信任还是思考：认知强迫功能可以减少人工智能辅助决策中对AI的过度依赖
To Trust or to Think: Cognitive Forcing Functions Can Reduce Overreliance on AI in AI-assisted Decision-making
摘要：
由人工智能驱动的决策支持工具支持的人经常过度依赖人工智能：他们接受人工智能的建议，即使该建议是错误的。在人工智能决策中添加解释似乎并不能减少过度依赖，一些研究表明，它甚至可能会增加过度依赖。根据认知的双过程理论，我们认为，人们很少对每个人工智能建议和解释进行分析，而是对是否以及何时遵循人工智能建议进行一般性的分析。基于先前对医疗决策的研究，我们设计了三种认知强迫干预措施，以迫使人们更仔细地参与人工智能生成的解释。我们进行了一项实验（N=199），将我们的三种认知强迫设计与两种简单可解释的人工智能方法和一种无人工智能基线进行了比较。结果表明，与简单的可解释AI方法相比，认知强迫显著降低了过度依赖。然而，有一个权衡：人们给那些最能减少过度依赖的设计分配了最不有利的主观评级。为了审计我们对干预产生的不平等的工作，我们调查了我们的干预是否平等地使具有不同认知需求水平的人受益（即，积极参与有意义的心理活动）。我们的研究结果表明，平均而言，认知强迫干预使参与者在认知需求方面受益更多。我们的研究表明，人类的认知动机会调节可解释的人工智能解决方案的有效性。
英文摘要：
People supported by AI-powered decision support tools frequently overrely on the AI: they accept an AI's suggestion even when that suggestion is wrong. Adding explanations to the AI decisions does not appear to reduce the overreliance and some studies suggest that it might even increase it. Informed by the dual-process theory of cognition, we posit that people rarely engage analytically with each individual AI recommendation and explanation, and instead develop general heuristics about whether and when to follow the AI suggestions. Building on prior research on medical decision-making, we designed three cognitive forcing interventions to compel people to engage more thoughtfully with the AI-generated explanations. We conducted an experiment (N=199), in which we compared our three cognitive forcing designs to two simple explainable AI approaches and to a no-AI baseline. The results demonstrate that cognitive forcing significantly reduced overreliance compared to the simple explainable AI approaches. However, there was a trade-off: people assigned the least favorable subjective ratings to the designs that reduced the overreliance the most. To audit our work for intervention-generated inequalities, we investigated whether our interventions benefited equally people with different levels of Need for Cognition (i.e., motivation to engage in effortful mental activities). Our results show that, on average, cognitive forcing interventions benefited participants higher in Need for Cognition more. Our research suggests that human cognitive motivation moderates the effectiveness of explainable AI solutions.
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