人非圣贤孰能无过:偏见突出有助于克服对医疗人工智能的抵触情绪

IF 9 1区 心理学 Q1 PSYCHOLOGY, EXPERIMENTAL
Mathew S. Isaac , Rebecca Jen-Hui Wang , Lucy E. Napper , Jessecae K. Marsh
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引用次数: 0

摘要

先前的研究表明,许多人对算法表现出反感,并抵制在医疗保健中使用人工智能(AI)。在本研究中,我们发现,如果干预措施能增加决策中偏见的显著性--无论是总体上的还是具体到性别或年龄上的--就会使人们相对更容易接受医疗人工智能。这种对人工智能接受度的提高是因为偏见被认为是人类的根本缺陷。因此,当偏见的前景变得突出时,人们对人工智能完整性的感知就会增强,这种完整性是指人工智能代理相对于人类代理的公平性和可信度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
To err is human: Bias salience can help overcome resistance to medical AI

Prior research has shown that many individuals exhibit an aversion to algorithms and are resistant to the use of artificial intelligence (AI) in healthcare. In the present research, we show that an intervention that increases the salience of bias in decision making—either in general or specifically with respect to gender or age—makes individuals relatively more receptive to medical AI. This increased receptiveness to AI occurs because bias is perceived to be a fundamentally human shortcoming. As such, when the prospect of bias is made salient, perceptions of AI integrity—defined as the perceived fairness and trustworthiness of an AI agent relative to a human counterpart—are enhanced.

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来源期刊
CiteScore
19.10
自引率
4.00%
发文量
381
审稿时长
40 days
期刊介绍: Computers in Human Behavior is a scholarly journal that explores the psychological aspects of computer use. It covers original theoretical works, research reports, literature reviews, and software and book reviews. The journal examines both the use of computers in psychology, psychiatry, and related fields, and the psychological impact of computer use on individuals, groups, and society. Articles discuss topics such as professional practice, training, research, human development, learning, cognition, personality, and social interactions. It focuses on human interactions with computers, considering the computer as a medium through which human behaviors are shaped and expressed. Professionals interested in the psychological aspects of computer use will find this journal valuable, even with limited knowledge of computers.
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