A Scoping Study of Evaluation Practices for Responsible AI Tools: Steps Towards Effectiveness Evaluations
Glen Berman, Nitesh Goyal, Michael Madaio
Abstract
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.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 084c4bc4-c007-400c-a041-eb46b5455c2aCited by top-tier papers12
- Towards AI Accountability Infrastructure: Gaps and Opportunities in AI Audit ToolingVictor Ojewale, Ryan Steed, Briana Vecchione, Abeba Birhane et al.CHI 2025 · 46 citations
- ASHABot: An LLM-Powered Chatbot to Support the Informational Needs of Community Health WorkersPragnya Ramjee, Mehak Chhokar, Bhuvan Sachdeva, Mahendra Meena et al.CHI 2025 · 26 citations
- Participatory AI Considerations for Advancing Racial Health EquityAndrea G. Parker, Laura M. Vardoulakis, Jatin Alla, Christina N. HarringtonCHI 2025 · 15 citations
- Improving Governance Outcomes Through AI Documentation: Bridging Theory and PracticeAmy A. Winecoff, Miranda BogenCHI 2025 · 13 citations
- Knowledge Workers' Perspectives on AI Training for Responsible AI UseAngie Zhang, Min Kyung LeeCHI 2025 · 13 citations
Builds on22
- Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine LearningHarmanpreet Kaur, Harsha Nori, Samuel Jenkins, Rich Caruana et al.CHI 2020 · 541 citations
- Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AIMichael A. Madaio, Luke Stark, Jennifer Wortman Vaughan, Hanna M. WallachCHI 2020 · 428 citations
- Where Responsible AI meets Reality: Practitioner Perspectives on Enablers for Shifting Organizational PracticesBogdana Rakova, Jingying Yang, Henriette Cramer, Rumman ChowdhuryCSCW 2021 · 326 citations
- Everyday Algorithm Auditing: Understanding the Power of Everyday Users in Surfacing Harmful Algorithmic BehaviorsHong Shen, Alicia DeVos, Motahhare Eslami, Kenneth HolsteinCSCW 2021 · 156 citations
- Assessing the Fairness of AI Systems: AI Practitioners' Processes, Challenges, and Needs for SupportMichael Madaio, Lisa Egede, Hariharan Subramonyam, Jennifer Wortman Vaughan et al.CSCW 2022 · 149 citations
Related papers
- RAI Guidelines: Method for Generating Responsible AI Guidelines Grounded in Regulations and Usable by (Non-)Technical RolesMarios Constantinides, Edyta Paulina Bogucka, Daniele Quercia, Susanna Kallio et al.CSCW 2024 · 28 citations
- Designing Responsible AI: Adaptations of UX Practice to Meet Responsible AI ChallengesQiaosi Wang, Michael Madaio, Shaun K. Kane, Shivani Kapania et al.CHI 2023 · 90 citations
- Guidelines for Integrating Value Sensitive Design in Responsible AI ToolkitsMalak Sadek, Marios Constantinides, Daniele Quercia, Céline MougenotCHI 2024 · 49 citations
- Tinker, Tailor, Configure, Customize: The Articulation Work of Contextualizing an AI Fairness ChecklistMichael A. Madaio, Jingya Chen, Hanna M. Wallach, Jennifer Wortman VaughanCSCW 2024 · 13 citations
- Seeing Like a Toolkit: How Toolkits Envision the Work of AI EthicsRichmond Y. Wong, Michael A. Madaio, Nick MerrillCSCW 2023 · 108 citations
