‘Artificial stupidity’ made AI trading bots spontaneously form cartels when left unsupervised, Wharton study reveals

A study from University of Pennsylvania’s Wharton School and the Hong Kong University of Science and Technology found that when placed in simulated markets, AI trading bots did not compete with one another, but rather began colluding in price-fixing behaviors. According to the study authors, research on how AI behaves in market environments can help regulators understand gaps in existing rules and statutes. Artificial intelligence is just smart-and stupid-enough to pervasively form price-fixing cartels in financial market conditions if left to their own devices. A working paper posted earlier this year on the National Bureau of Economic Research website from the Wharton School at the University of Pennsylvania and Hong Kong University of Science and Technology found when AI-powered trading agents were released into simulated markets, the bots colluded with one another, engaging in price fixing to make a collective profit. In the study, researchers let bots loose in market models, essentially a computer program designed to simulate real market conditions and train AI to interpret market-pricing data, with virtual market makers setting prices based on different variables in the model. These markets can have various levels of “noise,” referring to the amount of conflicting information and price fluctuation in the various market contexts. While some bots were trained to behave like retail investors and others like hedge funds, in many cases, the machines engaged in “pervasive” price-fixing behaviors by collectively refusing to trade aggressively-without being explicitly told to do so. In one algorithmic model looking at price-trigger strategy, AI agents traded conservatively on signals until a large enough market swing triggered them to trade very aggressively. The bots, trained through reinforcement learning, were sophisticated enough to implicitly understand that widespread aggressive trading could create more market volatility. In another model, AI bots had over-pruned biases and were trained to internalize that if any risky trade led to a negative outcome, they should not pursue that strategy again. The bots traded conservatively in a “dogmatic” manner, even when more aggressive trades were seen as more profitable, collectively acting in a way the study called “artificial stupidity.” “In both mechanisms, they basically converge to this pattern where they are not acting aggressively, and in the long run, it’s good for them,” study co-author and Wharton finance professor Itay Goldstein told Fortune . Financial regulators have long worked to address anti-competitive practices like collusion and price fixing in markets. But in retail, AI has taken the spotlight, particularly as companies using algorithmic pricing come under scrutiny. This month, Instacart , which uses AI-powered pricing tools , announced it will end its program where some customers saw different prices for the same item on the delivery company’s platform. It follows a Consumer Reports analysis found in an experiment that Instacart offered nearly 75% of its grocery items at multiple prices. “For the [Securities and Exchange Commission] and those regulators in financial markets, their primary goal is to not only preserve this kind of stability, but also ensure competitiveness of the market and market...

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