Gods and Robots In this episode of the podcast we shake things up! Neil is on the guest side of the table with his partner Rabbi Laura Janner-Klausner to discuss their upcoming project Gods and Robots. Katherine is joined on the host side by friend of the show professor Michael Littman. See... See More Episodes arXiv Whitepapers Auditing Work: Exploring the New York City algorithmic bias audit regime In July 2023, New York City (NYC) initiated the first algorithm auditing system for commercial machine-learning systems. Local Law 144 (LL 144) mandates NYC-based employers using automated employment decision-making tools (AEDTs) in hiring to undergo annual bias audits conducted by an independent... Epistemic Power, Objectivity and Gender in AI Ethics Labor: Legitimizing Located Complaints What counts as legitimate AI ethics labor, and consequently, what are the epistemic terms on which AI ethics claims are rendered legitimate? Based on 75 interviews with technologists including researchers, developers, open source contributors, artists, and activists, this paper explores various... Measuring machine learning harms from stereotypes: requires understanding who is being harmed by which errors in what ways As machine learning applications proliferate, we need an understanding of their potential for harm. However, current fairness metrics are rarely grounded in human psychological experiences of harm. Drawing on the social psychology of stereotypes, we use a case study of gender stereotypes in image... More featured content News Articles Building explainability into the components of machine-learning models Robots play with play dough Stay in the loop. Subscribe to our newsletter for a weekly update on the latest podcast, news, events, and jobs postings. E-mail Leave this field blank Seeing the whole from some of the parts Keeping web-browsing data safe from hackers In Farming, a Constant Drive For Technology Do AI systems really have their own secret language? The downside of machine learning in health care AI and machine learning are improving weather forecasts, but they won’t replace human experts In bias we trust? In India, Digital Snooping on Sanitation Workers More news