{"id":2163,"date":"2023-06-30T21:15:16","date_gmt":"2023-06-30T21:15:16","guid":{"rendered":"https:\/\/dailyai.com\/?p=2163"},"modified":"2023-07-03T16:28:22","modified_gmt":"2023-07-03T16:28:22","slug":"anthropic-releases-paper-highlighting-the-potential-bias-of-large-language-models","status":"publish","type":"post","link":"https:\/\/dailyai.com\/fr\/2023\/06\/anthropic-releases-paper-highlighting-the-potential-bias-of-large-language-models\/","title":{"rendered":"L'article sur les rejets anthropiques r\u00e9v\u00e8le la partialit\u00e9 des grands mod\u00e8les de langage"},"content":{"rendered":"

Un nouvel article de la soci\u00e9t\u00e9 Anthropic, sp\u00e9cialis\u00e9e dans l'IA, a mis en lumi\u00e8re les biais potentiels inh\u00e9rents aux grands mod\u00e8les de langage (LLM), sugg\u00e9rant que ces syst\u00e8mes d'IA pourraient ne pas repr\u00e9senter de mani\u00e8re ad\u00e9quate les diverses perspectives mondiales sur les questions soci\u00e9tales.<\/strong><\/p>\n

Les chercheurs ont constitu\u00e9 un ensemble de donn\u00e9es, GlobalOpinionQA, comprenant des questions et des r\u00e9ponses provenant d'enqu\u00eates transnationales con\u00e7ues pour recueillir des opinions vari\u00e9es sur des questions mondiales dans diff\u00e9rents pays.\u00a0<\/span><\/p>\n

Anthropique exp\u00e9riences<\/span><\/a> a interrog\u00e9 un LLM et a constat\u00e9 que, par d\u00e9faut, les r\u00e9ponses du mod\u00e8le tendaient \u00e0 s'aligner plus \u00e9troitement sur les opinions de populations sp\u00e9cifiques, notamment celles des \u00c9tats-Unis, du Royaume-Uni, du Canada, de l'Australie et de quelques autres pays d'Europe et d'Am\u00e9rique du Sud.\u00a0<\/span><\/p>\n

Comment cela fonctionne-t-il ?<\/span><\/h2>\n
    \n
  1. Cr\u00e9ation de jeux de donn\u00e9es<\/b>: L'\u00e9quipe a cr\u00e9\u00e9 l'ensemble de donn\u00e9es GlobalOpinionQA. Cet ensemble de donn\u00e9es comprend des questions et des r\u00e9ponses provenant d'enqu\u00eates transnationales sp\u00e9cialement con\u00e7ues pour recueillir un large \u00e9ventail d'opinions sur des questions mondiales.<\/span><\/li>\n
  2. D\u00e9finition d'une m\u00e9trique de similarit\u00e9<\/b>: Ensuite, Anthropic a formul\u00e9 une m\u00e9trique pour mesurer la similarit\u00e9 entre les r\u00e9ponses donn\u00e9es par les LLM et les r\u00e9ponses des personnes. Cette m\u00e9trique prend en compte le pays d'origine des r\u00e9pondants humains.<\/span><\/li>\n
  3. Formation au LLM<\/b>: Anthropic a form\u00e9 un LLM bas\u00e9 sur \"l'IA constitutionnelle\", en s'assurant que le LLM \u00e9tait utile, honn\u00eate et inoffensif. L'IA constitutionnelle est une technique d\u00e9velopp\u00e9e par Anthropic qui vise \u00e0 impr\u00e9gner les syst\u00e8mes d'IA de \"valeurs\" d\u00e9finies par une \"constitution\".<\/span><\/li>\n
  4. Mener des exp\u00e9riences<\/b>: En utilisant leur cadre soigneusement con\u00e7u, l'\u00e9quipe d'Anthropic a ex\u00e9cut\u00e9 3 exp\u00e9riences distinctes sur le LLM form\u00e9.<\/span><\/li>\n<\/ol>\n

    Selon les chercheurs, cela met en \u00e9vidence les biais potentiels des mod\u00e8les, qui conduisent \u00e0 une sous-repr\u00e9sentation des opinions de certains groupes par rapport \u00e0 celles des pays occidentaux.\u00a0<\/span><\/p>\n

    Ils ont not\u00e9 que \"si un mod\u00e8le linguistique repr\u00e9sente de mani\u00e8re disproportionn\u00e9e certaines opinions, il risque d'avoir des effets potentiellement ind\u00e9sirables tels que la promotion de visions du monde h\u00e9g\u00e9moniques et l'homog\u00e9n\u00e9isation des points de vue et des croyances des gens\".<\/span><\/p>\n

    En outre, les chercheurs ont observ\u00e9 que le fait d'inciter le mod\u00e8le \u00e0 prendre en compte le point de vue d'un pays sp\u00e9cifique conduisait \u00e0 des r\u00e9ponses plus proches des opinions de ces populations. <\/span><\/p>\n

