arXiv AI

Investigating the Impacts of Generative AI on Information Seeking

arXiv AI
Sep 10

Ordinary, Reasonable Chatbots: Do AI Models Track Human Legal Judgments?

The paper investigates whether large language model (LLM) chatbots can emulate human legal judgments of reasonableness. By comparing responses from 26 LLMs to those of human participants across 25 legal scenarios, the study finds that chatbots generally track human answers but tend to produce more homogeneous, government‑ and corporation‑friendly responses and align more closely with white, male, older, and more educated respondents. The authors note that these patterns warrant further systematic research.

By Nirav Patel, Emily Wenger, Christopher Buccafusco
arXiv AI
Jun 2

VET: A Framework for Analyzing AI Discourse

arXiv:2606. 01929v1 Announce Type: new Abstract: Public discourse on AI has become polarized; exaggerated positions on AI in traditional and social media threaten the development of AI Literacy among the general public.

By Meredith Ringel Morris
arXiv AI
4d ago

Personalizing Personal Health Interfaces: Co-Design with Generative AI

The paper explores how generative AI can lower the barrier to personalizing health dashboards by enabling users to co-design interfaces in Figma Make. In a study with 14 participants, redesigns of Google and Apple Health focused on personal context, future planning, and interactive experiences, though conversational AI designs tended toward chat-window conventions. AI facilitated the materialization of loosely articulated ideas, yet model defaults and generation latency influenced iteration, and the process highlighted interpretability and accountability over privacy, trust, and emotional safety.

By Karthik S. Bhat, Vidhi Shah, Vedika Agnihotri, Dong Whi Yoo, Koustuv Saha