ETHICS AND TRUST: NAVIGATING BIAS AND PRIVACY IN AI ENABLED HOSPITALITY

Abstract

The rapid adoption of artificial intelligence in the hospitality industry has transformed service delivery, customer engagement, and operational efficiency. AI-driven systems such as facial recognition check-ins, dynamic pricing algorithms, recommendation engines, and predictive analytics increasingly shape guest experiences and managerial decision-making. However, these technological advancements also introduce complex ethical concerns related to algorithmic bias, data privacy, surveillance, and trust erosion among stakeholders. This chapter conceptually examines the ethical and trust-related challenges associated with AI-enabled hospitality systems, with particular emphasis on bias embedded in automated decision-making and privacy risks arising from large-scale data collection and processing. Drawing upon interdisciplinary literature from hospitality management, information systems, and AI ethics, the chapter synthesizes key ethical tensions and governance gaps influencing trust formation between guests, employees, and organizations. The analysis highlights how opaque algorithms, unequal data representation, and insufficient regulatory safeguards can undermine fairness, transparency, and accountability in hospitality operations. The chapter further proposes a conceptual framework that links ethical AI practices with trust outcomes in hospitality contexts. By articulating implications for theory, practice, and policy, this chapter contributes to ongoing debates on responsible AI adoption and underscores the necessity of embedding ethical governance mechanisms to sustain long-term trust in AI-enabled hospitality ecosystems.

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