NLP Venues Should Incentivize Interdisciplinary AI Research
About
How has work studying LLMs changed the identity of NLP research, and how should the community proceed? We investigate by analyzing abstract content and author disciplines for papers from ACL venues and find that the proportion of research focused on studying AI systems has increased significantly, while interdisciplinary research has also increased. We therefore claim that NLP venues today already welcome interdisciplinary AI work and argue that, moving forward, the NLP community should claim interdisciplinary AI research as one of its core strengths, arguing against both blanket rejection and acceptance of all AI research at NLP venues.
Details
- Date:
- Friday, October 2, 2026
- Time:
- 12:00 PM - 1:00 PM
- Location:
- CDS 1646
- Theme:
- AI
Speaker
Micah Benson
Micah studies the societal impacts of large language models (LLMs) as a PhD Student at Boston University's Faculty of Computing & Data Sciences. His current research seeks to understand the psychological harms of conversational AI use. He evaluates how LLMs respond to users who disclose mental health symptoms, with the goal of characterizing patterns in these responses and proposing policy changes that would make the models safer for vulnerable users. Before BU, Micah graduated from WashU with a double major in data science and English.