[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"branding":3,"analytics":7,"article-ai-models-cant-flip-a-fair-coin-study-finds":10,"sections":34},{"siteName":4,"siteTagline":5,"publisherName":4,"contactEmail":6},"The Revision","Tech news, decoded.","editor@therevision.news",{"gaMeasurementId":8,"adsenseClientId":9},"G-ZW2MV82GYR","ca-pub-8533917693782264",{"article":11},{"id":12,"slug":13,"title":14,"dek":15,"body_md":16,"tags_json":17,"published_at":18,"created_at":19,"updated_at":20,"status":21,"review_note":22,"review_notes":23,"image_url":22,"persona_id":22,"persona_name":22,"section":24,"tags":25,"sources":29,"feedback":33,"feedback_at":22,"cost_usd":33,"total_tokens":33},10071,"ai-models-cant-flip-a-fair-coin-study-finds","AI Models Can't Flip a Fair Coin, Study Finds","A new study finds large language models mimic classic human biases when simulating coin flips, like over-alternating, but often exaggerate them further.","Ask an AI to flip a coin, and it cheats in oddly human ways.\n\nResearchers tested how large language models generate binary random sequences, using the classic simulated coin-flip paradigm from behavioral science. They compared single flips, 20-flip sequences, n-gram statistics, run lengths, alternation rates, and next-flip predictability against true random (Bernoulli) baselines and existing human data from prior studies. The models reproduced well-documented human biases: they alternate between heads and tails too often, avoid long streaks, and show a slight first-flip preference. Turning up the \"temperature\" setting, which adds more randomness to outputs, softened some rigid patterns but didn't erase the underlying structure, and follow-up tests, including prompt changes, continuation tests, corpus searches, and internal model probes, ruled out simple memorization or tokenization quirks as the cause.\n\nThat matters because plenty of real-world uses, like sampling data, simulating survey respondents, or generating test cases, assume an LLM can stand in for a coin flip or a human guess. It can't, reliably. That's a quiet but consequential caveat for anyone leaning on these models for anything resembling unbiased chance.\n\nHumans have been bad at faking randomness since long before chatbots existed; the machines, it turns out, learned that particular flaw a little too well.","[\"ai\",\"llm-research\",\"randomness\",\"cognitive-bias\"]","2026-10-05T04:00:00.000Z","2026-10-05T21:33:55.655Z","2026-10-05T21:34:00.292Z","published",null,[],"ai",[24,26,27,28],"llm-research","randomness","cognitive-bias",[30],{"name":31,"url":32},"arXiv cs.AI","https:\u002F\u002Farxiv.org\u002Fabs\u002F2406.00092",0,{"sections":35},[36,39,43,48,53,58,62,67,71,76,81,86,91,96],{"name":37,"slug":24,"count":38,"latest_published_at":18},"AI",6314,{"name":40,"slug":41,"count":42,"latest_published_at":18},"Security","security",871,{"name":44,"slug":45,"count":46,"latest_published_at":47},"Policy","policy",444,"2026-10-03T15:02:01.000Z",{"name":49,"slug":50,"count":51,"latest_published_at":52},"Deals","deals",325,"2026-10-04T13:00:00.000Z",{"name":54,"slug":55,"count":56,"latest_published_at":57},"Hardware","hardware",204,"2026-10-03T14:50:50.000Z",{"name":59,"slug":60,"count":61,"latest_published_at":18},"Science","science",179,{"name":63,"slug":64,"count":65,"latest_published_at":66},"Consumer Tech","consumer-tech",158,"2026-10-03T03:21:12.000Z",{"name":68,"slug":69,"count":70,"latest_published_at":18},"Dev Tools","dev-tools",98,{"name":72,"slug":73,"count":74,"latest_published_at":75},"Software","software",97,"2026-10-04T10:00:00.000Z",{"name":77,"slug":78,"count":79,"latest_published_at":80},"Startups","startups",92,"2026-10-04T14:36:25.000Z",{"name":82,"slug":83,"count":84,"latest_published_at":85},"Gaming","gaming",53,"2026-10-02T02:50:39.000Z",{"name":87,"slug":88,"count":89,"latest_published_at":90},"General","general",51,"2026-10-05T02:35:01.000Z",{"name":92,"slug":93,"count":94,"latest_published_at":95},"Reviews","reviews",32,"2026-10-02T18:00:00.000Z",{"name":97,"slug":98,"count":99,"latest_published_at":100},"How-To","how-to",7,"2026-10-01T09:00:00.000Z"]