论文标题

设计AI,以与年轻女性一起在线到在线安全风险:社交匹配的背景

Designing AI for Online-to-Offline Safety Risks with Young Women: The Context of Social Matching

论文作者

Zytko, Douglas, Aljasim, Hanan

论文摘要

在该职位上,我们提请人们注意针对青年和年轻人的安全风险,这些风险源于在线和面对面的互动,以及AI解决这些风险的机会。我们的研究背景是社会匹配系统(例如,Tinder,Bumble),这些系统被年轻人用于与陌生人的在线访问互动,并且与在线和亲自的性暴力相关。该论文介绍了正在进行的参与性AI设计研究的早期见解,其中年轻妇女建立了可解释的模型,以检测与发现的社交机会相关的风险,并阐明一旦发现了风险,AI应该做什么。我们寻求倡导参与性的AI设计,以此将青年和年轻人直接融入更安全的互联网设计中。我们还提请人们注意该方法的挑战。

In this position paper we draw attention to safety risks against youth and young adults that originate through the combination of online and in-person interaction, and opportunities for AI to address these risks. Our context of study is social matching systems (e.g., Tinder, Bumble), which are used by young adults for online-to-offline interaction with strangers, and which are correlated with sexual violence both online and in-person. The paper presents early insights from an ongoing participatory AI design study in which young women build directly explainable models for detecting risk associated with discovered social opportunities, and articulate what AI should do once risk has been detected. We seek to advocate for participatory AI design as a way to directly incorporate youth and young adults into the design of a safer Internet. We also draw attention to challenges with the method.

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