Algorithmic Bias and Hospitality Justice: Simulating AI Discrimination through Legal and Neurocognitive Lenses

Algorithmic Bias and Hospitality Justice: Simulating AI Discrimination through Legal and Neurocognitive Lenses | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Algorithmic Bias and Hospitality Justice: Simulating AI Discrimination through Legal and Neurocognitive Lenses Majid Heidari, Hossein Hosseinalibeiki, Mohammad Zaree, Mary Goretti Byamugisha This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6976786/v2 This work is licensed under a CC BY 4.0 License Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Abstract As artificial intelligence becomes increasingly integrated into the hospitality and tourism service systems, it raises questions related to fairness, inclusion, and accountability in algorithmic decision-making. This study presents a simulation-based evaluation model to explore how AI service-delivery decisions impact guests from cognitive, affective, and legal perspectives. Drawing on predictive processing theory, affective neuroscience, and international anti-discrimination law, the model simulates interactions between diverse traveler profiles and distinct AI decision architectures—transparent, opaque, and multi-input systems—commonly deployed in hospitality and tourism contexts that involve AI-based personalization, such as access decisions, eligibility screening, or service prioritization. A total of 108 synthetic interactions were generated across systematically varied profile–AI pairings and diagnostic rules. Every simulation-based interaction produces two main outputs: a perceptual fairness index and a legal compliance score, thus identifying trust deficits that correlate with normative risks. The results consistently exhibit differences in emotional legitimacy and legal adequacy for profiles marked as either linguistically or gender-based. Opaque and multi-input systems often heighten dissonance, but transparent AI encodings can serve as perceptual stabilizers for different identity system groups. This study demonstrates that algorithmic fairness must evolve from merely procedural logic to encompass relational trust and emotional valence. Moreover, it also helps design inclusivity and check the compliance of hospitality technologies by providing a tool that creates a risk simulator, which can be tested in meaningful and real-world situations. Hospitality and Tourism Algorithmic Fairness Affective Trust Simulation-Based Governance Hospitality AI Anti-Discrimination Compliance Neurocognitive Risk Modeling Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6976786","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":477233687,"identity":"2b9b2125-d3e0-45ff-a00b-ddcb5369786f","order_by":0,"name":"Majid Heidari","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAw0lEQVRIiWNgGAWjYDACCQaGAzwMDDz8QPYBIOYhXotkA1QLYT0SUJMNDkAFCGrRnd188MCbmnsyxjdyDx78UcMgY09Ii9mdYwkH5xwr5jG7kZdwmOcYEQ4zu5FjcJiHLYEHzGBgI0pL/ofDPP8SeIxn5Bgc/PGPOFsYDvO2JfAYSOQYHOBtI0pLmsHBuX0JPBJn3hgc5u2T4OE5QFBL8uMPb74l2PO35xh//PHNxp69gZA1aECCRPWjYBSMglEwCrACAAN/PsFTynYRAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-5619-2289","institution":"University of Salerno","correspondingAuthor":true,"prefix":"","firstName":"Majid","middleName":"","lastName":"Heidari","suffix":""},{"id":477233688,"identity":"991d8f62-1055-4b23-baf9-ebc6f7e325a2","order_by":1,"name":"Hossein Hosseinalibeiki","email":"","orcid":"https://orcid.org/0009-0000-0270-2944","institution":"University of Salerno","correspondingAuthor":false,"prefix":"","firstName":"Hossein","middleName":"","lastName":"Hosseinalibeiki","suffix":""},{"id":477233689,"identity":"31b69d40-c3b0-4b2f-abbc-5b853cebfa55","order_by":2,"name":"Mohammad Zaree","email":"","orcid":"","institution":"University of Salerno","correspondingAuthor":false,"prefix":"","firstName":"Mohammad","middleName":"","lastName":"Zaree","suffix":""},{"id":477233690,"identity":"62914800-ff7e-465b-8a4f-2994d158af7b","order_by":3,"name":"Mary Goretti Byamugisha","email":"","orcid":"","institution":"University of Salerno","correspondingAuthor":false,"prefix":"","firstName":"Mary","middleName":"Goretti","lastName":"Byamugisha","suffix":""}],"badges":[],"createdAt":"2025-06-25 16:51:42","currentVersionCode":2,"declarations":{"humanSubjects":false,"vertebrateSubjects":true,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":true},"doi":"10.21203/rs.3.rs-6976786/v2","doiUrl":"https://doi.org/10.21203/rs.3.rs-6976786/v2","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85574747,"identity":"934e989f-d92d-45f6-ba4d-b4408b14a12d","added_by":"auto","created_at":"2025-06-27 17:55:58","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1111334,"visible":true,"origin":"","legend":"","description":"","filename":"BlindedManuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6976786/v2_covered_9567ee7d-664c-4d21-9c20-8f176d24cd43.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"Algorithmic Bias and Hospitality Justice: Simulating AI Discrimination through Legal and Neurocognitive Lenses","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of Salerno","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Algorithmic Fairness, Affective Trust, Simulation-Based Governance, Hospitality AI, Anti-Discrimination Compliance, Neurocognitive Risk Modeling","lastPublishedDoi":"10.21203/rs.3.rs-6976786/v2","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6976786/v2","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAs artificial intelligence becomes increasingly integrated into the hospitality and tourism service systems, it raises questions related to fairness, inclusion, and accountability in algorithmic decision-making. 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