44 citations · 51 across the 4 of their papers we have counts for
5 papers
Artificial intelligences and human scientists exhibit complementary strengths in theory building
Ke Li, Spyros I. Zoumpoulis, Phanish Puranam +80
We investigate the effectiveness of artificial intelligences (AI)-specifically large language models (LLMs)-relative to human scientists at high-level cognitive tasks in social sci…
Sycophantic AI makes human interaction feel more effortful and less satisfying over time
Lujain Ibrahim, Franziska Sofia Hafner, Myra Cheng +5
Millions of people now turn to artificial intelligence (AI) systems for personal advice, guidance, and support. Such systems can be sycophantic, frequently affirming users' views a…
Accumulating Context Changes the Beliefs of Language Models
Jiayi Geng, Howard Chen, Ryan Liu +4
Language model (LM) assistants are increasingly used in applications such as brainstorming and research. Improvements in memory and context size have allowed these models to become…
Labeling Messages as AI-Generated Does Not Reduce Their Persuasive Effects
Isabel O. Gallegos, Chen Shani, Weiyan Shi +4
As generative artificial intelligence (AI) enables the creation and dissemination of information at massive scale and speed, it is increasingly important to understand how people p…
LLM Agents Grounded in Self-Reports Enable General-Purpose Simulation of Individuals
Joon Sung Park, Carolyn Q. Zou, Jonne Kamphorst +8
Machine learning can predict human behavior well when substantial structured data are available for well-defined outcomes. Such models are typically outcome-specific, however, requ…