most citedThe Surveillance AI Pipeline

24 citations · 29 across the 5 of their papers we have counts for

collaborators

5 papers

cs.HC2026

Safety Nudges: User-Facing Interventions for Real-Time AI Risk Awareness

Varshini Elangovan, James Wedgwood, Chhavi Yadav +3

Conversational AI systems can pose safety risks to their users such as hallucination, sycophancy, overconfidence, and anthropomorphism, but these risks are difficult for users to d…

cs.CL2026

DelusionEval: Measuring Delusion-Linked Behaviors in AI Chatbots

Jared Moore, Andrea Mock, Yifan Mai +9

Mental health professionals have raised concerns about risks of psychological harm from interaction with large language models (LLMs), including "delusional spirals" in which conce…

cs.CL2026★ 5 cited

Characterizing Delusional Spirals through Human-LLM Chat Logs

Jared Moore, Ashish Mehta, William Agnew +11

As large language models (LLMs) have proliferated, disturbing anecdotal reports of negative psychological effects, such as delusions, self-harm, and ``AI psychosis,'' have emerged…

cs.HC2026

How Professional Visual Artists are Negotiating Generative AI in the Workplace

Harry H. Jiang, Jordan Taylor, William Agnew

Generative AI has been heavily critiqued by artists in both popular media and HCI scholarship. However, more work is needed to understand the impacts of generative AI on profession…

cs.CV2023★ 24 cited

The Surveillance AI Pipeline

Pratyusha Ria Kalluri, William Agnew, Myra Cheng +3

A rapidly growing number of voices argue that AI research, and computer vision in particular, is powering mass surveillance. Yet the direct path from computer vision research to su…