{"id":242404,"date":"2026-08-08T02:32:24","date_gmt":"2026-08-08T07:32:24","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2026\/08\/hidden-goals-can-undermine-ai-teamwork-study-finds"},"modified":"2026-08-08T02:32:24","modified_gmt":"2026-08-08T07:32:24","slug":"hidden-goals-can-undermine-ai-teamwork-study-finds","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2026\/08\/hidden-goals-can-undermine-ai-teamwork-study-finds","title":{"rendered":"Hidden goals can undermine AI teamwork, study finds"},"content":{"rendered":"<p><a class=\"aligncenter blog-photo\" href=\"https:\/\/lifeboat.com\/blog.images\/hidden-goals-can-undermine-ai-teamwork-study-finds.jpg\"><\/a><\/p>\n<p>Large language models (LLMs), the computational models that underpin conversational agents such as Gemini and ChatGPT, are now widely used by people worldwide to rapidly find information, summarize documents and generate texts for specific purposes. Some computer scientists are now combining two or more of these models to create multi-agent systems, which prompt multiple artificial intelligence (AI) agents to interact, cooperate and\/or compete with the goal of completing specific tasks.<\/p>\n<p>In some scenarios, however, AI agents could have different objectives and might have access to more or less information than the other agents they are interacting with. Understanding how AI agents typically behave in these situations could help shed more light on the potential benefits and risks of multi-agent systems.<\/p>\n<p>Researchers at Mila, Universit\u00e9 de Montr\u00e9al and McGill University recently set out to explore how the hidden goals of individual AI agents could influence a multi-agent system\u2019s performance, using a framework inspired by the multiplayer social deduction game Werewolf.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Large language models (LLMs), the computational models that underpin conversational agents such as Gemini and ChatGPT, are now widely used by people worldwide to rapidly find information, summarize documents and generate texts for specific purposes. Some computer scientists are now combining two or more of these models to create multi-agent systems, which prompt multiple artificial [\u2026]<\/p>\n","protected":false},"author":662,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6],"tags":[],"class_list":["post-242404","post","type-post","status-publish","format-standard","hentry","category-robotics-ai"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/242404","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/users\/662"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=242404"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/242404\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=242404"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=242404"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=242404"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}