<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Research on Greycloak</title><link>https://greycloak.com/tags/research/</link><description>Recent content in Research on Greycloak</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><copyright>Copyright © 2023, Vince Wadhwani; all rights reserved.</copyright><lastBuildDate>Wed, 16 Sep 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://greycloak.com/tags/research/index.xml" rel="self" type="application/rss+xml"/><item><title>When AI Solves the Problem but Skips the Understanding</title><link>https://greycloak.com/post/2026-09-16-mathematicians-warn-ai-benchmarks-harm-their-field/</link><pubDate>Wed, 16 Sep 2026 00:00:00 +0000</pubDate><guid>https://greycloak.com/post/2026-09-16-mathematicians-warn-ai-benchmarks-harm-their-field/</guid><description>
&lt;p&gt;If your organization is deploying AI to produce the output of expert work, a letter published this week by some of the world's most accomplished mathematicians names a cost that won't show up on next quarter's productivity dashboard: the erosion of the judgment that made the work valuable in the first place. The argument is narrow on its surface and much broader underneath, and it's worth reading before you sign off on the next automation project aimed at your senior people.&lt;/p&gt;</description></item></channel></rss>