{"id":1991,"date":"2023-06-22T21:18:13","date_gmt":"2023-06-22T21:18:13","guid":{"rendered":"https:\/\/dailyai.com\/?p=1991"},"modified":"2023-06-22T21:38:35","modified_gmt":"2023-06-22T21:38:35","slug":"stanford-researchers-test-ai-model-compliance-against-the-eu-ai-act","status":"publish","type":"post","link":"https:\/\/dailyai.com\/sv\/2023\/06\/stanford-researchers-test-ai-model-compliance-against-the-eu-ai-act\/","title":{"rendered":"Stanford-studie testar grundl\u00e4ggande AI-modellers \u00f6verensst\u00e4mmelse med EU:s AI-lag"},"content":{"rendered":"

AI-forskare vid Stanford utv\u00e4rderade 10 ledande AI-modellers efterlevnad av EU:s f\u00f6reslagna AI-lag och fann stora variationer, med generellt sett svaga resultat \u00f6ver hela linjen.\u00a0<\/b><\/p>\n

Studien<\/a> har kritiskt granskat 10 AI-modeller mot 12 kriterier som anges i EU:s lagf\u00f6rslag och uppt\u00e4ckt stora variationer i efterlevnaden, d\u00e4r ingen modell uppfyller alla kriterier.\u00a0<\/span><\/p>\n

Studien belyser klyftan mellan AI-lagens f\u00f6rv\u00e4ntningar och nuvarande styrningsinsatser bland ledande AI-utvecklare. <\/span><\/p>\n

F\u00f6r att f\u00f6lja lagen m\u00e5ste utvecklarna avsev\u00e4rt f\u00f6rb\u00e4ttra sin transparens och sina strategier f\u00f6r riskreducering, som i vissa fall saknas n\u00e4stan helt.\u00a0<\/span><\/p>\n

Hur studien genomf\u00f6rdes<\/span><\/h2>\n

F\u00f6rfattarna genomf\u00f6rde en detaljerad studie av AI-lagen och tog fram 22 krav. <\/span><\/p>\n

Av dessa valde de ut 12 som p\u00e5 ett meningsfullt s\u00e4tt kunde utv\u00e4rderas med hj\u00e4lp av offentlig information. D\u00e4refter skapade de ett 5-gradigt kriterium f\u00f6r vart och ett av dessa 12 krav.\u00a0<\/span><\/p>\n

Den \u00f6ppna AI-modellen BLOOM, som tagits fram av Hugging Face, var den modell som fick h\u00f6gst po\u00e4ng med totalt 36 av 48 m\u00f6jliga po\u00e4ng.\u00a0<\/span><\/p>\n

Omv\u00e4nt presterade Google-st\u00f6dda Anthropic och det tyska AI-f\u00f6retaget Aleph Alpha betydligt s\u00e4mre, med 7 respektive 5 po\u00e4ng.\u00a0<\/span>ChatGPT f\u00f6ll i mitten av paketet med 25\/48.<\/span><\/p>\n

\"Grundl\u00e4ggande
Stanfords po\u00e4ng f\u00f6r 10 grundl\u00e4ggande modeller. Kredit: Stanford<\/a>.<\/figcaption><\/figure>\n

De fyra fr\u00e4msta omr\u00e5dena f\u00f6r bristande efterlevnad \u00e4r upphovsr\u00e4ttsskyddade data, energi, riskreducering och utv\u00e4rdering\/testning.<\/span><\/p>\n

En av f\u00f6rfattarna, Kevin Klyman, forskare vid Stanfords Center for Research on Foundation Models, noterade att de flesta utvecklare inte avsl\u00f6jar sina riskreduceringsstrategier, vilket kan vara en dealbreaker. Klyman sa: \"Leverant\u00f6rer avsl\u00f6jar ofta inte effektiviteten i sina riskreducerande \u00e5tg\u00e4rder, vilket inneb\u00e4r att vi inte kan s\u00e4ga hur riskfyllda vissa grundmodeller \u00e4r.\"<\/span><\/p>\n

Dessutom finns det stora variationer i de tr\u00e4ningsdata som anv\u00e4nds f\u00f6r att tr\u00e4na modeller. EU kommer att kr\u00e4va att AI-utvecklare \u00e4r mer transparenta med sina datak\u00e4llor, vilket 4\/10 av utvecklarna misslyckas med att g\u00f6ra. ChatGPT fick bara 1 po\u00e4ng p\u00e5 det omr\u00e5det.\u00a0<\/span><\/p>\n

