Linking Explainable AI and Responsible AI in Hospitality and Tourism
Madara Balawardhana, Ioana Sabrina Stoica · 2026
This chapter explores the integration of Explainable Artificial Intelligence (XAI) and Responsible Artificial Intelligence (RAI) within the hospitality and tourism sectors (H&T). It examines how explainability supports transparency, fairness, and trust, while responsibility ensures ethical, inclusive, and accountable AI deployment. The proposed E3R Framework explainability by Design, Ethical Impact Assessment, Regulatory Readiness, and Responsibility Mapping provides a strategic guide for implementing ethical AI practices. The chapter also addresses challenges such as algorithmic bias, transparency-performance trade-offs, and cultural adaptation. Ultimately, it demonstrates that integrating XAI and RAI enables human-centric, trustworthy, and sustainable AI systems essential for the future of H&T.