From Individual Gains to Collective Losses? The Socially Corrosive Path of Generative AI
Year: 2026
Type: preprint
Abstract: AI tools including generative AI (genAI) and agentic AI promise individual productivity gains, and users experience them as a resource that makes them more capable. However, research documents a robust social evaluation penalty for individual genAI use: people who use genAI, or are suspected of doing so, are judged as less competent, less diligent, and less caring. We argue that these judgments, followed through to their behavioral consequences, outline a socially corrosive path of collective genAI use. Along this path, when people substitute human contact with genAI and devalue what colleagues produce, relational interdependence, metaknowledge, and resulting opportunities for scalable collective intelligence decline, whereas trust erodes through a cycle of concealment, suspicion, policing, and blame. Current technology design and productivity narratives amplify these dynamics. We caution against waiting for genAI use to normalize and propose countermeasures: designing genAI for collective functioning, resisting the productivity trap, and making the social norms of genAI use explicit.
Source: PsyArXiv (OSF Preprints)
Authors: Markus Langer, Igor Grossmann
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7225427859