Second Article on New Scientist: “A different way of thinking”

“A different way of thinking” by Nello Cristianini

CAN a human-made creature ever surprise its creator, taking initiatives of its own? This question has been asked for centuries, from the golem of Jewish folklore to Frankenstein to I, Robot. There are various answers, but at least one computing pioneer knew well where she stood. “The Analytical Engine has no pretensions whatever to originate anything,” said Ada Lovelace, Charles Babbage’s collaborator, in 1843, removing any doubt about what a computing machine can ever hope to do. “It can do whatever we know how to order it to perform,” she added. “It can follow analysis; but it has no power of anticipating any analytical relations or truths.”

But 173 years later, a computer program developed just over a mile away from her house in London beat a master of the game Go. None of AlphaGo’s programmers can come close to defeating such a strong player, let alone the program they created. They don’t even understand its strategies. This machine has learned to do things that its programmers can’t do and don’t understand.

Far from being an exception, AlphaGo is the new normal. Engineers began creating machines that could learn from experience decades ago, and this is now the key to modern artificial intelligence (AI). We use them every day, usually without realising it.

For programmers who develop such machines, the whole point is to make them learn things that we don’t know or understand well enough to program in directly. This approach – called machine learning – has been extremely fruitful. It is the secret sauce of modern AI and has delivered recent successes (and spectacular failures) in autonomous cars, product recommendations, personal assistants, Go and more.

How can a machine learn? When I was growing up, my bicycle never learned its way home and my typewriter never suggested a word or spotted a spelling mistake. Mechanical behaviour was synonymous with being fixed, predictable and rigid. For a long time, a “learning machine” sounded like a contradiction, yet today we talk happily of machines that are flexible, adaptive, even curious.