<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>News on Zak - AI Research Intelligence</title><link>https://trueworkoffice.com/tags/news/</link><description>Recent content in News on Zak - AI Research Intelligence</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Mon, 06 Jul 2026 12:23:23 +0000</lastBuildDate><atom:link href="https://trueworkoffice.com/tags/news/index.xml" rel="self" type="application/rss+xml"/><item><title>Can readers tell human writing from AI anymore?</title><link>https://trueworkoffice.com/blog/2026-07-06-can-readers-tell-human-writing-from-ai-anymore/</link><pubDate>Mon, 06 Jul 2026 12:23:23 +0000</pubDate><guid>https://trueworkoffice.com/blog/2026-07-06-can-readers-tell-human-writing-from-ai-anymore/</guid><description>&lt;p&gt;The literary world is confronting a question that would have seemed absurd a decade ago: could artificial intelligence produce the next great novel, and would anyone notice if it did. A recent examination by The Guardian suggests the boundary between human and machine writing is far more porous than readers assume.&lt;/p&gt;
&lt;p&gt;The evidence comes from forensic linguistics research led by Claire Hardaker at the University of Lancaster. Her online assessment, Bot or Not, presents users with fifteen text samples and asks them to identify which were generated by large language models. Most participants score approximately sixty percent, barely above chance. This is not a niche concern confined to technical journals. Allegations of LLM use have already caused significant disruption in both literary and media circles, prompting serious questions about authenticity, attribution, and the value placed on human creative labour.&lt;/p&gt;</description></item></channel></rss>