Operationalizing Responsible AI

Nyhet

Häftad, Engelska, 2026

429 kr

Kommande

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.

Produktinformation

Utgivningsdatum2026-08-31
FormatHäftad
SpråkEngelska
FörlagCambridge University Press
ISBN9781009625197

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Daniele Quercia is Director of Responsible AI at Nokia Bell Labs Cambridge, United Kingdom and Professor at Politecnico di Torino, Italy. Named one of Fortune's Data All-Stars, he has spoken at TED and published widely on urban computing and Responsible AI after research roles at Yahoo Labs, Cambridge, and MIT. Marios Constantinides is a Senior Research Scientist at CYENS Centre of Excellence, Cyprus and Honorary Lecturer at University College London, United Kingdom. His research on Human-Computer Interaction and Responsible AI has received international recognition, with publications in top venues and press coverage.

Preface; 1. Can AI be Fair? Yi-Chieh Lee, Jingshu Li, Renwen Zhang and Nan Liu; 2. Can AI be Explainable? Simone Stumpf; 3. Can AI be Psychologically Safe? Uthman Ali; 4. Can AI be Accountable? Andrew L. Kun; 5. Can AI be Consentful? Giada Pistilli and Bruna Selin Trevelin; 6. Can AI be Transparent? Fabian Linde, Dalia Ali and Orestis Papakyriakopoulos; 7. Can AI be Auditable? Himanshu Verma, Kirtan Shyamal Padh and Eva Thelisson; 8. Can AI be Contextualized? Glen Berman and James Smithies; Index.