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When people receive advice while making difficult decisions, they often makebetter decisions in the moment and also increase their knowledge in theprocess. However, such incidental learning can only occur when peoplecognitively engage with the information they receive and process thisinformation thoughtfully. How do people process the information and advice theyreceive from AI, and do they engage with it deeply enough to enable learning?To answer these questions, we conducted three experiments in which individualswere asked to make nutritional decisions and received simulated AIrecommendations and explanations. In the first experiment, we found that whenpeople were presented with both a recommendation and an explanation beforemaking their choice, they made better decisions than they did when theyreceived no such help, but they did not learn. In the second experiment,participants first made their own choice, and only then saw a recommendationand an explanation from AI; this condition also resulted in improved decisions,but no learning. However, in our third experiment, participants were presentedwith just an AI explanation but no recommendation and had to arrive at theirown decision. This condition led to both more accurate decisions and learninggains. We hypothesize that learning gains in this condition were due to deeperengagement with explanations needed to arrive at the decisions. This workprovides some of the most direct evidence to date that it may not be sufficientto include explanations together with AI-generated recommendation to ensurethat people engage carefully with the AI-provided information. This work alsopresents one technique that enables incidental learning and, by implication,can help people process AI recommendations and explanations more carefully.

Do People Engage Cognitively with AI? Impact of AI Assistance on Incidental Learning