Michael Wooldridge is like the teacher you wish you had: approachable, able to explain difficult things in simple terms, and genuinely enthusiastic about his work. 'I love it when you see the light go on in somebody, when they understand something that they didn't understand before,' he says. 'I find that incredibly gratifying.'
As an Oxford professor with more than 500 scientific articles and 10 books, he is far from ordinary. His favorite work is his contribution to Ladybird's Expert Books on artificial intelligence. 'I'm very proud of this,' he says, handing a copy from his bookshelf. In his study at Oxford's computing department, our discussion takes the form of a seminar.
Game Theory and Real-World Applications
Wooldridge's latest book, Life Lessons from Game Theory: The Art of Thinking Strategically in a Complex World, translates game theory into 21 digestible scenarios. 'It is surprising how many global events can be explained by a relatively small number of game theoretic models,' he says. One simple model is the game of 'chicken,' illustrated by the James Dean movie Rebel Without a Cause. Two teenagers drive cars toward a cliff; the first to jump is the 'chicken.' This plays out in real life, such as the US-Iran conflict. 'You've got two sides with ever-escalating threats; somebody's got to back down,' Wooldridge says. 'The danger is, if neither backs down, you get the worst-case scenario.'
Communication and third-party incentives can help. 'One of the ways a game can get changed is if a third party provides an incentive for one party to behave differently.' Being unpredictable is also a classic strategy, but it makes it hard for the opponent to respond.
Zero-Sum Mentality and Its Dangers
The concept of 'zero-sum game' is widely misunderstood. A zero-sum game is not simply one where one side gains what the other loses; it is where the incentive is to make your opponent lose as badly as possible. 'This zero-sum mentality is very damaging. It's a very male trait,' Wooldridge says. 'The evidence is that you end up not necessarily doing as well in life, and you end as a more miserable person.' He advocates for the Veil of Ignorance thought experiment, which incentivizes socially desirable outcomes while following self-interest.
AI and Silicon Valley
Wooldridge has worked in AI for over 30 years and retains healthy skepticism. In his 2023 Christmas lectures, he used a robotic dog to explain reinforcement learning. He notes that the core techniques driving the AI revolution were invented by the mid-80s, but computers weren't powerful enough. The breakthrough of GPT-3 in 2020 was based on OpenAI's bet that scaling up would deliver results. 'A lot of people, including me, were skeptical,' he says. 'But it turned out to be a successful bet.'
However, AI pioneers may be reaching limits. Wooldridge thinks expectations for AGI are overoptimistic. 'We don't have AI that could come into your house, locate the kitchen, and clear the dinner table.' Data is now a real constraint. 'The whole of Wikipedia made up just 3% of GPT-3's training data. Where do you get 10 times more data?' The NHS holds valuable data, but selling it could lead to dystopian scenarios.
Silicon Valley's Dominance
Wooldridge resents how Silicon Valley has dominated AI. 'We have seen the narrative stolen by Silicon Valley, promoting a version of AI that me and my colleagues have no interest in building.' He points to benefits like an AI tool that analyzes heart scans via mobile phone. 'This is the kind of expensive stuff the NHS struggles to provide, now available at negligible cost.'
He won the Royal Society's Faraday prize in 2025 and gave a lecture titled This Is Not the AI We Were Promised. He speculates on an AI 'Hindenburg moment' but says existential risks from AI are not in his top five concerns. Nuclear war is a greater threat.
Slowing AI Development
Wooldridge would slow AI development to understand what's going on. It's a classic 'prisoner's dilemma': AI companies are locked in a race, spending more resources with no net benefit. 'We've got wealthy companies pursuing AI while saying they're afraid something will go wrong. Why? Because they think if they back down, somebody else will.'
He advises students to study what they're passionate about. 'I didn't get into computing for a good job. I got into it because I was really interested.' His book Life Lessons from Game Theory is published on 21 May.
