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Updated: Sep 23, 2025

The HoneyComb Paradigm for Research on Collective Human Behavior
Published on: January 19, 2019
Predictive models for human-AI nexus in group decision making
Omid Askarisichani1, Francesco Bullo2,3, Noah E Friedkin3,4
1Department of Computer Science, University of California, Santa Barbara, California, USA.
Abstract:
Machine learning (ML) and artificial intelligence (AI) have had a profound impact on our lives. Domains like health and learning are naturally helped by human-AI interactions and decision making. In these areas, as ML algorithms prove their value in making important decisions, humans add their distinctive expertise and judgment on social and interpersonal issues that need to be considered in tandem with algorithmic inputs of information. Some questions naturally arise. What rules and regulations should be invoked on the employment of AI, and what protocols should be in place to evaluate available AI resources? What are the forms of effective communication and coordination with AI that best promote effective human-AI teamwork? In this review, we highlight factors that we believe are especially important in assembling and managing human-AI decision making in a group setting.
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