<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Generative-AI-Review on LegalRealist AI</title><link>https://legalrealist.ai/tags/generative-ai-review/</link><description>Recent content in Generative-AI-Review on LegalRealist AI</description><generator>Hugo -- gohugo.io</generator><language>en</language><managingEditor>hi@legalrealist.ai (LegalRealist AI)</managingEditor><webMaster>hi@legalrealist.ai (LegalRealist AI)</webMaster><copyright>© 2026 LegalRealist AI</copyright><lastBuildDate>Tue, 09 Jun 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://legalrealist.ai/tags/generative-ai-review/index.xml" rel="self" type="application/rss+xml"/><item><title>88% Recall, One Attorney, 18 Hours</title><link>https://legalrealist.ai/posts/52-redgrave-genai-review-study/</link><pubDate>Tue, 09 Jun 2026 00:00:00 +0000</pubDate><author>hi@legalrealist.ai (LegalRealist AI)</author><guid>https://legalrealist.ai/posts/52-redgrave-genai-review-study/</guid><description>A new working paper ran generative AI document review and a managed active-learning workflow head to head on the same 45,004-document corpus. Same review protocol, same reference labels, same scorecard. The GenAI system won on recall, and the paired test backs it up. The rest of the scorecard — precision, the 62-to-1 effort gap, the population extrapolation — needs more qualification than the headline suggests.</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://legalrealist.ai/posts/52-redgrave-genai-review-study/feature.png"/></item></channel></rss>