{"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\/pt\/2023\/06\/stanford-researchers-test-ai-model-compliance-against-the-eu-ai-act\/","title":{"rendered":"Estudo de Stanford testa a conformidade de modelos fundamentais de IA com o AI Act da UE"},"content":{"rendered":"

Os investigadores de IA de Stanford avaliaram a conformidade de 10 dos principais modelos de IA com a proposta de Lei da IA da UE e encontraram grandes varia\u00e7\u00f5es, com resultados geralmente med\u00edocres em todos os sectores.\u00a0<\/b><\/p>\n

O estudo<\/a> examinou criticamente 10 modelos de IA em rela\u00e7\u00e3o a 12 crit\u00e9rios estabelecidos no projeto de legisla\u00e7\u00e3o da UE e revelou uma grande varia\u00e7\u00e3o na conformidade, n\u00e3o havendo nenhum modelo que preencha todas as condi\u00e7\u00f5es.\u00a0<\/span><\/p>\n

O estudo destaca o fosso entre as expectativas da Lei da IA e os actuais esfor\u00e7os de governa\u00e7\u00e3o entre os principais criadores de IA. <\/span><\/p>\n

Para cumprir a lei, os promotores devem melhorar consideravelmente as suas estrat\u00e9gias de transpar\u00eancia e de redu\u00e7\u00e3o dos riscos, que, em alguns casos, s\u00e3o quase inexistentes.\u00a0<\/span><\/p>\n

Como foi realizado o estudo<\/span><\/h2>\n

Os autores efectuaram um estudo pormenorizado da Lei da IA, tendo extra\u00eddo 22 requisitos. <\/span><\/p>\n

Destes, seleccionaram 12 que poderiam ser avaliados de forma significativa utilizando informa\u00e7\u00e3o p\u00fablica. De seguida, criaram uma grelha de avalia\u00e7\u00e3o de 5 pontos para cada um destes 12 requisitos.\u00a0<\/span><\/p>\n

O modelo de IA de c\u00f3digo aberto BLOOM, produzido pela Hugging Face, emergiu como o modelo com a pontua\u00e7\u00e3o mais elevada, com um total de 36 de um potencial de 48 pontos.\u00a0<\/span><\/p>\n

Por outro lado, a Anthropic, apoiada pela Google, e a empresa alem\u00e3 de IA Aleph Alpha tiveram um desempenho significativamente inferior, com 7 e 5 pontos, respetivamente.\u00a0<\/span>ChatGPT ficou no meio do pelot\u00e3o com 25\/48.<\/span><\/p>\n

\"Modelo
Pontua\u00e7\u00f5es de Stanford para 10 modelos fundamentais. Cr\u00e9dito: Stanford<\/a>.<\/figcaption><\/figure>\n

Os quatro principais dom\u00ednios de n\u00e3o conformidade s\u00e3o os dados protegidos por direitos de autor, a energia, a atenua\u00e7\u00e3o dos riscos e a avalia\u00e7\u00e3o\/ensaio.<\/span><\/p>\n

Um dos autores, Kevin Klyman, investigador do Centro de Investiga\u00e7\u00e3o de Modelos de Funda\u00e7\u00f5es de Stanford, observou que a maioria dos criadores n\u00e3o divulga as suas estrat\u00e9gias de redu\u00e7\u00e3o do risco, o que pode ser um fator de rutura do neg\u00f3cio. Klyman disse: \"Os fornecedores muitas vezes n\u00e3o divulgam a efic\u00e1cia de suas medidas de mitiga\u00e7\u00e3o de risco, o que significa que n\u00e3o podemos dizer o qu\u00e3o arriscados s\u00e3o alguns modelos de funda\u00e7\u00e3o\".<\/span><\/p>\n

