From Queries to Conversations: Examining Human–GenAI Information-Seeking through Belkin's Cognitive Communication Model

Publication Date

10-1-2025

Document Type

Article

Publication Title

Proceedings of the Association for Information Science and Technology

Volume

62

Issue

1

DOI

10.1002/pra2.1240

First Page

105

Last Page

116

Abstract

Generative artificial intelligence (GenAI) is rapidly transforming how human beings perform cognitive and creative tasks, including the strategies they employ in seeking information. Freed from the constraints that have shaped query formulation in traditional query-response information retrieval (IR) systems, GenAI users employ novel strategies – framing commands in natural language, embedding personal details, and experimenting with conversational approaches. Drawing on information-seeking research in library and information science (LIS), the present study examines the structure and defining features of these human–GenAI interactions, revealing notable parallels with Belkin's (1980) Cognitive Communication System for Information Retrieval. Employing qualitative methods, we uncover a pattern of evolving user information needs, user doubt, and iterative search processes in human-GenAI interaction consistent with anomalous states of knowledge (ASKs) and the information search strategies for successfully resolving these. Through our observation of these human-GenAI interaction sessions, we provide insights into the nature of information and contemporary information retrieval in an era of expanding global GenAI adoption.

Keywords

cognitive communication, Generative AI, human–AI interaction, information seeking, library and information science (LIS)

Department

Information

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