论文标题
人们会认知与人工智能互动吗？ AI援助对偶然学习的影响
Do People Engage Cognitively with AI? Impact of AI Assistance on Incidental Learning
论文作者
论文摘要
当人们在做出艰难决定的同时收到建议时，他们通常会在此刻做出更好的决定，并在此过程中提高知识。但是，这种偶然的学习只有在人们认知地参与收到的信息并经过深思熟虑处理这些信息时才会发生这种偶然的学习。人们如何处理他们从AI中获得的信息和建议，并且他们与之互动以实现学习？为了回答这些问题，我们进行了三个实验，要求个人做出营养决策并收到模拟的AI建议和解释。在第一个实验中，我们发现，当人们在做出选择之前向人们提出建议和解释时，他们做出的决定比没有得到这样的帮助时做出了更好的决定，但他们没有学习。在第二个实验中，参与者首先做出了自己的选择，然后才看到了AI的建议和解释。这种情况也导致了改善的决策，但没有学习。但是，在我们的第三次实验中，参与者仅提供了AI解释，但没有建议，必须做出自己的决定。这种情况导致了更准确的决策和学习成就。我们假设在这种情况下的学习收益是由于对决定所需的解释的更深入的参与。这项工作提供了迄今为止最直接的证据，即包括解释以及AI生成的建议还不足以确保人们仔细地参与AI-提供的信息。这项工作还提出了一种技术，该技术能够逐渐学习，并暗示可以帮助人们更仔细地处理AI建议和解释。
When people receive advice while making difficult decisions, they often make better decisions in the moment and also increase their knowledge in the process. However, such incidental learning can only occur when people cognitively engage with the information they receive and process this information thoughtfully. How do people process the information and advice they receive from AI, and do they engage with it deeply enough to enable learning? To answer these questions, we conducted three experiments in which individuals were asked to make nutritional decisions and received simulated AI recommendations and explanations. In the first experiment, we found that when people were presented with both a recommendation and an explanation before making their choice, they made better decisions than they did when they received no such help, but they did not learn. In the second experiment, participants first made their own choice, and only then saw a recommendation and an explanation from AI; this condition also resulted in improved decisions, but no learning. However, in our third experiment, participants were presented with just an AI explanation but no recommendation and had to arrive at their own decision. This condition led to both more accurate decisions and learning gains. We hypothesize that learning gains in this condition were due to deeper engagement with explanations needed to arrive at the decisions. This work provides some of the most direct evidence to date that it may not be sufficient to include explanations together with AI-generated recommendation to ensure that people engage carefully with the AI-provided information. This work also presents one technique that enables incidental learning and, by implication, can help people process AI recommendations and explanations more carefully.
