🔬 Research Summary by Andrew W. Reddie, Sarah Shoker, and Leah Walker. Andrew W. Reddie is an Associate Research Professor at the University of California, Berkeley’s Goldman School of Public Policy, and Founder … [Read more...] about Confidence-Building Measures for Artificial Intelligence
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Self-Consuming Generative Models Go MAD
🔬 Research Summary by Josue Casco-Rodriguez and Sina Alemohammad. Josue is a 2nd-year PhD student at Rice University. He is interested in illuminating the intersection of machine learning and neuroscience from … [Read more...] about Self-Consuming Generative Models Go MAD
From OECD to India: Exploring cross-cultural differences in perceived trust, responsibility and reliance of AI and human experts
🔬 Research Summary by Vishakha Agrawal, an independent researcher interested in human-AI collaboration, participatory AI and AI safety. [Original paper by Vishakha Agrawal, Serhiy Kandul, Markus Kneer, and Markus … [Read more...] about From OECD to India: Exploring cross-cultural differences in perceived trust, responsibility and reliance of AI and human experts
Demystifying Local and Global Fairness Trade-offs in Federated Learning Using Partial Information Decomposition
🔬 Research Summary by Faisal Hamman, a Ph.D. student at the University of Maryland, College Park. Faisal’s research focuses on Fairness, Explainability, and Privacy in Machine Learning, where he brings novel foundational … [Read more...] about Demystifying Local and Global Fairness Trade-offs in Federated Learning Using Partial Information Decomposition
Acceptable Risks in Europe’s Proposed AI Act: Reasonableness and Other Principles for Deciding How Much Risk Management Is Enough
🔬 Research Summary by Dr. Henry Fraser, a Research Fellow in Law, Accountability, and Data Science at the Centre of Excellence for Automated Decision-Making and Society. [Original paper by Henry Fraser and … [Read more...] about Acceptable Risks in Europe’s Proposed AI Act: Reasonableness and Other Principles for Deciding How Much Risk Management Is Enough