{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T13:40:57Z","timestamp":1787924457860,"version":"build-2784847793"},"reference-count":120,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2025,2,2]],"date-time":"2025-02-02T00:00:00Z","timestamp":1738454400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Military Sealift Command","award":["N0003323WX00531"],"award-info":[{"award-number":["N0003323WX00531"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Artificial intelligence is set to incorporate additional decision space that has traditionally been the purview of humans. However, AI systems that support decision making also entail the rationalization of AI outputs by humans. Yet, incongruencies between AI and human rationalization processes may introduce uncertainties in human decision making, which require new conceptualizations to improve the predictability of these interactions. The application of quantum probability theory (QPT) to human cognition is on the ascent and warrants potential consideration to human\u2013AI decision making to improve these outcomes. This perspective paper explores how QPT may be applied to human\u2013AI interactions and contributes by integrating these concepts into human-in-the-loop decision making. To capture this and offer a more comprehensive conceptualization, we use human-in-the-loop constructs to explicate how recent applications of QPT can ameliorate the models of interaction by providing a novel way to capture these behaviors. Followed by a summary of the challenges posed by human-in-the-loop systems, we discuss newer theories that advance models of the cognitive system by using quantum probability formalisms. We conclude by outlining areas of promising future research in human\u2013AI decision making in which the proposed methods may apply.<\/jats:p>","DOI":"10.3390\/e27020152","type":"journal-article","created":{"date-parts":[[2025,2,3]],"date-time":"2025-02-03T05:36:32Z","timestamp":1738560992000},"page":"152","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["A Quantum Probability Approach to Improving Human\u2013AI Decision Making"],"prefix":"10.3390","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2257-3072","authenticated-orcid":false,"given":"Scott","family":"Humr","sequence":"first","affiliation":[{"name":"Department of Information Sciences, Naval Postgraduate School, Monterey, CA 93943, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mustafa","family":"Canan","sequence":"additional","affiliation":[{"name":"Department of Information Sciences, Naval Postgraduate School, Monterey, CA 93943, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mustafa","family":"Demir","sequence":"additional","affiliation":[{"name":"Applied Cognitive Ergonomics Laboratory, Texas A&M University, College Station, TX 77843, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,2,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1287\/orsc.2021.1544","article-title":"In the land of the blind, the one-eyed man is king: Knowledge brokerage in the age of learning algorithms","volume":"33","author":"Waardenburg","year":"2022","journal-title":"Organ. 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