<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Ai Fairness on Onur Baydaş</title><link>https://onurbaydas.com/en/tags/ai-fairness/</link><description>Recent content in Ai Fairness on Onur Baydaş</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Wed, 21 Oct 2026 10:35:55 +0300</lastBuildDate><atom:link href="https://onurbaydas.com/en/tags/ai-fairness/index.xml" rel="self" type="application/rss+xml"/><item><title>Evaluating Fairness in LLM Decision-Making</title><link>https://onurbaydas.com/en/news/2026-10-21-llm-fairness-evaluation/</link><pubDate>Wed, 21 Oct 2026 10:35:55 +0300</pubDate><guid>https://onurbaydas.com/en/news/2026-10-21-llm-fairness-evaluation/</guid><description>FairStress is a study that delves deeper into the fairness of large language models&amp;#39; (LLM) decision-making processes. This work evaluates how LLMs might make biased decisions in various scenarios.</description></item></channel></rss>