{"id":64482,"date":"2025-07-08T20:15:06","date_gmt":"2025-07-08T20:15:06","guid":{"rendered":"https:\/\/pros.com\/b2b\/\/?post_type=news&#038;p=64482"},"modified":"2025-07-14T20:17:31","modified_gmt":"2025-07-14T20:17:31","slug":"the-layered-ai-responsibility-lair-framework","status":"publish","type":"news","link":"https:\/\/pros.com\/b2b\/fr\/news\/the-layered-ai-responsibility-lair-framework\/","title":{"rendered":"Le cadre de responsabilit\u00e9 hi\u00e9rarchique de l'IA (LAIR)"},"content":{"rendered":"<p>\u00c0 mesure que les grands mod\u00e8les de langage deviennent plus intelligents et que les agents d'intelligence artificielle acqui\u00e8rent davantage d'outils et de capacit\u00e9s, le d\u00e9veloppement responsable de ces technologies devient primordial. Ayant beaucoup travaill\u00e9 dans l'industrie et dans le monde universitaire, j'ai observ\u00e9 un foss\u00e9 important dans la mani\u00e8re dont l'IA responsable est consid\u00e9r\u00e9e comme une priorit\u00e9. <\/p>\n<h2>Introduction : Perspectives acad\u00e9miques et industrielles sur l'IA responsable<\/h2>\n<p>Le monde universitaire a tendance \u00e0 aborder l'IA responsable avec un \u00e9tat d'esprit id\u00e9aliste. Les \u00e9tudiants et les chercheurs apprennent \u00e0 int\u00e9grer des consid\u00e9rations \u00e9thiques, juridiques et de s\u00e9curit\u00e9 dans les syst\u00e8mes d'IA d\u00e8s le premier jour et tout au long du processus de d\u00e9veloppement. Cette approche est pr\u00e9cieuse et permet d'atteindre les normes les plus \u00e9lev\u00e9es. Cependant, elle est souvent peu pratique dans les milieux industriels, o\u00f9 les pressions financi\u00e8res et les d\u00e9lais des produits exigent un d\u00e9veloppement et un d\u00e9ploiement rapides.<\/p>\n<p>&nbsp;<\/p>\n<p><a class=\"pill-button\" href=\"https:\/\/aijourn.com\/the-layered-ai-responsibility-lair-framework\/\" target=\"_blank\" rel=\"noopener\">En savoir plus<\/a><\/p>","protected":false},"excerpt":{"rendered":"<p>As large language models (LLMs) grow smarter and AI agents gain more tools and capabilities, the responsible development of these technologies becomes paramount. Having worked extensively in both industry and academia, I have observed a significant divide in how responsible AI is prioritized. Introduction: Academia vs. Industry Perspectives on Responsible AI Academia tends to approach [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"_acf_changed":false,"inline_featured_image":false},"news-type":[20],"class_list":["post-64482","news","type-news","status-publish","hentry","news-type-pros-in-the-news"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v26.7 (Yoast SEO v27.3) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>The Layered AI Responsibility (LAIR) Framework | PROS B2B<\/title>\n<meta name=\"robots\" content=\"noindex, nofollow\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"The Layered AI Responsibility (LAIR) Framework\" \/>\n<meta property=\"og:description\" content=\"As large language models (LLMs) grow smarter and AI agents gain more tools and capabilities, the responsible development of these technologies becomes paramount. 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