🔬 Event summary by Connor Wright, our Partnerships Manager. Overview: A summary of our panel discussion “Now I’m Seen: An AI Ethics
Ethics of AI in Education: Towards a Community-wide Framework
🔬 Research Summary by Wayne Holmes, a learning sciences and innovation researcher who teaches at University College London, is a consultant researcher
Performative Power
🔬 Research Summary by Meena Jagadeesan and Celestine Mendler-Dünner. Meena Jagadeesan is a PhD student in Computer Science at UC Berkeley. Her
FaiRIR: Mitigating Exposure Bias from Related Item Recommendations in Two-Sided Platforms
🔬 Research Summary by Abhisek Dash, a PhD student (TCS Research Fellow) at the Department of Computer Science and Engineering, Indian Institute of
Breaking Fair Binary Classification with Optimal Flipping Attacks
🔬 Research Summary by Changhun Jo, Jy-yong Sohn, Kangwook Lee. Changhun Jo is a PhD candidate at University of Wisconsin-Madison, working on
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
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
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
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
Let Users Decide: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse
Summary contributed by Martin Pawelczyk, a PhD student at the University of Tübingen working on interpretability of machine learning models with a
The Larger The Fairer? Small Neural Networks Can Achieve Fairness for Edge Devices
Summary contributed by Yi Sheng, a Ph.D. student at George Mason University, advised by Weiwen Jiang, and interested in software and hardware
Visions of Artificial Intelligence and Robots in Science Fiction: a computational analysis
🔬 Research summary by Connor Wright, our Partnerships Manager. [Original paper by Hirotaka Osawa, Dohjin Miyamoto, Satoshi Hase, Reina Saijo,