6 papers
Position: Evaluations of AI Moral Reasoning Still Miss Half of the Picture
Aidan Kierans, Ritam Dutt, Kaley Rittichier +2
Recent work on evaluating the moral competence of large language models (LLMs) has focused primarily on what we call the moral value problem, i.e., whether model outputs align with…
Fully Autonomous AI Agents Should Not be Developed
Margaret Mitchell, Avijit Ghosh, Alexandra Sasha Luccioni +1
This paper argues that fully autonomous AI agents should not be developed. In support of this position, we build from prior scientific literature and current product marketing to d…
Stop treating `AGI' as the north-star goal of AI research
Borhane Blili-Hamelin, Christopher Graziul, Leif Hancox-Li +13
The AI research community plays a vital role in shaping the scientific, engineering, and societal goals of AI research. In this position paper, we argue that focusing on the highly…
A Scaling Law for Token Efficiency in LLM Fine-Tuning Under Fixed Compute Budgets
Ryan Lagasse, Aidan Kierans, Avijit Ghosh +1
We introduce a scaling law for fine-tuning large language models (LLMs) under fixed compute budgets that explicitly accounts for data composition. Conventional approaches measure t…
Catastrophic Liability: Managing Systemic Risks in Frontier AI Development
Aidan Kierans, Kaley Rittichier, Utku Sonsayar +1
As artificial intelligence systems grow more capable and autonomous, frontier AI development poses potential systemic risks that could affect society at a massive scale. Current pr…
Quantifying Misalignment Between Agents: Towards a Sociotechnical Understanding of Alignment
Aidan Kierans, Avijit Ghosh, Hananel Hazan +1
Existing work on the alignment problem has focused mainly on (1) qualitative descriptions of the alignment problem; (2) attempting to align AI actions with human interests by focus…