Why “human‐ <scp>AI</scp> collaboration” obscures what actually happens in information seeking

Abstract The rhetoric of “human‐AI collaboration” frames contemporary discussions of interacting with artificial intelligence systems. Drawing from 15 years of research in collaborative information seeking, we argue that this metaphor fundamentally misrepresents these interactions and obscures critical issues of agency, accountability, and labor. Real collaboration—whether mediated by algorithms or not—requires mutual understanding, shared goals, reciprocal adaptation, and common ground building. Current AI systems meet none of these criteria. Here we examine what genuine collaboration entails, why the AI industry's appropriation of this language matters, and what we lose when we mistake sophisticated autocomplete for partnership.

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Publication Details

Journal
Journal of the Association for Information Science and Technology
Published
2026-02-26
DOI
https://doi.org/10.1002/asi.70059
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
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article

Why “human‐ AI collaboration” obscures what actually happens in information seeking

Lynda Tamine, Chirag Shah
Journal of the Association for Information Science and Technology
Ethics and Social Impacts of AI
article

Why “human‐ AI collaboration” obscures what actually happens in information seeking

Lynda Tamine, Chirag Shah
article en

Abstract

Abstract The rhetoric of “human‐AI collaboration” frames contemporary discussions of interacting with artificial intelligence systems. Drawing from 15 years of research in collaborative information seeking, we argue that this metaphor fundamentally misrepresents these interactions and obscures critical issues of agency, accountability, and labor. Real collaboration—whether mediated by algorithms or not—requires mutual understanding, shared goals, reciprocal adaptation, and common ground building. Current AI systems meet none of these criteria. Here we examine what genuine collaboration entails, why the AI industry's appropriation of this language matters, and what we lose when we mistake sophisticated autocomplete for partnership.

Journal of the Association for Information Science and Technology
Université Toulouse III - Paul Sabatier (FR), University of Washington (US), Université Toulouse-I-Capitole (FR), Institut de Recherche en Informatique de Toulouse (FR), Université Toulouse - Jean Jaurès (FR), Institut Polytechnique de Bordeaux (FR)
Partnerships for the goals
Openalex Percentile: Top 35%
Ethics and Social Impacts of AI
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