From Individual Gains to Collective Losses? The Socially Corrosive Path of Generative AI

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.

Authors

Publication Details

Journal
PsyArXiv (OSF Preprints)
Published
2026-11-06
DOI
https://doi.org/10.31234/osf.io/a7jms_v1
Primary Topic
Ethics and Social Impacts of AI
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
preprint

From Individual Gains to Collective Losses? The Socially Corrosive Path of Generative AI

Igor Grossmann, Markus Langer
5 links
PsyArXiv (OSF Preprints)
Ethics and Social Impacts of AI
preprint

From Individual Gains to Collective Losses? The Socially Corrosive Path of Generative AI

Igor Grossmann, Markus Langer
preprint en

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.

PsyArXiv (OSF Preprints)
Ethics and Social Impacts of AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon
From Individual Gains to Collective Losses? The Socially Corrosive Path of Generative AI — Igor Grossmann, Markus Langer · PsyArXiv (OSF Preprints) (2026) | TGRS Research Map | TGRS