    Cela signifie que vous pouvez demander \u00e0 l'IA de \"prendre en compte la perspective sud-am\u00e9ricaine\" dans un certain d\u00e9bat culturel, par exemple. <\/span>Cependant, ces r\u00e9ponses refl\u00e9taient parfois des st\u00e9r\u00e9otypes culturels pr\u00e9judiciables, ce qui sugg\u00e8re que les mod\u00e8les n'ont pas une compr\u00e9hension nuanc\u00e9e des valeurs et des perspectives culturelles.<\/p>\n

    Il est int\u00e9ressant de noter que lorsque les chercheurs ont traduit les questions de GlobalOpinionQA dans une langue cible, les r\u00e9ponses du mod\u00e8le ne correspondaient pas n\u00e9cessairement aux opinions des locuteurs de ces langues. <\/span><\/p>\n

    Ainsi, poser une question en japonais, par exemple, n'entra\u00eene pas n\u00e9cessairement des r\u00e9ponses conformes aux valeurs culturelles japonaises. On ne peut pas \"s\u00e9parer\" l'IA de ses valeurs principalement occidentales. <\/span><\/p>\n

    Cela sugg\u00e8re qu'en d\u00e9pit de leur adaptabilit\u00e9, les MFR doivent acqu\u00e9rir une compr\u00e9hension plus profonde des contextes sociaux pour g\u00e9n\u00e9rer des r\u00e9ponses qui refl\u00e8tent fid\u00e8lement les opinions locales.<\/span><\/p>\n

    Les chercheurs estiment que leurs r\u00e9sultats permettront de mieux comprendre les perspectives encod\u00e9es et refl\u00e9t\u00e9es par les mod\u00e8les linguistiques actuels. Malgr\u00e9 les limites de leur \u00e9tude, ils esp\u00e8rent qu'elle guidera le d\u00e9veloppement de syst\u00e8mes d'IA qui incarnent une diversit\u00e9 de points de vue et d'exp\u00e9riences culturelles, et pas seulement ceux des groupes privil\u00e9gi\u00e9s ou dominants. Ils ont \u00e9galement publi\u00e9 leur ensemble de donn\u00e9es ainsi qu'un rapport sur l'\u00e9tat de l'art de l'IA. <\/span>visualisation interactive.<\/span><\/a><\/p>\n

    Cette \u00e9tude s'inscrit largement dans la lign\u00e9e d'autres travaux universitaires sur le th\u00e8me des valeurs sociales et culturelles de l'IA.<\/p>\n

    D'une part, la plupart des IA fondamentales sont form\u00e9es par des entreprises et des \u00e9quipes de recherche essentiellement occidentales.<\/p>\n

    En outre, le donn\u00e9es utilis\u00e9es pour former les IA<\/a> ne repr\u00e9sente pas toujours la soci\u00e9t\u00e9 dans son ensemble. Par exemple, la grande majorit\u00e9 des donn\u00e9es de formation pour les LLM sont \u00e9crites en anglais, ce qui refl\u00e8te probablement les valeurs soci\u00e9tales et culturelles des anglophones.<\/p>\n

    Les chercheurs sont bien conscients des risques de biais et de discrimination dans l'IA. Cependant, la r\u00e9solution de ce probl\u00e8me est extr\u00eamement complexe et n\u00e9cessite un m\u00e9lange judicieux d'ensembles de donn\u00e9es personnalis\u00e9s de haute qualit\u00e9 et d'une contribution et d'un suivi humains diligents.<\/p>","protected":false},"excerpt":{"rendered":"

    Un nouvel article de la soci\u00e9t\u00e9 Anthropic, sp\u00e9cialis\u00e9e dans l'IA, a mis en lumi\u00e8re les biais potentiels inh\u00e9rents aux grands mod\u00e8les de langage (LLM), sugg\u00e9rant que ces syst\u00e8mes d'IA pourraient ne pas repr\u00e9senter de mani\u00e8re ad\u00e9quate les diverses perspectives mondiales sur les questions soci\u00e9tales. Les chercheurs ont constitu\u00e9 un ensemble de donn\u00e9es, GlobalOpinionQA, comprenant des questions et des r\u00e9ponses provenant d'enqu\u00eates transnationales con\u00e7ues pour recueillir des opinions vari\u00e9es sur des questions mondiales dans diff\u00e9rents pays. Les exp\u00e9riences d'Anthropic ont interrog\u00e9 un LLM et ont montr\u00e9 que, par d\u00e9faut, les r\u00e9ponses du mod\u00e8le tendaient \u00e0 s'aligner plus \u00e9troitement sur les opinions de populations sp\u00e9cifiques, notamment celles des \u00c9tats-Unis, du Royaume-Uni, du Canada, de l'Australie et de quelques autres pays d'Europe et d'Am\u00e9rique du Sud. Comment<\/p>","protected":false},"author":2,"featured_media":2164,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[88],"tags":[148,118],"class_list":["post-2163","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ethics","tag-anthropic","tag-llms"],"yoast_head":"\nAnthropic releases paper revealing the bias of large language models | DailyAI<\/title>\n<meta name=\"description\" content=\"A new paper by AI company Anthropic has shed light on the potential biases inherent in large language models (LLMs), suggesting these AI systems may not adequately represent diverse global perspectives on societal issues.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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