AI Papers Atlas Wave 0
AIORG-W029 Peer-reviewed research

Evidence of a Social Evaluation Penalty for Using AI

PNAS 2426766122 · social penalty for AI use

peer reviewed multi study article

Source of record — doi.org See it on the corpus view
Recorded claims
2
coded from the inspected source
Evidence classes
1
independent-empirical
Recorded limitations
4
stated, never hidden

From the wave-0 evidence ledger

Recorded claims

Each claim states what the inspected source says, at the recorded location—bounded by its scope and graded by its confidence. Nothing here is a synthesis across works.

Across studies totaling 1,215 participants, disclosing AI use produced a social-evaluation penalty: AI users were judged as less competent, diligent, or self-reliant in the studied evaluation contexts.

confidence: high within experiments; medium external validity independent-empirical

Scope: Experimental interpersonal evaluations; not measured promotion, pay, or firm outcomes.

The penalty varied with evaluators' own AI use, indicating that adoption norms and evaluator incentives can change whether workers feel safe revealing or using AI even when a formal policy encourages it.

confidence: medium-high independent-empirical

Scope: Experimental judgments; organization-policy implication requires local validation.

Boundaries

Limitations & independence

Recorded at coding time, carried with the work forever. A claim without its limits is not evidence.

Recorded limitations

  • 1,215 participants across experimental judgment settings
  • Perceptions may differ from workplace behavior
  • No firm performance or long-run career outcome
  • Context and disclosure norms can moderate effects

Source independence

Independent academic behavioral experiments; not a field measure of continuing employment outcomes.