How can we build and govern trustworthy AI? Operationalizing Responsible AI brings together leading scholars and practitioners to address this urgent question. Each chapter explores a key dimension of responsibility - fairness, explainability, psychological safety, accountability, consent, transparency, auditability, and contextualization – defining what it means, why it matters, and how it can be achieved in practice. Through interdisciplinary perspectives and real-world examples, the book bridges ethical principles, legal frameworks such as the EU AI Act, and technical approaches including explainable AI and audit methodologies. Written for researchers, policymakers, and professionals, the book offers both conceptual clarity and practical guidance for advancing Responsible AI that is fair, transparent, and aligned with human values.
‘Operationalizing Responsible AI is one of the first books to offer both comprehensive coverage and an accessible entry point into the most important questions surrounding what it truly means to build responsible AI. As these challenges grow more urgent by the day, this book is an essential guide for anyone serious about developing or shaping AI technologies that could bring benefits and minimize harms to people and society.’
Q. Vera Liao - University of Michigan
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