Al\u00e9m disso, h\u00e1 uma grande varia\u00e7\u00e3o nos dados de treino utilizados para treinar modelos. A UE exigir\u00e1 que os criadores de IA sejam mais transparentes com as suas fontes de dados, o que 4\/10 dos criadores n\u00e3o conseguem fazer. O ChatGPT obteve apenas 1 ponto neste dom\u00ednio.\u00a0<\/span><\/p>\n

Modelos de fonte aberta versus modelos propriet\u00e1rios<\/span><\/h2>\n

O relat\u00f3rio tamb\u00e9m descobriu uma clara dicotomia na conformidade, dependendo do facto de um modelo ser de fonte aberta ou propriet\u00e1ria.\u00a0<\/span><\/p>\n

Os modelos de fonte aberta obtiveram bons resultados no que respeita \u00e0 divulga\u00e7\u00e3o de recursos e aos requisitos de dados, mas os seus riscos n\u00e3o est\u00e3o, em grande medida, documentados.<\/span><\/p>\n

Os modelos propriet\u00e1rios s\u00e3o o oposto - s\u00e3o muito testados e altamente documentados com estrat\u00e9gias robustas de mitiga\u00e7\u00e3o de riscos, mas n\u00e3o s\u00e3o transparentes no que respeita aos dados e \u00e0s m\u00e9tricas relacionadas com a tecnologia.\u00a0<\/span><\/p>\n

Ou, para ser mais preciso, os programadores de c\u00f3digo aberto n\u00e3o t\u00eam tantos segredos competitivos para proteger, mas os seus produtos s\u00e3o inerentemente mais arriscados, uma vez que podem ser utilizados e modificados por quase toda a gente.\u00a0<\/span><\/p>\n

Por outro lado, os programadores privados manter\u00e3o provavelmente alguns aspectos dos seus modelos fechados a sete chaves, mas podem demonstrar seguran\u00e7a e redu\u00e7\u00e3o de riscos. At\u00e9 mesmo a Microsoft, o principal investidor da OpenAI, n\u00e3o tem a certeza absoluta de que os seus modelos s\u00e3o seguros. compreender o funcionamento dos modelos da OpenAI<\/a>.\u00a0<\/span><\/p>\n

O que \u00e9 que o estudo recomenda?\u00a0<\/span><\/h2>\n

Os autores do estudo reconhecem que o fosso entre as expectativas da UE e a realidade \u00e9 alarmante e apresentam v\u00e1rias recomenda\u00e7\u00f5es aos decisores pol\u00edticos e aos criadores de modelos.<\/p>\n

O estudo recomenda aos decisores pol\u00edticos da UE:<\/span><\/p>\n

    \n
  • Aperfei\u00e7oar e especificar os par\u00e2metros da Lei da IA da UE<\/b>: Os investigadores argumentam que a linguagem t\u00e9cnica e os par\u00e2metros da Lei da IA s\u00e3o pouco espec\u00edficos.\u00a0<\/span><\/li>\n
  • Promover a transpar\u00eancia e a responsabiliza\u00e7\u00e3o<\/b>: Os investigadores defendem que as regras mais rigorosas devem ser ultra-orientadas para os maiores e mais dominantes promotores, o que dever\u00e1 conduzir a uma aplica\u00e7\u00e3o mais eficaz.\u00a0<\/span><\/li>\n
  • Disponibilizar recursos suficientes para a aplica\u00e7\u00e3o da lei<\/b>: Para que a Lei da IA da UE seja efetivamente aplicada, devem ser disponibilizados recursos t\u00e9cnicos e talentos \u00e0s ag\u00eancias de execu\u00e7\u00e3o.\u00a0<\/span><\/li>\n<\/ul>\n