\u00d6ppen k\u00e4llkod kontra propriet\u00e4ra modeller<\/span><\/h2>\n

Rapporten visade ocks\u00e5 att det fanns en tydlig skillnad i efterlevnad beroende p\u00e5 om en modell var \u00f6ppen k\u00e4llkod eller propriet\u00e4r.\u00a0<\/span><\/p>\n

Modeller med \u00f6ppen k\u00e4llkod fick h\u00f6ga po\u00e4ng n\u00e4r det g\u00e4ller redovisning av resurser och datakrav, men deras risker \u00e4r till stor del odokumenterade.<\/span><\/p>\n

Propriet\u00e4ra modeller \u00e4r motsatsen - de \u00e4r h\u00e5rt testade och v\u00e4ldokumenterade med robusta strategier f\u00f6r riskreducering, men de \u00e4r inte transparenta n\u00e4r det g\u00e4ller data och teknikrelaterade m\u00e4tv\u00e4rden.\u00a0<\/span><\/p>\n

Eller, f\u00f6r att s\u00e4tta fingret p\u00e5 det, utvecklare av \u00f6ppen k\u00e4llkod har inte s\u00e5 m\u00e5nga konkurrenshemligheter att skydda, men deras produkter \u00e4r i sig mer riskfyllda eftersom de kan anv\u00e4ndas och modifieras av n\u00e4stan vem som helst.\u00a0<\/span><\/p>\n

Omv\u00e4nt kommer privata utvecklare sannolikt att h\u00e5lla delar av sina modeller under l\u00e5s och bom, men de kan visa p\u00e5 s\u00e4kerhet och riskreducering. Till och med Microsoft, OpenAI:s huvudinvesterare, \u00e4r inte helt f\u00f6rst\u00e5 hur OpenAI:s modeller fungerar<\/a>.\u00a0<\/span><\/p>\n

Vad rekommenderar studien?\u00a0<\/span><\/h2>\n

F\u00f6rfattarna till studien medger att gapet mellan EU:s f\u00f6rv\u00e4ntningar och verkligheten \u00e4r alarmerande och l\u00e4gger fram flera rekommendationer till beslutsfattare och modellutvecklare.<\/p>\n

I studien rekommenderas EU:s beslutsfattare:<\/span><\/p>\n

    \n
  • F\u00f6rb\u00e4ttra och specificera parametrarna f\u00f6r EU:s AI-lag<\/b>: Forskarna h\u00e4vdar att AI-lagens tekniska spr\u00e5k och parametrar \u00e4r underspecificerade.\u00a0<\/span><\/li>\n
  • Fr\u00e4mja \u00f6ppenhet och ansvarighet<\/b>: Forskare h\u00e4vdar att de str\u00e4ngaste reglerna b\u00f6r vara extremt inriktade p\u00e5 de allra st\u00f6rsta och mest dominerande utvecklarna, vilket b\u00f6r leda till effektivare till\u00e4mpning.\u00a0<\/span><\/li>\n
  • Tillhandah\u00e5lla tillr\u00e4ckliga resurser f\u00f6r verkst\u00e4llighet<\/b>: F\u00f6r att EU:s AI-lag ska kunna till\u00e4mpas p\u00e5 ett effektivt s\u00e4tt b\u00f6r tekniska resurser och talang g\u00f6ras tillg\u00e4ngliga f\u00f6r tillsynsmyndigheterna.\u00a0<\/span><\/li>\n<\/ul>\n

