Anita Williams Woolley

About

Anita Williams Woolley is a Professor of Organizational Behavior and Theory at the Tepper School of Business. Her work is centered on research related to organizational behavior, leadership, and teamwork. She is involved in the academic community at Carnegie Mellon University, contributing to the faculty profile and engaging in research activities that explore how artificial intelligence and machine learning intersect with business, management science, and organizational behavior. Woolley's expertise and research focus on understanding the dynamics of organizations and the impact of technological advancements on business practices.

Research topics

• Computer Science
• Artificial Intelligence
• Psychology
• Knowledge management
• Social psychology
• Computer Security
• Political Science
• Sociology
• Microeconomics
• Management

Selected publications

• Human Trust in Artificial Intelligence: Review of Empirical Research

  Academy of Management Annals · 2020 · 2102 citations

  Senior authorCorresponding

  Artificial intelligence (AI) characterizes a new generation of technologies capable of interacting with the environment and aiming to simulate human intelligence. The success of integrating AI into organizations critically depends on workers’ trust in AI technology. This review explains how AI differs from other technologies and presents the existing empirical research on the determinants of human “trust” in AI, conducted in multiple disciplines over the last 20 years. Based on the reviewed lite…

  DOI

• Quantifying collective intelligence in human groups

  Proceedings of the National Academy of Sciences · 2021 · 163 citations

  Senior authorCorresponding

  Collective intelligence (CI) is critical to solving many scientific, business, and other problems, but groups often fail to achieve it. Here, we analyze data on group performance from 22 studies, including 5,279 individuals in 1,356 groups. Our results support the conclusion that a robust CI factor characterizes a group's ability to work together across a diverse set of tasks. We further show that CI is predicted by the proportion of women in the group, mediated by average social perceptiveness…

  PublisherOA PDFDOI

• How large language models can reshape collective intelligence

  Nature Human Behaviour · 2024-09-20 · 84 citations

  review
  PublisherDOI

• Speaking out of turn: How video conferencing reduces vocal synchrony and collective intelligence

  PLoS ONE · 2021 · 79 citations

  Collective intelligence (CI) is the ability of a group to solve a wide range of problems. Synchrony in nonverbal cues is critically important to the development of CI; however, extant findings are mostly based on studies conducted face-to-face. Given how much collaboration takes place via the internet, does nonverbal synchrony still matter and can it be achieved when collaborators are physically separated? Here, we hypothesize and test the effect of nonverbal synchrony on CI that develops throug…

  PublisherDOI

• Collective Attention and Collective Intelligence: The Role of Hierarchy and Team Gender Composition

  Organization Science · 2022 · 30 citations

  1st authorCorresponding

  Collective intelligence (CI) captures a team’s ability to work together across a wide range of tasks and can vary significantly between teams. Extant work demonstrates that the level of collective attention a team develops has an important influence on its level of CI. An important question, then, is what enhances collective attention? Prior work demonstrates an association with team composition; here, we additionally examine the influence of team hierarchy and its interaction with team gender c…

  PublisherOA PDFDOI

Recent grants

• Collaborative Research: Measuring Collective Intelligence

  NSF · $188k · 2010–2012

• VOSS: Collaborative Research: Is Larger Smarter? Investigating the Effect of Group Size on Collective Intelligence

  NSF · $168k · 2013–2017

Frequent coauthors

• Christopher F. Chabris

  111 shared

• J. Richard Hackman

  Harvard Global Health Institute

  104 shared

• Stephen M. Kosslyn

  102 shared

• Sean L. Bennett

  Carnegie Mellon University

  101 shared

• Margaret E. Gerbasi

  Sage Therapeutics (United States)

  101 shared

• Jonathon P. Schuldt

  Cornell University

  101 shared

• Thomas E. Jerde

  Autism & Developmental Medicine Institute

  101 shared

• Jonathan Wai

  Arkansas Department of Education

  100 shared

Education

• Ph.D., Management Science

  Carnegie Mellon University

  2003

• M.S., Management Science

  Carnegie Mellon University

  1999

• B.S., Operations Research and Industrial Engineering

  University of North Carolina at Chapel Hill

  1995

Similar researchers at Carnegie Mellon University

• Denise Rousseauh-76
• Robert Millerh-67
• David Krackhardth-54