[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"branding":3,"analytics":7,"article-ai-alignment-has-a-hidden-composition-problem":10,"sections":35},{"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":24,"persona_id":22,"persona_name":22,"section":25,"tags":26,"sources":30,"feedback":34,"feedback_at":22,"cost_usd":34,"total_tokens":34},2500,"ai-alignment-has-a-hidden-composition-problem","AI Alignment Has a Hidden Composition Problem","New research finds that AI \"constitutions\" fail to specify how their own rules combine, causing judges to disagree nearly 1 in 4 times.","The rules used to align AI models are less precise than they look.\n\nResearchers studying Constitutional AI methods found that compressing human preference data into short lists of natural-language principles leaves a critical gap: the principles say nothing about how to resolve conflicts between them. Using three benchmark datasets — PRISM, AlpacaEval, and Chatbot Arena — the team identified three concrete problems. Principle quality is hard to measure; existing proxies like coverage and accuracy don't predict real-world reconstruction. Composition is ambiguous: two different executors applying the same principles agreed only 73% of the time. And constitutions aren't portable — cross-model agreement sat at 73%, while the same model judging its own outputs reached 81%.\n\nThis matters because Constitutional AI and its variants underpin alignment work at several major labs, and the assumption has long been that a well-written list of principles is close enough to a decision rule. It isn't. A 7-point gap between intra-model and cross-model agreement means that what counts as \"aligned\" shifts depending on which model is doing the judging — a problem that scales badly as labs deploy these systems broadly.\n\nThe paper's proposed fix, a refinement step called ICAI+, nudges inter-executor agreement from 73% to 78% and brings transparent executors within a point of LLM judge accuracy. That's progress, but it's incremental — and the authors frame their work explicitly as open problems, not solutions.","[\"ai\",\"alignment\",\"llm\",\"research\"]","2026-06-30T04:00:00.000Z","2026-06-30T06:47:39.855Z","2026-06-30T06:47:46.799Z","published",null,[],"https:\u002F\u002Fcdn.xyz.onl\u002Farticle-images\u002Fai-alignment-has-a-hidden-composition-problem.webp","ai",[25,27,28,29],"alignment","llm","research",[31],{"name":32,"url":33},"arXiv cs.AI","https:\u002F\u002Farxiv.org\u002Fabs\u002F2606.30116",0,{"sections":36},[37,41,46,51,56,61,66,71,76,81,86,90,95,100],{"name":38,"slug":25,"count":39,"latest_published_at":40},"AI",2590,"2026-07-16T04:00:00.000Z",{"name":42,"slug":43,"count":44,"latest_published_at":45},"Security","security",294,"2026-07-15T19:59:48.000Z",{"name":47,"slug":48,"count":49,"latest_published_at":50},"Deals","deals",179,"2026-06-29T20:02:07.000Z",{"name":52,"slug":53,"count":54,"latest_published_at":55},"Policy","policy",158,"2026-07-16T00:02:48.000Z",{"name":57,"slug":58,"count":59,"latest_published_at":60},"Hardware","hardware",122,"2026-07-14T19:46:26.000Z",{"name":62,"slug":63,"count":64,"latest_published_at":65},"Consumer Tech","consumer-tech",93,"2026-07-13T13:20:48.000Z",{"name":67,"slug":68,"count":69,"latest_published_at":70},"Software","software",70,"2026-07-13T19:52:25.000Z",{"name":72,"slug":73,"count":74,"latest_published_at":75},"Science","science",66,"2026-07-10T10:29:37.000Z",{"name":77,"slug":78,"count":79,"latest_published_at":80},"Dev Tools","dev-tools",59,"2026-07-07T04:00:00.000Z",{"name":82,"slug":83,"count":84,"latest_published_at":85},"Gaming","gaming",41,"2026-07-09T04:00:00.000Z",{"name":87,"slug":88,"count":84,"latest_published_at":89},"Startups","startups","2026-06-29T20:55:50.000Z",{"name":91,"slug":92,"count":93,"latest_published_at":94},"General","general",29,"2026-07-10T22:28:58.000Z",{"name":96,"slug":97,"count":98,"latest_published_at":99},"Reviews","reviews",20,"2026-06-24T12:00:01.000Z",{"name":101,"slug":102,"count":103,"latest_published_at":104},"How-To","how-to",6,"2026-06-16T09:00:00.000Z"]