18 citations · 21 across the 9 of their papers we have counts for
5 papers · 1 filter
Measuring and mitigating overreliance to build human-compatible AI
Lujain Ibrahim, Katherine M. Collins, Sunnie S. Y. Kim +14
Large language models (LLMs) distinguish themselves from previous technologies by functioning as collaborative ``thought partners,'' capable of engaging more fluidly in natural lan…
On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective
Yue Huang, Chujie Gao, Siyuan Wu +63
Generative Foundation Models (GenFMs) have emerged as transformative tools. However, their widespread adoption raises critical concerns regarding trustworthiness across dimensions.…
Prioritization First, Principles Second: An Adaptive Interpretation of Helpful, Honest, and Harmless Principles
Yue Huang, Chujie Gao, Yujun Zhou +5
The Helpful, Honest, and Harmless (HHH) principle is a foundational framework for aligning AI systems with human values. However, existing interpretations of the HHH principle ofte…
Human vs. Machine: Behavioral Differences Between Expert Humans and Language Models in Wargame Simulations
Max Lamparth, Anthony Corso, Jacob Ganz +3
To some, the advent of artificial intelligence (AI) promises better decision-making and increased military effectiveness while reducing the influence of human error and emotions. H…
Risks from Language Models for Automated Mental Healthcare: Ethics and Structure for Implementation
Declan Grabb, Max Lamparth, Nina Vasan
Amidst the growing interest in developing task-autonomous AI for automated mental health care, this paper addresses the ethical and practical challenges associated with the issue a…