计算机科学
空格(标点符号)
人机交互
领域(数学分析)
可信赖性
人在回路中
人工智能应用
贷款
人工智能
人类智力
用户界面
计算机安全
数学分析
数学
操作系统
财务
经济
作者
Yuri Nakao,Lorenzo Strappelli,Simone Stumpf,Aisha Naseer,Daniele Regoli,Giulia Del Gamba
标识
DOI:10.1080/10447318.2022.2067936
摘要
With Artificial intelligence (AI) to aid or automate decision-making advancing rapidly, a particular concern is its fairness. In order to create reliable, safe and trustworthy systems through human-centred artificial intelligence (HCAI) design, recent efforts have produced user interfaces (UIs) for AI experts to investigate the fairness of AI models. In this work, we provide a design space exploration that supports not only data scientists but also domain experts to investigate AI fairness. Using loan applications as an example, we held a series of workshops with loan officers and data scientists to elicit their requirements. We instantiated these requirements into FairHIL, a UI to support human-in-the-loop fairness investigations, and describe how this UI could be generalized to other use cases. We evaluated FairHIL through a think-aloud user study. Our work contributes better designs to investigate an AI model’s fairness—and move closer towards responsible AI.
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