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 An automated way to assemble thousands of objects From a ‘deranged’ provocateur to IBM’s failed AI superproject: the controversial story of how data has transformed healthcare 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 Computers that power self-driving cars could be a huge driver of global carbon emissions Subtle biases in AI can influence emergency decisions AI might be seemingly everywhere, but there are still plenty of things it can’t do – for now A simpler path to better computer vision Solving brain dynamics gives rise to flexible machine-learning models Not everything we call AI is actually ‘artificial intelligence’. Here’s what you need to know Breaking the scaling limits of analog computing The dawn of AI has come, and its implications for education couldn’t be more significant More news