AI Ethics in Hospitality and Tourism: Theoretical Perspectives, Ethical Beliefs, and Actionable Outcomes

Nasim Binesh and Ahmad M. Syah

No akf4z_v1, OSF Preprints from Center for Open Science

Abstract: The rapid integration of artificial intelligence (AI) into hospitality and tourism presents profound ethical challenges, yet the industry lags behind in addressing them. Unlike sectors with established AI governance frameworks, hospitality and tourism remain highly dependent on human interaction, making ethical considerations particularly complex. This scoping review explores AI ethics in hospitality and tourism through the lenses of epistemology and the ethics of belief, examining issues of transparency, bias, privacy, and algorithmic decision-making. We critically analyze how AI systems in hospitality construct and act upon beliefs, distinguishing between justified and unjustified AI-driven assumptions in service automation, personalization, and pricing strategies. By mapping risks across different AI applications (from biometric surveillance in hotels to AI-generated recommendations in tourism) we categorize ethical concerns based on their impact and regulatory landscape. In addition to diagnosing these ethical risks, this study proposes actionable solutions to guide the responsible adoption of AI in hospitality and tourism. We introduce a sectoral risk framework to classify AI applications from unacceptable to minimal risk, offering clear regulatory pathways. We also present a structured AI life cycle approach, outlining ethical safeguards at each stage (from problem definition to deployment and feedback) ensuring AI systems align with fairness, accountability, and consumer trust. Ultimately, this research advances theoretical discourse on AI ethics in hospitality while providing practical guidelines for industry stakeholders, policymakers, and researchers seeking to develop AI-driven innovations responsibly.

Date: 2025-03-05
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Persistent link: https://EconPapers.repec.org/RePEc:osf:osfxxx:akf4z_v1

DOI: 10.31219/osf.io/akf4z_v1

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