activity
20242026
most citedFully Autonomous AI Agents Should Not be Developed

9 citations · 15 across the 6 of their papers we have counts for

collaborators

7 papers

cs.AI2026

AI Agents Push Humans Out of the Loop

Margaret Mitchell, Avijit Ghosh, Samir Passi

AI agents pose significant risks as they are granted increasing autonomy. A commonly proposed solution is human oversight and keeping a ''human in the loop'', but this is not a sim…

cs.AI2026

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…

cs.CL2025

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…

cs.CY2025★ 2 cited

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…

cs.CY2025★ 1 cited

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…

cs.AI2025★ 9 cited

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…

cs.MA2024★ 3 cited

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…