我看起来像罪犯吗？研究种族呈现如何影响人类对累犯的判断
Do I Look Like a Criminal? Examining how Race Presentation Impacts Human Judgement of Recidivism
摘要：
了解种族信息如何影响在线系统中的人类决策在当今世界至关重要。以前的工作表明，刑事被告的种族信息，当作为一个文本字段，对用户的累犯的判断没有显着的影响。我们复制并扩展了这项工作，以探索如何以及何时种族信息影响用户的判断，就显着性的介绍。我们的研究结果表明，在种族标签中添加照片对女性用户的累犯预测有显著影响，但对男性用户没有影响。被告的种族也影响了这些结果，与白人被告相比，黑人被告更不可能被预测重新犯罪。这些结果对系统设计师如何选择显示种族信息有很大的影响，并提醒研究人员在使用亚马逊土耳其机器人时要注意性别和种族的影响。
英文摘要：
Understanding how racial information impacts human decision making in online systems is critical in today's world. Prior work revealed that race information of criminal defendants, when presented as a text field, had no significant impact on users' judgements of recidivism. We replicated and extended this work to explore how and when race information influences users' judgements, with respect to the saliency of presentation. Our results showed that adding photos to the race labels had a significant impact on recidivism predictions for users who identified as female, but not for those who identified as male. The race of the defendant also impacted these results, with black defendants being less likely to be predicted to recidivate compared to white defendants. These results have strong implications for how system-designers choose to display race information, and cautions researchers to be aware of gender and race effects when using Amazon Mechanical Turk workers.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
