"Biased AI Writing Assistants Shift Users' Attitudes on Societal Issues": People are increasingly using AI writing assistants powered by Large Language Models (LLMs) to provide autocomplete suggestions to help them write in various online settings. However, LLMs often reproduce biased viewpoints in their text, and research from psychology has shown that manipulating people’s behavior can, in turn, influence their attitudes. Can writing with biased suggestions from AI writing assistants impact people’s attitudes in this process? — Sterling Williams-Ceci

"Privacy of Groups in Dense Street Imagery": In this work, we find that increased data density and advancements in artificial intelligence enable harmful group membership inferences from purportedly anonymized data. We perform a penetration test to demonstrate how easily sensitive group affiliations can be inferred from obfuscated pedestrians in 25,232,608 dashcam images taken in New York City. We develop a typology of identifiable groups within DSI and analyze implications for privacy and public space through the lens of contextual integrity. — Matt Franchi

AI governance underscores the AI “supply chain” and the “many hands” involved in the production of AI systems. Even when it addresses downstream risks, the focus remains on AI's producers. Although invaluable and important, this production-centered approach risks overlooking what happens when real people use AI tools. This paper identifies and theorizes AI governance’s missing half, which I call the “demand side.”

The rise of large language models (LLMs) is reshaping knowledge production, raising urgent questions for research communication and publishing writ large. Drawing on qualitative survey responses from over 850 academic book authors from across a range of fields and institutions, we highlight widespread concern about the unlicensed use of in-copyright scientific and scholarly publications for AI training. Most authors are not opposed to generative AI, but they strongly favor consent, attribution, and compensation as conditions for use of their work.