Related Experiment Video
Updated: Jul 2, 2026
15:01
Peering into the Dynamics of Social Interactions: Measuring Play Fighting in Rats
Published on: January 18, 2013
You can't fight in here! This is BBS!
Richard Futrell1, Kyle Mahowald2
1University of California Irvine, USA rfutrell@uci.edu.
The Behavioral and Brain Sciences
|June 30, 2026
Summary
Modern language models (LMs) can offer valuable insights into the language sciences. Researchers should adopt a broader perspective, moving beyond current limitations to advance both human language understanding and LM development.
Area of Science:
- Linguistics
- Computational Linguistics
- Cognitive Science
- AI Research
Background:
- Discussions between theoretical linguists and computational language scientists explore the utility of modern language models (LMs).
- A diverse group of experts from various scientific disciplines convened to discuss the intersection of LMs and language sciences.
- Key challenges identified include the "String Statistics Strawman" and the "As Good As It Gets Assumption" regarding LM capabilities.
Purpose of the Study:
- To evaluate the potential of current language models to address fundamental questions in the language sciences.
- To identify and address common misconceptions and limitations in the application of LMs to linguistic research.
- To advocate for an expanded research agenda in the AI era for a more robust science of human language and LMs.
Main Methods:
- Qualitative analysis of a discussion involving experts from linguistics, neuroscience, cognitive science, psychology, philosophy, and computer science.
- Identification and critique of prevalent assumptions regarding the linguistic capabilities and research limitations of LMs.
- Formulation of recommendations for future research directions in the language sciences.
Main Results:
- Language models (LMs) are often underestimated due to the "String Statistics Strawman," mistakenly equating their statistical nature with a lack of linguistic competence.
- The "As Good As It Gets Assumption" limits research by assuming current LM capabilities represent the ultimate extent of their scientific utility.
- A need exists for a more comprehensive research framework to leverage LMs for deeper insights into human language.
Conclusions:
- Modern language models hold significant potential for advancing the language sciences beyond their current perceived limitations.
- Addressing misconceptions about LMs is crucial for unlocking their full potential in linguistic research.
- An expansive, interdisciplinary research program is necessary to foster a more robust understanding of both human language and artificial language models.
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