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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>An analysis of AI Decision under Risk: Prospect theory emerges in Large Language Models · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2508.00902/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2508.00902/feed.xml" rel="self" type="application/rss+xml" /><item><title>An analysis of AI Decision under Risk: Prospect theory emerges in Large Language Models — mentioned by ineedasername</title><link>https://news.ycombinator.com/item?id=47157707</link><guid isPermaLink="false">urn:hackerpapers:mention:2508.00902:47157707</guid><pubDate>Wed, 25 Feb 2026 20:53:27 GMT</pubDate><description>&lt;p&gt;Horribly misleading title on this article, the actual research paper&amp;#x27;s headline is better. (https://arxiv.org/pdf/2508.00902) But the research itself has flawed methodology if the goal is to get a precise model of the LLM&amp;#x27;s real response in a real scenario. First, the real research does not at all present conclusions quite this way, much less in these terms. It, at least, is more neutral in tone on this aspect. However, the LLM&amp;#x27;s knew it was a wargame, pretend scenario and contrived circumstances. They were told they were the commander. Most flawed for determining real world actions, their…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2508.00902/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item></channel></rss>
