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<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">SSR</journal-id><journal-title-group><journal-title>Scientific and Social Research</journal-title></journal-title-group><issn>2661-4332</issn><eissn>2981-9946</eissn><publisher><publisher-name>Bio-Byword Scientific Publishing Pty. Ltd.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26689/ssr.v8i7.15953</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Application of Artificial Intelligence in Psychological Assessment: Current Status and Challenges</title><url>https://artdesignp.com/journal/SSR/8/7/10.26689/ssr.v8i7.15953</url><author>YueYuqiao</author><pub-date pub-type="publication-year"><year>2026</year></pub-date><volume>8</volume><issue>7</issue><history><date date-type="pub"><published-time>2026-08-14</published-time></date></history><abstract>Psychological assessment is an important part of mental health services. Scientific and efficient mental health assessment and intervention are the premise of effective mental health services. Traditional psychological assessment mainly includes psychological tests and clinical interviews. With the rapid development of artificial intelligence and big data technology, psychological assessment is gradually moving towards intelligence. This paper reviews the current application of key technologies of artificial intelligence in psychological assessment, discusses its challenges in psychometric validity, ethics, and technical limitations. The results show that although artificial intelligence has great potential to improve the accessibility, efficiency, and accuracy of psychological assessment, its integration with clinical practice requires careful attention to measurement equivalence, data privacy, algorithmic fairness, and the irreplaceable role of human consultants. 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