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Matz et al. (2017)
webPNAS(peer-reviewed)·pnas.org/doi/10.1073/pnas.1710966114
Authors
Matz, S. C.·Kosinski, M.·Nave, G.·Stillwell, D. J.
Credibility Rating
5/5
Gold(5)Gold standard. Rigorous peer review, high editorial standards, and strong institutional reputation.
Rating inherited from publication venue: PNAS
A peer-reviewed journal article published in PNAS; without the content preview, likely relevant to AI safety if addressing topics like machine learning, algorithmic decision-making, or related empirical research.
Paper Details
Citations
0
Metadata
journal articleprimary source
Cited by 1 page
| Page | Type | Quality |
|---|---|---|
| AI Preference Manipulation | Risk | 55.0 |
Resource ID:
9a2e4105a28f731f | Stable ID: ZDg1MmVlZj