{"id":12174,"date":"2026-04-17T05:04:14","date_gmt":"2026-04-17T05:04:14","guid":{"rendered":"https:\/\/serisec.com\/index.php\/2026\/04\/17\/human-trust-of-ai-agents-html\/"},"modified":"2026-04-17T05:04:14","modified_gmt":"2026-04-17T05:04:14","slug":"human-trust-of-ai-agents-html","status":"publish","type":"post","link":"https:\/\/serisec.com\/index.php\/2026\/04\/17\/human-trust-of-ai-agents-html\/","title":{"rendered":"Human Trust of AI Agents"},"content":{"rendered":"\n<div>Human Trust of AI Agents<\/div>\n<p> \t<BR><br \/>\n<BR><\/BR><br \/>\n    <!-- no image --><br \/>\n \t<BR><br \/>\n<BR><\/BR><\/p>\n<div>\n<p>Interesting research: \u201c<a href=\"https:\/\/arxiv.org\/pdf\/2505.11011\">Humans expect rationality and cooperation from LLM opponents in strategic games<\/a>.\u201d<\/p>\n<blockquote>\n<p><b>Abstract:<\/b> As Large Language Models (LLMs) integrate into our social and economic interactions, we need to deepen our understanding of how humans respond to LLMs opponents in strategic settings. We present the results of the first controlled monetarily-incentivised laboratory experiment looking at differences in human behaviour in a multi-player p-beauty contest against other humans and LLMs. We use a within-subject design in order to compare behaviour at the individual level. We show that, in this environment, human subjects choose significantly lower numbers when playing against LLMs than humans, which is mainly driven by the increased prevalence of \u2018zero\u2019 Nash-equilibrium choices. This shift is mainly driven by subjects with high strategic reasoning ability. Subjects who play the zero Nash-equilibrium choice motivate their strategy by appealing to perceived LLM\u2019s reasoning ability and, unexpectedly, propensity towards cooperation. Our findings provide foundational insights into the multi-player human-LLM interaction in simultaneous choice games, uncover heterogeneities in both subjects\u2019 behaviour and beliefs about LLM\u2019s play when playing against them, and suggest important implications for mechanism design in mixed human-LLM systems.<\/p>\n<\/blockquote>\n<\/div>\n<p> \t<BR><br \/>\n <BR><\/BR><br \/>\n    Bruce Schneier<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n<a href=\"https:\/\/www.schneier.com\/blog\/archives\/2026\/04\/human-trust-of-ai-agents.html\">Go to bruce schneier<\/a><br \/>\n \t<BR><br \/>\n <BR><\/BR><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Human Trust of AI Agents Interesting research: \u201cHumans expect rationality and cooperation from LLM opponents in strategic games.\u201d Abstract: As Large Language Models (LLMs) integrate into our social and economic interactions, we need to deepen our understanding of how humans respond to LLMs opponents in strategic settings. We present the results of the first controlled [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[88,167,57,849,268,999,1],"tags":[87],"class_list":["post-12174","post","type-post","status-publish","format-standard","hentry","category-academic-papers","category-ai","category-bruce-schneier","category-games","category-llm","category-trust","category-uncategorized","tag-bruce-schneier"],"_links":{"self":[{"href":"https:\/\/serisec.com\/index.php\/wp-json\/wp\/v2\/posts\/12174"}],"collection":[{"href":"https:\/\/serisec.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/serisec.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/serisec.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/serisec.com\/index.php\/wp-json\/wp\/v2\/comments?post=12174"}],"version-history":[{"count":0,"href":"https:\/\/serisec.com\/index.php\/wp-json\/wp\/v2\/posts\/12174\/revisions"}],"wp:attachment":[{"href":"https:\/\/serisec.com\/index.php\/wp-json\/wp\/v2\/media?parent=12174"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/serisec.com\/index.php\/wp-json\/wp\/v2\/categories?post=12174"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/serisec.com\/index.php\/wp-json\/wp\/v2\/tags?post=12174"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}