A Conceptual Framework for the Ethical Governance of Responsible Tourism AI

Abstract

Purpose This study examines ethical risks in hyper-personalized tourism recommendations and generative tourism information, proposes a conceptual governance framework for responsible tourism AI, and explores its application to Bukchon Hanok Village. Methods This conceptual study synthesizes literature on smart tourism, tourism AI, recommender systems, generative AI, AI ethics and responsible AI, algorithmic governance, and sustainable tourism. It links six risk domains to eight governance elements, six AI lifecycle stages, and stakeholder responsibilities, and applies the framework conceptually to Bukchon using laws, official materials, prior studies, and media reports. Results The framework identifies six risks: privacy and tourist autonomy; algorithmic bias and recommendation fairness; information accuracy, timeliness, feasibility, and safety; cultural representation and local identity; accountability and redress; and destination sustainability and regional imbalance. Eight governance elements are organized into normative principles, implementation mechanisms, and tourism-specific outcomes within an iterative lifecycle. The Bukchon application reveals tensions among regulatory accuracy, residents’ living rights, tourist safety, and provider fairness. Conclusion The framework extends AI ethics to tourism’s place-based, culturally mediated, multi-stakeholder, and capacity-constrained context. Severe or difficult-to-reverse harms and legal duties are treated as prior constraints, while remaining trade-offs are coordinated through local stakeholder governance. Further empirical validation is required.