    Studien rekommenderar globala beslutsfattare:<\/span><\/p>\n

      \n
    • Prioritera \u00f6ppenhet<\/b>: Forskarna betonar att transparens \u00e4r avg\u00f6rande och b\u00f6r vara huvudfokus f\u00f6r politiska insatser. De menar att l\u00e4rdomarna fr\u00e5n regleringen av sociala medier visar p\u00e5 de skadliga konsekvenserna av bristande transparens, n\u00e5got som inte b\u00f6r upprepas i samband med AI.\u00a0<\/span><\/li>\n
    • Klarg\u00f6ra fr\u00e5gor om upphovsr\u00e4tt<\/b>: Gr\u00e4nserna f\u00f6r upphovsr\u00e4tten f\u00f6r AI-tr\u00e4ningsdata och AI-resultat \u00e4r omdiskuterade. Med tanke p\u00e5 den l\u00e5ga efterlevnad som observerats n\u00e4r det g\u00e4ller att avsl\u00f6ja upphovsr\u00e4ttsskyddade tr\u00e4ningsdata, h\u00e4vdar forskarna att juridiska riktlinjer m\u00e5ste ange hur upphovsr\u00e4tten interagerar med tr\u00e4ningsprocedurer och resultatet av generativa modeller. Detta inkluderar att definiera de villkor enligt vilka upphovsr\u00e4tt eller licenser m\u00e5ste respekteras under utbildning och att fastst\u00e4lla hur maskingenererat inneh\u00e5ll kan g\u00f6ra intr\u00e5ng i upphovsr\u00e4tten.<\/span><\/li>\n<\/ul>\n

      Studien ger rekommendationer till utvecklare av grundl\u00e4ggningsmodeller:<\/span><\/p>\n

        \n
      • Str\u00e4va efter st\u00e4ndiga f\u00f6rb\u00e4ttringar<\/b>: Leverant\u00f6rer b\u00f6r konsekvent str\u00e4va efter att f\u00f6rb\u00e4ttra sin efterlevnad. St\u00f6rre leverant\u00f6rer, som OpenAI, b\u00f6r f\u00f6reg\u00e5 med gott exempel och sprida resurser till nedstr\u00f6mskunder som f\u00e5r tillg\u00e5ng till deras modeller via API.\u00a0<\/span><\/li>\n
      • F\u00f6respr\u00e5ka branschstandarder<\/b>: Modellleverant\u00f6rer b\u00f6r bidra till att etablera branschstandarder, vilket kan leda till ett mer transparent och ansvarsfullt AI-ekosystem.<\/span><\/li>\n<\/ul>\n

        \u00c4ven om det finns vissa positiva saker att h\u00e4mta fr\u00e5n de risk- och \u00f6vervakningsstandarder som fastst\u00e4llts av ledande utvecklare som OpenAI, \u00e4r bristerna inom omr\u00e5den som upphovsr\u00e4tt l\u00e5ngt ifr\u00e5n idealiska.<\/p>\n

        N\u00e4r det g\u00e4ller att till\u00e4mpa reglering p\u00e5 AI som en allomfattande kategori -<\/span> Det kan visa sig vara mycket knepigt. - <\/span>eftersom kommersiella modeller och modeller med \u00f6ppen k\u00e4llkod \u00e4r strukturellt olika och sv\u00e5ra att klumpa ihop.<\/p>","protected":false},"excerpt":{"rendered":"

        AI-forskare vid Stanford utv\u00e4rderade 10 ledande AI-modellers efterlevnad av EU:s f\u00f6reslagna AI Act och fann stora variationer, med generellt svaga resultat \u00f6ver hela linjen. I studien granskades 10 AI-modeller kritiskt mot 12 kriterier som anges i EU:s lagf\u00f6rslag och man fann stora variationer i efterlevnaden, d\u00e4r ingen modell uppfyllde alla kriterier. Studien belyser klyftan mellan AI-lagens f\u00f6rv\u00e4ntningar och de nuvarande styrningsinsatserna bland ledande AI-utvecklare. F\u00f6r att f\u00f6lja lagen m\u00e5ste utvecklarna avsev\u00e4rt f\u00f6rb\u00e4ttra sina strategier f\u00f6r transparens och riskreducering, vilket i vissa fall saknas n\u00e4stan helt. Hur<\/p>","protected":false},"author":2,"featured_media":1993,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[85],"tags":[129,145,120],"class_list":["post-1991","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-policy","tag-ai-regulation","tag-ai-risk","tag-eu-ai-act"],"yoast_head":"\nStanford study tests foundational AI model compliance against the EU AI Act | DailyAI<\/title>\n<meta name=\"description\" content=\"AI researchers at Stanford evaluated the compliance of 10 leading AI models against the proposed EU AI Act and found wide variation.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dailyai.com\/sv\/2023\/06\/stanford-researchers-test-ai-model-compliance-against-the-eu-ai-act\/\" \/>\n<meta property=\"og:locale\" content=\"sv_SE\" 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