Garry Kasparov: At peace with AI

by ChessBase
2/23/2020 – Just under twenty-three years ago Garry Kasparov made history by losing a match against a computer named Deep Blue. Today smartphones are capable of running chess engines as powerful as IBM's giant mainframe in 1997. More significantly, thanks to recent progress in artificial intelligence, machines are learning and exploring the game for themselves. So what does the legendary World Champion think about the progress of AI in chess, and its effect on humanity in general? He told Wired Magazine that he has made his peace with AI.

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"Progress cannot be stopped"

Recently Garry Kasparov returned to the scene of his famous Deep Blue defeat—the ballroom of a New York hotel—for a debate with AI experts organized by the Association for the Advancement of Artificial Intelligence. He met with WIRED senior writer Will Knight there to discuss chess, AI, and a strategy for staying a step ahead of machines. The following are short excerpts from the interview entitled "Defeated Chess Champ Garry Kasparov Has Made Peace With AI," which is well worth reading in full. 

About losing to Deep Blue:

I’ve made my peace with it. 1997 was an unpleasant experience, but it helped me understand the future of human-machine collaboration. We thought we were unbeatable, at chess, Go, shogi. All these games, they have been gradually pushed to the side [by increasingly powerful AI programs. But it doesn't mean that life is over. We have to find out how we can turn it to our advantage.

The impact of AI?

Every technology destroys jobs before creating jobs. When these jobs start disappearing, we need new industries, we need to build foundations that will help. Maybe it’s universal basic income, but we need to create a financial cushion for those who are left behind. We have to look for opportunities to create jobs that will emphasize our strengths. Technology is the main reason why so many of us are still alive to complain about technology.

Assist a chess engine to make it stronger?

I can look at AlphaZero’s games and understand the potential weaknesses. I describe the human role as being shepherds. You just have to nudge the flock of intelligent algorithms. Just basically push them in one direction or another, and they will do the rest of the job.

On human-level AI

We are comfortable with machines making us faster and stronger, but smarter? It’s some sort of human fear. I don't believe in AGI [artificial general intelligence]. I don't believe that machines are capable of transferring knowledge from one open-ended system to another. So machines will be dominant in the closed systems, whether it's games, or any other world designed by humans. Let's say you accumulated knowledge in one game. Can it transfer this knowledge to another game, which might be similar but not the same? Humans can. With computers, in most cases you have to start from scratch.

On the ethics of AI

We know from history that progress cannot be stopped. So we have certain things we cannot prevent. Humans still have the monopoly on evil. The problem is not AI. The problem is humans using new technologies to harm other humans. AI is like a mirror, it amplifies both good and bad. It's a tool. And unfortunately we have enough political problems, both inside and outside the free world, that could be made much worse by the wrong use of AI.

AlphaZero’s style of play

Every computer player is now too strong for humans. It was a mistake to think that if we develop very powerful chess machines, the game would be dull, that there will be many draws, maneuvers, or a game will be 1,800, 1,900 moves and nobody can break through. AlphaZero is totally the opposite. For me it was complementary, because it played more like Kasparov than Karpov! It found that it could actually sacrifice material for aggressive action. It’s not creative, it just sees the pattern, the odds. But this actually makes chess more aggressive, more attractive. Magnus Carlsen has said that he studied AlphaZero games, and he discovered certain elements of the game, certain connections. He could have thought about a move, but never dared to actually consider it; now we all know it works.

Also read: Chess, a Drosophila of reasoning. by Garry Kaspaov in Science Magazine:

"Based on a generic game-playing algorithm, AlphaZero incorporates deep learning and other AI techniques like Monte Carlo tree search to play against itself to generate its own chess knowledge. Unlike top traditional programs like Stockfish and Fritz, which employ many preset evaluation functions as well as massive libraries of opening and endgame moves, AlphaZero starts out knowing only the rules of chess, with no embedded human strategies. In just a few hours, it plays more games against itself than have been recorded in human chess history. It teaches itself the best way to play, reevaluating such fundamental concepts as the relative values of the pieces. It quickly becomes strong enough to defeat the best chess-playing entities in the world.

I admit that I was pleased to see that AlphaZero had a dynamic, open style like my own. The conventional wisdom was that machines would approach perfection with endless dry maneuvering, usually leading to drawn games. But in my observation, AlphaZero prioritizes piece activity over material, preferring positions that to my eye looked risky and aggressive. Programs usually reflect priorities and prejudices of programmers, but because AlphaZero programs itself, I would say that its style reflects the truth. This superior understanding allowed it to outclass the world's top traditional program despite calculating far fewer positions per second."

If you are interested in the AI development in chess you may want to take a look at the ChessBase program package of Fritz 17. It contains an AlphaZero clone, engineered over the past year and tested by some of the best players in the world — all of whom expressed unmitigated delight over the ideas and improvements it came up with. Here are all the articles that have appeared on Fat Fritz.

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spieler8 spieler8 2/27/2020 08:13
Yet he still hasn't apologized to Hsu and Campbell for his ridiculous accusations.
Sampru Sampru 2/27/2020 02:37
Mr. Toad, since Kasparov did beat the machine in the first game, he proved able to do so. Consequently, I think he could still have beaten it in a match, provided he had more control over his environment rather than effectively be in a Skinner box.
physica physica 2/23/2020 11:02
@jimijr Yes, thanks to zillion dollar budget on the project and PR AlphaZero gets the credit for creating something new. The Truth is Stockfish had been playing g4 breakthrough at TCEC several times couple of years before A0 entered the chess scene.
Mr Toad Mr Toad 2/23/2020 08:07
I always thought Kasparov was tricked out of beating Deep Blue even apart from his complaints about the scenario he walkd into. He made a mistake at a crucial point, he seemed to understand where he went wrong but he was not given a rematch. At that time I do believe he could have won. This possibility is never discussed! What does everyone think?
SermadShah SermadShah 2/23/2020 03:22
I think after 30, strong grand-masters should research how to beat computer. I still believe humans are superior in chess.
thirteen thirteen 2/23/2020 12:23
Unfortunately, you have to be a millionaire to afford the excessively high graphic card upgrade necessary to remotely be performing at those SUPER levels claimed. This £1000 [ish] need is not within every club player budget, I think. Whilst I really do like the new Fritz 17 much awaited 'improvements' as always, as I'm sure so do others, this FACT remains. Am I alone, feeling like I have found a penny, but lost more somewhere?
jimijr jimijr 2/23/2020 01:57
Thanks for this. I've seen games by Alpha Zero that mirrored Nimzovich, restrict - blockade - destroy. And yes, Magnus and others like Naka have started playing g4 lately thanks to Alpha Zero.
jaberwocky jaberwocky 2/23/2020 01:45
Thanks for the article.
The human brain is still the most complicated and mysterious thing known to science.

bring the band
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armies of robots
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