96 citations · 234 across the 7 of their papers we have counts for
7 papers
The Fair Lending Model: How the Longest-Running Algorithmic Fairness Programs Work in Practice
Emily Black, Miranda Bogen, Logan Koepke +3
U.S. financial institutions subject to fair lending laws have been running algorithmic fairness programs for decades. Despite this long history, remarkably little is known about ho…
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…
Towards "Anytime, Anywhere" Community Learning and Engagement around the Design of Public Sector AI
Wesley Hanwen Deng, Motahhare Eslami, Kenneth Holstein
Data-driven algorithmic and AI systems are increasingly being deployed to automate or augment decision processes across a wide range of public service settings. Yet community membe…
Understanding Practices, Challenges, and Opportunities for User-Engaged Algorithm Auditing in Industry Practice
Wesley Hanwen Deng, Bill Boyuan Guo, Alicia DeVrio +3
Recent years have seen growing interest among both researchers and practitioners in user-engaged approaches to algorithm auditing, which directly engage users in detecting problema…
Beyond General Purpose Machine Translation: The Need for Context-specific Empirical Research to Design for Appropriate User Trust
Wesley Hanwen Deng, Nikita Mehandru, Samantha Robertson +1
Machine Translation (MT) has the potential to help people overcome language barriers and is widely used in high-stakes scenarios, such as in hospitals. However, in order to use MT…
Exploring How Machine Learning Practitioners (Try To) Use Fairness Toolkits
Wesley Hanwen Deng, Manish Nagireddy, Michelle Seng Ah Lee +4
Recent years have seen the development of many open-source ML fairness toolkits aimed at helping ML practitioners assess and address unfairness in their systems. However, there has…
Value Cards: An Educational Toolkit for Teaching Social Impacts of Machine Learning through Deliberation
Hong Shen, Wesley Hanwen Deng, Aditi Chattopadhyay +3
Recently, there have been increasing calls for computer science curricula to complement existing technical training with topics related to Fairness, Accountability, Transparency, a…