, programmers, engineers, guide dogs, and rodeo clowns it took to just to build the computer. It’s thousands of years of human progress.

  1. All that for a PR stunt?

    At least they are using Watson to do people’s taxes and medical research.

    I understand that AI is a major goal for the Tech industry, but why isn’t anyone looking at ‘Should we?’ instead of ‘Can we?’ Or even ‘Where would AI do the most good for the most people?’

    It’s like with anything else – somebody wants to make short term money and doesn’t care about long term results.

    I guess someone is going to have to program an AI to look into the long term benefits for the majority of humans like Asimov’s Evidence.

  2. I understand that AI is a major goal for the Tech industry, but why isn’t anyone looking at ‘Should we?’ instead of ‘Can we?’ Or even ‘Where would AI do the most good for the most people?’

    Lots of people are looking at those questions. But, why should we care what they want?

    We’re sitting here communicating with folks all over the world, using cheap machines that were only a dream 50 years ago. Who planned all that? Who guided us? Who was so smart that their wisdom and guidance led us here?

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