不要只告诉我,要问我:人工智能系统将解释智能地框架为问题,比因果人工智能解释提高了人类逻辑识别的准确性

Valdemar Danry, Pat Pataranutaporn, Yaoli Mao, P. Maes
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引用次数: 1

摘要

批判性思维是一项基本的人类技能。尽管批判性思维很重要,但研究表明,我们的推理能力受到个人偏见和认知资源限制的影响,从而导致潜在的危险结果。本文提出了人工智能框架提问的新思想,将与人工智能分类相关的信息转化为问题,以积极参与用户的思考并支撑他们的推理过程。我们对204名参与者进行了一项研究,比较了人工智能框架提问对批判性思维任务的影响;辨别社会分裂言论的逻辑有效性。我们的研究结果表明,与没有反馈甚至是一个始终正确的系统的因果AI解释相比,AI框架的提问显着提高了人类对逻辑错误陈述的识别能力。我们的实验举例说明了未来人类-人工智能共同推理系统的风格,其中人工智能成为批判性思维的刺激物,而不是信息讲述者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Don’t Just Tell Me, Ask Me: AI Systems that Intelligently Frame Explanations as Questions Improve Human Logical Discernment Accuracy over Causal AI explanations
Critical thinking is an essential human skill. Despite the importance of critical thinking, research reveals that our reasoning ability suffers from personal biases and cognitive resource limitations, leading to potentially dangerous outcomes. This paper presents the novel idea of AI-framed Questioning that turns information relevant to the AI classification into questions to actively engage users’ thinking and scaffold their reasoning process. We conducted a study with 204 participants comparing the effects of AI-framed Questioning on a critical thinking task; discernment of logical validity of socially divisive statements. Our results show that compared to no feedback and even causal AI explanations of an always correct system, AI-framed Questioning significantly increase human discernment of logically flawed statements. Our experiment exemplifies a future style of Human-AI co-reasoning system, where the AI becomes a critical thinking stimulator rather than an information teller.
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