{"id":6672,"date":"2023-10-22T17:29:32","date_gmt":"2023-10-22T17:29:32","guid":{"rendered":"https:\/\/dailyai.com\/?p=6672"},"modified":"2023-10-22T19:25:00","modified_gmt":"2023-10-22T19:25:00","slug":"chatgpt-shows-strengths-in-emulating-the-peer-review-process","status":"publish","type":"post","link":"https:\/\/dailyai.com\/fr\/2023\/10\/chatgpt-shows-strengths-in-emulating-the-peer-review-process\/","title":{"rendered":"ChatGPT montre des points forts dans l'\u00e9mulation du processus d'\u00e9valuation par les pairs"},"content":{"rendered":"

L'approche conventionnelle de la recherche scientifique s'appuie fortement sur l'examen par les pairs, o\u00f9 d'autres scientifiques \u00e9valuent et critiquent m\u00e9ticuleusement une \u00e9tude avant qu'elle ne soit publi\u00e9e.\u00a0<\/b><\/p>\n

Toutefois, ce syst\u00e8me traditionnel se heurte \u00e0 des goulets d'\u00e9tranglement en raison du nombre croissant de soumissions et de la p\u00e9nurie d'\u00e9valuateurs humains disponibles.\u00a0<\/span><\/p>\n

\"Il est de plus en plus difficile pour les chercheurs d'obtenir un retour d'information de qualit\u00e9 de la part des \u00e9valuateurs\", explique James Zou, de l'universit\u00e9 de Stanford.<\/span><\/p>\n

Pour relever ce d\u00e9fi, Zou et son \u00e9quipe ont <\/span>tourn\u00e9 vers ChatGPT<\/span><\/a> afin de d\u00e9terminer si le chatbot pouvait fournir un retour d'information clair et objectif sur les articles de recherche. Ils ont utilis\u00e9 GPT-4 pour examiner plus de 3 000 manuscrits de Nature et plus de 1 700 articles de la Conf\u00e9rence internationale sur les repr\u00e9sentations de l'apprentissage (ICLR).\u00a0<\/span><\/p>\n

En comparant les commentaires du ChatGPT \u00e0 ceux des \u00e9valuateurs humains sur les m\u00eames articles, ils ont constat\u00e9 que plus de 50% des commentaires de l'IA sur les articles de Nature et plus de 77% sur les articles de l'ICLR s'alignaient sur les points soulev\u00e9s par les \u00e9valuateurs humains.<\/span><\/p>\n

En \u00e9largissant l'exp\u00e9rience, l'\u00e9quipe a \u00e9galement utilis\u00e9 ChatGPT pour \u00e9valuer plusieurs centaines d'articles qui n'ont pas encore \u00e9t\u00e9 examin\u00e9s par des pairs et qui se trouvent sur des serveurs de pr\u00e9impression. <\/span><\/p>\n

En recueillant les commentaires de 308 auteurs dans le domaine de l'IA et de la biologie informatique, ils ont constat\u00e9 que plus de 82% d'entre eux consid\u00e9raient que les commentaires de ChatGPT \u00e9taient g\u00e9n\u00e9ralement plus b\u00e9n\u00e9fiques que certains des commentaires qu'ils avaient re\u00e7us par le pass\u00e9 de la part d'\u00e9valuateurs humains.<\/span><\/p>\n

Malgr\u00e9 ces r\u00e9sultats prometteurs, des inqui\u00e9tudes subsistent quant \u00e0 la capacit\u00e9 de l'IA \u00e0 fournir un retour d'information nuanc\u00e9 et techniquement d\u00e9taill\u00e9.\u00a0<\/span><\/p>\n

De plus, le retour d'information de ChatGPT peut \u00eatre impr\u00e9visible, avec des r\u00e9sultats variables selon le contenu de l'\u00e9tude.<\/p>\n

Zou reconna\u00eet ces limites, notant que certains chercheurs ont trouv\u00e9 le retour d'information de ChatGPT trop vague. <\/span><\/p>\n

Les chercheurs sont rest\u00e9s optimistes quant \u00e0 la capacit\u00e9 du GPT-4 \u00e0 faciliter le processus d'\u00e9valuation par les pairs, en signalant les erreurs et les incoh\u00e9rences les plus \u00e9videntes.\u00a0<\/span><\/p>\n

En savoir plus sur l'\u00e9tude<\/span><\/h2>\n

ChatGPT - en particulier le mod\u00e8le GPT-4 - est pratiquement efficace pour examiner les \u00e9tudes scientifiques et fournir un retour d'information rapide.\u00a0<\/span><\/p>\n

