<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Recruitment on English AI Terms Dictionary</title><link>https://terms-en.ai-term-hub.com/en/tags/recruitment/</link><description>Recent content in Recruitment on English AI Terms Dictionary</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sat, 18 Jul 2026 11:44:44 +0000</lastBuildDate><atom:link href="https://terms-en.ai-term-hub.com/en/tags/recruitment/index.xml" rel="self" type="application/rss+xml"/><item><title>Artificial intelligence in hiring</title><link>https://terms-en.ai-term-hub.com/en/terms/artificial_intelligence_in_hiring/</link><pubDate>Sat, 18 Jul 2026 09:46:35 +0000</pubDate><guid>https://terms-en.ai-term-hub.com/en/terms/artificial_intelligence_in_hiring/</guid><description>&lt;h2 id="definition">Definition&lt;/h2>
&lt;p>AI in hiring utilizes algorithms to automate and enhance various stages of the recruitment lifecycle. Tools analyze resumes for keyword relevance, assess candidate fit through predictive modeling, and even evaluate video interviews via facial expression or tone analysis. This increases efficiency and reduces human bias in initial screenings. However, it can perpetuate existing biases if training data is flawed, leading to discriminatory outcomes. Organizations must balance automation with fairness and transparency to maintain trust and legal compliance.&lt;/p></description></item></channel></rss>