Using AI can improve decisions, but only when its recommendations are worth following.

The same behavior, relying on AI, can help or harm depending on recommendation quality.

People don’t consistently accept good recommendations or reject poor ones.

Perceived trustworthiness and confidence shape use more than actual recommendation quality.

Spend a few minutes scrolling through posts about AI, and you’ll see a divide. On one side are warnings about hallucinations, errors, and the risks of relying on a system that can sound confident while being wrong. On the other is a growing comfort with using it for just about everything — drafting, planning, even making decisions — sometimes with surprisingly little scrutiny.

That divide makes it seem like the main question is how much weight we should give AI’s recommendations. But that may not be the right question. Across two recent studies, my colleagues and I looked at how people actually use AI when making decisions. The results don’t fit neatly with the idea that the problem is simply using it too much or not enough.

What Happens When People Use AI

In two studies, we asked people to complete a relatively simple decision task — selecting a small set of items from a larger pool of options[1]. In the first study, they could decide whether to view ChatGPT’s recommendations before making their choices. In the second, they completed the task first, were then shown ChatGPT’s recommendations — with half receiving lower-quality suggestions — and were given the chance to revise their answers.

This setup lets us look at something that often gets overlooked in discussions about AI. Not just whether people use it, but what they do with what it produces once........

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