🔬 Research Summary by Changhun Jo, Jy-yong Sohn, Kangwook Lee. Changhun Jo is a PhD candidate at University of Wisconsin-Madison, working on algorithmic fairness, social recommender systems, and machine … [Read more...] about Breaking Fair Binary Classification with Optimal Flipping Attacks
Research Summaries
A Virtue-Based Framework to Support Putting AI Ethics into Practice
🔬 Research Summary by Thilo Hagendorff, an AI ethicist at the University of Tuebingen (Germany). [Original paper by Thilo Hagendorff] Overview: A virtue-based approach specific to the AI field is a missing … [Read more...] about A Virtue-Based Framework to Support Putting AI Ethics into Practice
Who Audits the Auditors? Recommendations from a field scan of the algorithmic auditing ecosystem
🔬 Research summary by Connor Wright, our Partnerships Manager. [Original paper by Sasha Costanza-Chock, Inioluwa Deborah Raji, Joy Buolamwini] Overview: The AI audit field is now larger than ever as a … [Read more...] about Who Audits the Auditors? Recommendations from a field scan of the algorithmic auditing ecosystem
Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation
🔬 Research Summary by Angelina Wang, a PhD student in computer science at Princeton University studying issues of machine learning fairness and algorithmic bias. [Original paper by Angelina Wang, Vikram V. … [Read more...] about Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation
Assessing the Fairness of AI Systems: AI Practitioners’ Processes, Challenges, and Needs for Support
🔬 Research Summary by Michael A. Madaio, a postdoctoral researcher at Microsoft Research, where his research is at the intersection of HCI and FATE (Fairness, Accountability, Transparency, and Ethics) in AI. … [Read more...] about Assessing the Fairness of AI Systems: AI Practitioners’ Processes, Challenges, and Needs for Support