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 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... Large language models cannot replace human participants because they cannot portray identity groups Large language models (LLMs) are increasing in capability and popularity, propelling their application in new domains -- including as replacements for human participants in computational social science, user testing, annotation tasks, and more. Traditionally, in all of these settings survey... Semantic Sensitivities and Inconsistent Predictions: Measuring the Fragility of NLI Models Recent studies of the emergent capabilities of transformer-based Natural Language Understanding (NLU) models have indicated that they have an understanding of lexical and compositional semantics. We provide evidence that suggests these claims should be taken with a grain of salt: we find that state... More featured content News Articles Computers that power self-driving cars could be a huge driver of global carbon emissions Subtle biases in AI can influence emergency decisions 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 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 Spotting plastic waste from space and counting the fish in the seas: here’s how AI can help protect the oceans In machine learning, synthetic data can offer real performance improvements More news