    O estudo recomenda aos decisores pol\u00edticos mundiais:<\/span><\/p>\n

      \n
    • Dar prioridade \u00e0 transpar\u00eancia<\/b>: Os investigadores sublinham que a transpar\u00eancia \u00e9 fundamental e deve ser o principal objetivo dos esfor\u00e7os pol\u00edticos. Argumentam que os ensinamentos retirados da regulamenta\u00e7\u00e3o dos meios de comunica\u00e7\u00e3o social revelam as consequ\u00eancias nefastas de uma transpar\u00eancia deficiente, que n\u00e3o devem ser repetidas no contexto da IA.\u00a0<\/span><\/li>\n
    • Esclarecer quest\u00f5es de direitos de autor<\/b>: Os limites dos direitos de autor para os dados de treino e os resultados da IA s\u00e3o objeto de um debate aceso. Dada a baixa conformidade observada na divulga\u00e7\u00e3o de dados de forma\u00e7\u00e3o protegidos por direitos de autor, os investigadores defendem que as directrizes legais devem especificar a forma como os direitos de autor interagem com os procedimentos de forma\u00e7\u00e3o e os resultados dos modelos generativos. Tal inclui a defini\u00e7\u00e3o dos termos em que os direitos de autor ou as licen\u00e7as devem ser respeitados durante a forma\u00e7\u00e3o e a determina\u00e7\u00e3o da forma como os conte\u00fados gerados por m\u00e1quinas podem infringir os direitos de autor.<\/span><\/li>\n<\/ul>\n

      O estudo recomenda aos criadores de modelos de funda\u00e7\u00f5es:<\/span><\/p>\n

        \n
      • Esfor\u00e7ar-se por melhorar continuamente<\/b>: Os fornecedores devem procurar melhorar sistematicamente a sua conformidade. Os fornecedores de maior dimens\u00e3o, como a OpenAI, devem dar o exemplo e divulgar recursos aos clientes a jusante que acedem aos seus modelos atrav\u00e9s de API.\u00a0<\/span><\/li>\n
      • Defender as normas do sector<\/b>: Os fornecedores de modelos devem contribuir para o estabelecimento de normas do sector, o que pode conduzir a um ecossistema de IA mais transparente e respons\u00e1vel.<\/span><\/li>\n<\/ul>\n

        Embora haja alguns aspectos positivos a retirar das normas de risco e monitoriza\u00e7\u00e3o estabelecidas pelos principais criadores, como a OpenAI, as defici\u00eancias em \u00e1reas como os direitos de autor est\u00e3o longe de ser ideais.<\/p>\n

        Quanto \u00e0 aplica\u00e7\u00e3o da regulamenta\u00e7\u00e3o \u00e0 IA como uma categoria abrangente -<\/span> isso pode revelar-se muito complicado - <\/span>uma vez que os modelos comerciais e de c\u00f3digo aberto s\u00e3o estruturalmente distintos e dif\u00edceis de agrupar.<\/p>","protected":false},"excerpt":{"rendered":"

        Os investigadores de IA de Stanford avaliaram a conformidade de 10 modelos de IA l\u00edderes em rela\u00e7\u00e3o \u00e0 proposta de Lei de IA da UE e descobriram uma grande varia\u00e7\u00e3o, com resultados geralmente med\u00edocres em toda a linha. O estudo examinou criticamente 10 modelos de IA em rela\u00e7\u00e3o a 12 crit\u00e9rios estabelecidos no projeto de legisla\u00e7\u00e3o da UE e revelou uma grande varia\u00e7\u00e3o na conformidade, n\u00e3o havendo nenhum modelo que preencha todos os requisitos. O estudo real\u00e7a o fosso entre as expectativas da Lei da IA e os actuais esfor\u00e7os de governa\u00e7\u00e3o entre os principais criadores de IA. Para cumprir a lei, os criadores t\u00eam de melhorar consideravelmente a sua transpar\u00eancia e as suas estrat\u00e9gias de mitiga\u00e7\u00e3o de riscos, que, em alguns casos, s\u00e3o quase inexistentes. Como<\/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\/pt\/2023\/06\/stanford-researchers-test-ai-model-compliance-against-the-eu-ai-act\/\" \/>\n<meta property=\"og:locale\" content=\"pt_PT\" 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