AI and Philosophy

‘There’s This Deep mystery of what, actually, is this thing?’: the philosopher inside Google DeepMind AI.

Since 2017, Iason Gabriel has worked at the tech giant, trying to anticipate – and think through – the impact of AI. But as commercial and geopolitical pressures escalate, can ethicists make any difference?

In 2017, a 33-year-old political philosopher named Iason Gabriel was told by a friend that he ought to apply for a job at DeepMind, the London-based subsidiary of Google where much of its AI research was concentrated. The suggestion was not an obvious one.

Gabriel was a cheerful but intense junior academic with a passion for Vipassana meditation and what his brother calls “enthusiastic” rock climbing. The eldest son of a Greek management professor and a British documentary maker, Gabriel split his time between teaching and international development work. At the University of Oxford, where he was a fellow at St John’s College, Gabriel taught courses on political theory and wrote papers on the moral contortions of “yuppie ethics” and the ethical blind spots of effective altruism. When he wasn’t there, he did crisis work for the United Nations Development Programme in Sudan and Lebanon.

DeepMind, meanwhile, was the world’s leading AI research lab. In part, this was because it had the financial and computational backing of Google, which had bought the company in 2014 for $650m. In part, it was because DeepMind had recently shown it could put those resources to stunning use. In Seoul, in 2016, a DeepMind system called AlphaGo defeated Lee Sedol, a South Korean Go champion, in a five-game match. The victory was significant not least because of Go’s legendary complexity; the game has more possible configurations than there are atoms in the universe.

Thanks to the fuss around AlphaGo, Gabriel was aware of DeepMind. Still, he found his friend’s suggestion puzzling: why did a company that made game-playing robots need an ethicist? The answer, as he soon learned, was that the company had its sights set much higher than Go. DeepMind was founded in 2010 by three men – Demis Hassabis, Shane Legg and Mustafa Suleyman – who believed that it must be possible to develop artificial general intelligence, or AGI. By this they meant computer systems that could match, and maybe surpass, human cognitive capabilities. When they started the company, this was not a popular view: to speak of AI, let alone AGI, was considered by many a sign of fatal unseriousness. Hassabis, Legg and Suleyman were undeterred. Their ambition, as they liked to say, was to “solve intelligence, and then solve everything else”.

For the DeepMind founders, it was clear that such an achievement would have widespread consequences. In 1999, when Legg was fresh out of university, he estimated that AGI would arrive somewhere between 2025 and 2028, a prediction he maintained in the face of much mockery for three decades. In his dissertation, completed in 2008, he insisted that society could not afford to wait until AGI was technically feasible to consider its effects: “We need to be seriously working on these things now.” More recently, Legg told me it was “obvious” why the company needed people like Gabriel on staff: “If you’re making some widget, and it’s probably not going to change the world, then maybe you don’t need a moral philosopher. But if you take AGI seriously, then I can’t really see how you wouldn’t consider this sort of thing as important.”

After starting at DeepMind in 2017, Gabriel was, for a time, the only active philosopher working at a frontier AI lab. He quickly discovered that his background in moral philosophy and political theory gave him an unusual perspective in an industry dominated by engineers. Over the past decade, he has assembled a body of work that tracked, and in many cases predicted, the ethical challenges created by the surprising success of large language models (LLMs).

As Dylan Hadfield-Menell, who leads the Algorithmic Alignment Group at MIT, told me, Gabriel was “the right person meeting the moment. As the field was ready to mature and move into prime time, he figured out a way to broaden the horizons without attacking or denigrating the work that came before.”

More generally, Gabriel has been a leading advocate for the idea that the current wave of AI development demands not just new technical vocabularies but also new ways of thinking about our relationship to technology, and even to ourselves. As he put it to me recently, in one of several long conversations we’ve had over the past few months, “I can take any technological artefact and ask: is it wise? Is it just? Is it caring? And the answer is no. But the depth of the question when it comes to AI – including what kind of ethics is appropriate to it – is hard to overstate. I sometimes feel like it’s very hard to look at AI directly. There’s this deep mystery there, which is: but what actually is this thing? We have a very literal answer, but the literal answer doesn’t seem to necessarily provide a moral answer.”

- Author: Robert P Baird, The Guardian

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