Deep reinforcement learning has trained AIs to beat humans at complex games like Go and StarCraft. Could it also do a better job at running the economy?

Income inequality is one of the overarching problems of economics. One of the most effective tools policymakers have to address it is taxation: governments collect money from people according to what they earn and redistribute it either directly, via welfare schemes, or indirectly, by using it to pay for public projects. But though more taxation can lead to greater equality, taxing people too much can discourage them from working or motivate them to find ways to avoid paying - which reduces the overall pot.

Getting the balance right is not easy. Economists typically rely on assumptions that are hard to validate. People's economic behavior is complex, and gathering data about it is hard. Decades of economic research has wrestled with designing the best tax policy, but it remains an open problem.

Scientists at the US business technology company Salesforce think AI can help. Led by Richard Socher, the team has developed a system called the AI Economist that uses reinforcement learning - the same sort of technique behind DeepMind's AlphaGo and AlphaZero - to identify optimal tax policies for a simulated economy.

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