Voici plus d'informations sur l'\u00e9tude :<\/span><\/p>\n

    \n
  1. Objectif<\/b>: L'\u00e9tude met en \u00e9vidence la difficult\u00e9 d'obtenir des \u00e9valuations de haute qualit\u00e9 par des pairs humains. Elle visait \u00e0 explorer l'utilisation de grands mod\u00e8les de langage (LLM) tels que GPT-4 pour fournir un retour d'information scientifique sur les manuscrits de recherche.\u00a0<\/span><\/li>\n
  2. Mod\u00e8le de conception<\/b>: Les chercheurs ont cr\u00e9\u00e9 un pipeline automatis\u00e9 utilisant GPT-4 pour fournir des commentaires sur les PDF complets d'articles scientifiques. Ce pipeline est con\u00e7u pour \u00e9valuer dans quelle mesure les commentaires g\u00e9n\u00e9r\u00e9s par LLM peuvent compl\u00e9ter ou aider les processus d'examen par les pairs existants dans l'\u00e9dition scientifique.<\/span><\/li>\n
  3. R\u00e9sultats<\/b>: La qualit\u00e9 du retour d'information de GPT-4 a \u00e9t\u00e9 \u00e9valu\u00e9e au moyen de deux \u00e9tudes. La premi\u00e8re consistait en une analyse r\u00e9trospective, dans laquelle les commentaires g\u00e9n\u00e9r\u00e9s ont \u00e9t\u00e9 compar\u00e9s aux commentaires d'\u00e9valuateurs humains sur 3 096 articles provenant de 15 revues de la famille Nature et 1 709 articles provenant de la conf\u00e9rence sur l'apprentissage automatique de l'ICLR. Le chevauchement des points soulev\u00e9s par le GPT-4 et les \u00e9valuateurs humains a fait l'objet d'une \u00e9valuation quantitative.<\/span><\/li>\n
  4. La seconde \u00e9tude a \u00e9t\u00e9 men\u00e9e aupr\u00e8s de 308 chercheurs de 110 institutions am\u00e9ricaines dans le domaine de l'IA et de la biologie computationnelle. Ces chercheurs ont donn\u00e9 leur avis sur le retour d'information g\u00e9n\u00e9r\u00e9 par le syst\u00e8me GPT-4 dans leurs propres articles.\u00a0<\/span><\/li>\n
  5. Conclusions<\/b>: Les chercheurs ont constat\u00e9 un chevauchement important entre les points soulev\u00e9s par le GPT-4 et les r\u00e9viseurs humains, ainsi que des perceptions positives du retour d'information g\u00e9n\u00e9r\u00e9 par le LLM de la part de la plupart des participants \u00e0 l'\u00e9tude sur les utilisateurs. Les r\u00e9sultats sugg\u00e8rent que le LLM et le feedback humain peuvent se compl\u00e9ter, bien que des limitations du feedback g\u00e9n\u00e9r\u00e9 par le LLM aient \u00e9galement \u00e9t\u00e9 identifi\u00e9es.<\/span><\/li>\n<\/ol>\n

    Le GPT-4 a tr\u00e8s certainement fait l'objet de centaines de milliers d'\u00e9tudes scientifiques, ce qui a eu pour effet d'augmenter les co\u00fbts de production.<\/span> contribue probablement \u00e0 la capacit\u00e9 du mod\u00e8le \u00e0 diss\u00e9quer et \u00e0 critiquer la recherche avec pr\u00e9cision, de la m\u00eame mani\u00e8re que les pairs \u00e9valuateurs humains.\u00a0<\/span><\/p>\n

    L'IA est de plus en plus imbriqu\u00e9e dans les processus acad\u00e9miques. Nature a r\u00e9cemment a interrog\u00e9 1 600 chercheurs<\/a> sur leurs opinions concernant les IA g\u00e9n\u00e9ratives telles que ChatGPT, et bien que beaucoup aient exprim\u00e9 des craintes de partialit\u00e9, la majorit\u00e9 a admis que leur int\u00e9gration dans le processus scientifique \u00e9tait in\u00e9vitable. <\/span><\/p>","protected":false},"excerpt":{"rendered":"

    L'approche conventionnelle de la recherche scientifique s'appuie fortement sur l'examen par les pairs, o\u00f9 d'autres scientifiques \u00e9valuent et critiquent m\u00e9ticuleusement une \u00e9tude avant qu'elle ne soit publi\u00e9e. Toutefois, ce syst\u00e8me traditionnel se heurte \u00e0 un goulot d'\u00e9tranglement en raison du nombre croissant de soumissions et de la raret\u00e9 des \u00e9valuateurs humains disponibles. \"Il est de plus en plus difficile pour les chercheurs d'obtenir un retour d'information de qualit\u00e9 de la part des \u00e9valuateurs\", explique James Zou, de l'universit\u00e9 de Stanford. Pour relever ce d\u00e9fi, M. Zou et son \u00e9quipe se sont tourn\u00e9s vers ChatGPT afin de d\u00e9terminer si le chatbot pouvait fournir des commentaires clairs et objectifs sur les articles de recherche. Ils ont utilis\u00e9 GPT-4 pour examiner plus de 3 000 manuscrits tir\u00e9s de Nature et plus encore.<\/p>","protected":false},"author":2,"featured_media":6673,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[88],"tags":[115,143,93,135],"class_list":["post-6672","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ethics","tag-chatgpt","tag-natural-language-processing","tag-openai","tag-science"],"yoast_head":"\nChatGPT shows strengths in emulating the peer review process | DailyAI<\/title>\n<meta name=\"description\" content=\"The conventional approach to scientific research heavily relies on peer review, where other scientists meticulously evaluate and critique a study before it gets published.\u00a0\" \/>\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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