<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Goodharts-Law on BRYSGO</title><link>https://www.brysgo.com/tags/goodharts-law/</link><description>Recent content in Goodharts-Law on BRYSGO</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Wed, 26 Aug 2026 00:50:49 +0000</lastBuildDate><atom:link href="https://www.brysgo.com/tags/goodharts-law/index.xml" rel="self" type="application/rss+xml"/><item><title>AI Safety Scores Mostly Measure How Big the Model Is</title><link>https://www.brysgo.com/post/2026-08-26-ai-safety-scores-mostly-measure-how-big-the-model-is/</link><pubDate>Wed, 26 Aug 2026 00:50:49 +0000</pubDate><guid>https://www.brysgo.com/post/2026-08-26-ai-safety-scores-mostly-measure-how-big-the-model-is/</guid><description>&lt;p&gt;A 2024 analysis found that scores on popular AI safety benchmarks correlate so strongly with general model capability that you can largely predict a model&amp;rsquo;s &amp;ldquo;safety&amp;rdquo; rating just by knowing how well it does on MMLU. No actual safety research required. Just make the model smarter, and the safety score follows automatically, like a shadow.&lt;/p&gt;&#10;&lt;p&gt;I&amp;rsquo;ve been thinking about what that means. On its face, it sounds like good news — bigger models are safer models. But sit with it for a second, and something starts to feel wrong.&lt;/p&gt;</description></item></channel></rss>