The Influence of AI Moderation on Decision-Making Teams' Information Search and Knowledge Exchange
Year: 2026
Type: preprint
Abstract: A previous study provided evidence that the decision-makers we examined were receptive to advice from AI moderators. The participants modified their information strategy, increasing or reducing the diversity of tests selected. The direction of the changes were sensitive to the type of advice received. However, the participants’ accuracy was unaffected by any changes in their information search. We want to further investigate how the participants use the experimental information, the accuracy of their belief updating, and how these factors are influencing accuracy. This study aims to address the following research questions: RQ1: How does moderating AI Advice influence the information search strategies of decision-making teams? RQ2: How do different information search strategies influence the accuracy of decision-making teams in a hypothesis-testing task? RQ3: How does a modified information search strategy following AI Advice affect the exchange of information in decision-making teams? Note regarding the timing of preregistration: The final draft of this preregistration was completed on March 7th 2025, before data collection began. It was not submitted to OSF at that time due to an oversight by the Lead Researcher (Eoin Cremen). The document has remained unchanged since this time. Immediately upon identifying this error we submitted the draft, (March 5th 2026). The preregistration remains a transparent documentation of the study plan that was specified prior to data collection.
Language: English
Subfield: General Decision Sciences
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7134190488