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🔬 Research Summary by Kenneth Church, a researcher who works on natural language processing, information retrieval, artificial intelligence and machine learning. [Original paper by Kenneth Church, Annika Schoene, … [Read more...] about Emerging trends: Unfair, biased, addictive, dangerous, deadly, and insanely profitable

🔬 Research Summary by Travis Greene, an Assistant Professor at Copenhagen Business School's Department of Digitalization with an interdisciplinary background in philosophy and research interests in data science ethics … [Read more...] about Atomist or holist? A diagnosis and vision for more productive interdisciplinary AI ethics dialogue

🔬 Research Summary by Lin Guan, a Ph.D. student at the School of Computing and Augmented Intelligence at Arizona State University, working at the Yochan Lab (AI Lab) under the supervision of Dr. Subbarao … [Read more...] about Relative Behavioral Attributes: Filling the Gap between Symbolic Goal Specification and Reward Learning from Human Preferences

🔬 Research Summary by Diogo Leitão, a Machine Learning Researcher at Feedzai. [Original paper by Diogo Leitão, Pedro Saleiro, Mário A. T. Figueiredo, Pedro Bizarro] Overview: Human-AI collaboration (HAIC) in … [Read more...] about Human-AI Collaboration in Decision-Making: Beyond Learning to Defer

🔬 Research Summary by Subho Majumdar, the founder of AI Vulnerability Database, co-founder of Bias Buccaneers and Trustworthy ML Initiative. [Towards Algorithmic Fairness in Space-Time: Filling in Black Holes by … [Read more...] about Towards Algorithmic Fairness in Space-Time: Filling in Black Holes and Detecting Bias in the Presence of Spatial Autocorrelation