arXiv:2607. 24243v1 Announce Type: new Abstract: Mainstream AI research emphasises capability growth and tolerates low failure rates when average-case performance is high.
By Keivan Navaie
arXiv:2608. 05656v1 Announce Type: cross Abstract: Safety risks of AI are becoming increasingly evident in human interactions with AI technologies.
By Jessica Y. Bo, Paula Akemi Aoyagui, Shalaleh Rismani, Dipto Das, Syed Ishtiaque Ahmed, Ashton Anderson
arXiv:2505. 22829v2 Announce Type: replace-cross Abstract: This paper bridges distribution shift and AI safety through a comprehensive analysis of their conceptual and methodological synergies.
By Chenruo Liu, Kenan Tang, Yao Qin, Qi Lei
Large language models (LLMs) have become significant providers of mental health support, yet they remain products of an attention economy whose operational and commercial targets favour sustained engagement over the friction that effective psychological support often requires. Developers' safety responses have been largely reactive, addressing the most visible and acute harms while subtler, longer-term patterns of risk (e.
arXiv:2609.05749v1 Announce Type: new
Abstract: Work on the risks of artificial intelligence has focused predominantly on capability risk: the danger that systems become too powerful, too autonomous,...
By Emilio Barkett, Alexander Kimpton, Daniel Graham, Yusuf Kundgol
arXiv:2607. 07766v1 Announce Type: new Abstract: Large language models (LLMs) have become significant providers of mental health support, yet they remain products of an attention economy whose operational and commercial targets favour sustained engagement over the friction that effective psychological support often requires.
By Gwydion Williams, Sara Zannone, Bilal A Mateen