arXiv AI

Designed by Journalists, but Is It for Readers? Rethinking AI Disclosures and Transparency in News

arXiv:2606. 11116v1 Announce Type: cross Abstract: As newsrooms integrate generative AI, journalists face a disclosure challenge: how to communicate AI involvement in ways that maintain reader trust.

arXiv AI
Jun 9

"So There's a Catch-22 Here": How Early Adopters Who Build Multi-Agent LLM Systems Conceptualize Transparency

arXiv:2606. 08323v1 Announce Type: cross Abstract: Multi-agent large language model (LLM) systems are rapidly emerging, yet transparency, a cornerstone of responsible AI, remains under-defined in these distributed architectures, which have complexities of inter-agent coordination and orchestration.

By Suchismita Naik, Samir Passi, Mihaela Vorvoreanu, Scott Saponas, Amanda Hall
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