26 citations · 36 across the 8 of their papers we have counts for
11 papers
Reasoning Models Generate Societies of Thought
Junsol Kim, Shiyang Lai, Nino Scherrer +2
Large language models have achieved remarkable capabilities across domains, yet mechanisms underlying sophisticated reasoning remain elusive. Recent reasoning models outperform com…
Generative AI collective behavior needs an interactionist paradigm
Laura Ferrarotti, Gian Maria Campedelli, Roberto Dessì +7
In this article, we argue that understanding the collective behavior of agents based on large language models (LLMs) is an essential area of inquiry, with important implications in…
We Need a New Ethics for a World of AI Agents
Iason Gabriel, Geoff Keeling, Arianna Manzini +1
The deployment of capable AI agents raises fresh questions about safety, human-machine relationships and social coordination. We argue for greater engagement by scientists, scholar…
Biased AI improves human decision-making but reduces trust
Shiyang Lai, Junsol Kim, Nadav Kunievsky +2
Current AI systems minimize risk by enforcing ideological neutrality, yet this may introduce automation bias by suppressing cognitive engagement in human decision-making. We conduc…
Epitome: Pioneering an Experimental Platform for AI-Social Science Integration
Jingjing Qu, Kejia Hu, Jun Zhu +9
Large Language Models (LLMs) enable unprecedented social science experimentation by creating controlled hybrid human-AI environments. We introduce Epitome (www.epitome-ai.com), an…
Big Data and the Computational Social Science of Entrepreneurship and Innovation
Ningzi Li, Shiyang Lai, James Evans
As large-scale social data explode and machine-learning methods evolve, scholars of entrepreneurship and innovation face new research opportunities but also unique challenges. This…