activity
20162023
most citedSeeing Like a Toolkit: How Toolkits Envision the Work of AI Ethics

105 citations · 214 across the 9 of their papers we have counts for

collaborators

9 papers

cs.LG2023★ 12 cited

Scaling Laws Do Not Scale

Fernando Diaz, Michael Madaio

Recent work has advocated for training AI models on ever-larger datasets, arguing that as the size of a dataset increases, the performance of a model trained on that dataset will c…

cs.HC2023

Investigating Practices and Opportunities for Cross-functional Collaboration around AI Fairness in Industry Practice

Wesley Hanwen Deng, Nur Yildirim, Monica Chang +3

An emerging body of research indicates that ineffective cross-functional collaboration -- the interdisciplinary work done by industry practitioners across roles -- represents a maj…

cs.HC2023★ 46 cited

Human-Centered Responsible Artificial Intelligence: Current & Future Trends

Mohammad Tahaei, Marios Constantinides, Daniele Quercia +13

In recent years, the CHI community has seen significant growth in research on Human-Centered Responsible Artificial Intelligence. While different research communities may use diffe…

cs.CY2022★ 105 cited

Seeing Like a Toolkit: How Toolkits Envision the Work of AI Ethics

Richmond Y. Wong, Michael A. Madaio, Nick Merrill

Numerous toolkits have been developed to support ethical AI development. However, toolkits, like all tools, encode assumptions in their design about what work should be done and ho…

cs.AI2021★ 12 cited

Assessing the Fairness of AI Systems: AI Practitioners' Processes, Challenges, and Needs for Support

Michael Madaio, Lisa Egede, Hariharan Subramonyam +2

Various tools and practices have been developed to support practitioners in identifying, assessing, and mitigating fairness-related harms caused by AI systems. However, prior resea…

cs.AI2021★ 23 cited

Stakeholder Participation in AI: Beyond "Add Diverse Stakeholders and Stir"

Fernando Delgado, Stephen Yang, Michael Madaio +1

There is a growing consensus in HCI and AI research that the design of AI systems needs to engage and empower stakeholders who will be affected by AI. However, the manner in which…

cs.CY2021★ 2 cited

Risks of AI Foundation Models in Education

Su Lin Blodgett, Michael Madaio

If the authors of a recent Stanford report (Bommasani et al., 2021) on the opportunities and risks of "foundation models" are to be believed, these models represent a paradigm shif…

cs.CY2021★ 8 cited

Beyond "Fairness:" Structural (In)justice Lenses on AI for Education

Michael Madaio, Su Lin Blodgett, Elijah Mayfield +1

Educational technologies, and the systems of schooling in which they are deployed, enact particular ideologies about what is important to know and how learners should learn. As art…

cs.CY2016★ 6 cited

Firebird: Predicting Fire Risk and Prioritizing Fire Inspections in Atlanta

Michael Madaio, Shang-Tse Chen, Oliver L. Haimson +5

The Atlanta Fire Rescue Department (AFRD), like many municipal fire departments, actively works to reduce fire risk by inspecting commercial properties for potential hazards and fi…