A Scoping Study of Evaluation Practices for Responsible AI Tools: Steps Towards Effectiveness Evaluations

要旨

Responsible design of AI systems is a shared goal across HCI and AI communities. Responsible AI (RAI) tools have been developed to support practitioners to identify, assess, and mitigate ethical issues during AI development. These tools take many forms (e.g., design playbooks, software toolkits, documentation protocols). However, research suggests that use of RAI tools is shaped by organizational contexts, raising questions about how effective such tools are in practice. To better understand how RAI tools are—and might be—evaluated, we conducted a qualitative analysis of 37 publications that discuss evaluations of RAI tools. We find that most evaluations focus on usability, while questions of tools’ effectiveness in changing AI development are sidelined. While usability evaluations are an important approach to evaluate RAI tools, we draw on evaluation approaches from other fields to highlight developer- and community-level steps to support evaluations of RAI tools’ effectiveness in shaping AI development practices and outcomes.

著者
Glen Berman
Australian National University, Canberra, ACT, Australia
Nitesh Goyal
Google Research, New York, New York, United States
Michael Madaio
Google Research, New York, New York, United States
論文URL

doi.org/10.1145/3613904.3642398

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Ethics of Digital Technologies B

318B
5 件の発表
2024-05-14 18:00:00
2024-05-14 19:20:00