Garry Kasparov is not only humanity’s greatest ever chess player but its highest-profile victim of artificial intelligence. His loss to IBM’s super computer Deep Blue in 1997 made global headlines and left him feeling bitter and, well, blue. Yet there is a warm glint in his eye when he talks about AlphaZero, the game-changing chess program that took just four hours to teach itself to become the strongest in history.

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“For me, as a very sharp and attacking player, it is a pleasure watching AlphaZero play,” he said after playing in a charity tournament for Chess in Schools before the London Chess Classic, which runs until Monday. “We all expect machines to play very solid and slow games but AlphaZero just does the opposite. It is surprising to see a machine playing so aggressively, and it also shows a lot of creativity. It is a real breakthrough – and I believe it could be extremely helpful for many other studies in the field of computer science.”

Aggressive. Creative. Helpful. These are words you might not normally associate with artificial intelligence. Indeed, they sound rather human. But for AlphaZero’s creator, Demis Hassabis, the CEO of Deep Mind, this is just the start of what it might be able to do. As he points out, the next step is to use its capabilities to solve real-world problems – such as protein folding, which is responsible for diseases including Alzheimer’s, Parkinson’s and cystic fibrosis. But he also expects AlphaZero to be able to develop stronger and lighter materials, better medicines and eventually become flexible enough to adapt to new situations.

“Deep Blue could play chess well,” explains Hassabis. “But that is all it could do. It couldn’t play noughts and crosses or Connect 4, or any such simple games. In other words, it couldn’t demonstrate two components which are core to what defines human intelligence – our flexible intelligence and our learning capacity.”

AlphaZero is different. In a long-awaited paper published in the journal Science last week, the authors explain how it learned to conquer Chess, Go and Shogi by playing millions of games against itself via a process of trial and error called reinforcement learning. In more than 1,000 games against Stockfish, a regular winner of the computer chess world championship, it won 155 games with only six defeats, with the rest drawn.

Facebook Twitter Pinterest Garry Kasparov and Terry Chapman play chess against the inventor of the Alpha Zero, Deepmind’s Demis Hassabis, and Matthew Sadler at the Google HQ London. Photograph: Lennart Ootes/AlphaZero

Hassabis was a child chess prodigy, who learned the game aged four and was able to beat his dad three weeks later – indeed, when he started playing competitively he was so small he had to bring a pillow with him to reach the board – and became a strong player. Yet in AlphaZero’s case there was no human input, other than telling it the rules of each game. “In a matter of a few hours it was superhuman,” Hassabis says proudly.

The next logical step, he agrees, would be for AlphaZero to attempt to master games with hidden information, such as poker or the computer game Starcraft 2. “Those are big challenges but we’ll have something interesting to say about those in the next 12 months,” he says. “It would very interesting if it could play nine-player Texas No Limit poker, with all the bluffing involved. No computer is yet able to do that but we think AlphaZero could, if we decided to do it.”

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Before setting up DeepMind in 2010, Hassabis worked in computer games, including being the lead AI programmer on the iconic god game Black & White. So does he ever worry that the machines could become our gods? “Powerful technologies, and AI is no different, are neutral in themselves,” he says. “So it depends on society and humanity. How we decide to share the gains is also going to determine whether it is good or bad for the world.”

That doesn’t sound entirely like a flat “no”. But Hassabis is a big believer in human ingenuity. “I think that given enough time and enough human brainpower we will address these questions,” he says. “We are at quite a nascent stage when it comes to understanding how AlphaZero is making decisions. Us and many other teams are now reverse-engineering these systems, and building visualisation and other analysis tools. In five years’ time we will have tools that allow us to look inside this black box and really understand what it does.”

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Kasparov, who last year published Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins, a well received book on his match against Deep Blue and the future of AI, agrees that we should be optimistic.

“I don’t see a shred of intelligence that AI will take over despite this anxiety and fear among the public,” he says. “This is a Hollywood dystopian view. In reality I believe AI will help tremendously and it is much more likely that we and computers will collaborate together for the benefit of humanity.”

Hassabis says that he would actually be more worried about the state of the world without the prospect of better AI in the future. “Look at the problems the world faces. We need cures for tragic diseases, such as cancer and Alzheimer’s, which are also costly to treat. I think AI could help with those kinds of things as well as helping find new drugs, new materials and to better analyse climate change.”

So how would he assuage the fears of doubters? “Ask yourself, if we didn’t have something like AI coming down the line how would we solve these problems?” he says. “Either we are going to need an exponential improvement in human behaviour, so we become more collaborative and less selfish and short term, or we have got to have an exponential improvement in technology to solve the big problems we are creating for ourselves. I don’t see much evidence for the former.”

• This article was amended on 12 December 2018. An earlier version referred to the AlphaZero chess programme. The spelling should have been “program” in accordance with our style guidelines for references to computer programs.