Trustworthy AI

Ethical Frameworks for Responsible Innovation

Inbunden, Engelska, 2026

589 kr

Kommande

Beskrivning

Artificial intelligence is reshaping decisions that affect people, institutions, and societies. Understanding how to design, deploy, and govern AI systems that can be trusted is now essential in many disciplines. This book offers a clear, concise introduction to trustworthy AI, treating AI not just as a technical artifact but as a socio-technical system embedded in human contexts. Developed from an internationally applicable educational framework, the book is designed for teaching and learning in computer science, data science, law, policy, business, and related fields. It equips students and professionals with the concepts and judgment needed to engage critically and responsibly with AI in practice. Combining ethics, governance, and practical insight, the book explains key concepts including transparency, fairness, accountability, human oversight, and stakeholder participation. An interdisciplinary approach makes the material accessible to both technical and non-technical audiences, with realistic scenarios and reflection questions so readers connect principles to real-world AI applications.

Produktinformation

Utgivningsdatum:2026-09-30
Format:Inbunden
Språk:Engelska
Antal sidor:154
Förlag:Cambridge University Press
ISBN:9781009492867

Utforska kategorier

Mer om författaren

Andrea Aler Tubella is a researcher specializing in Responsible Artificial Intelligence, logic, and the societal impact of technology. Dr. Aler Tubella's research is grounded in the intersection of formal logic and AI ethics. Her research includes design, impact and education around AI with a particular interest in multidisciplinary perspectives, and how collaboration and insights from various disciplines can inform and improve the impacts of intelligent systems. Virginia Dignum is Professor of Responsible Artificial Intelligence at Umeå University, Sweden. She is a leading voice in global AI policy, chairing the ACM Technology Policy Council, co-chairing the IEEE Global Initiative on the Ethics of Autonomous Systems, and advising the Wallenberg Foundations in Sweden. She is a member of expert groups at UNESCO, OECD, and was part of the EU's High-Level Expert Group on AI, the UN's High Level Advisory Body on AI, and World Economic Forum Global Future Council on Artificial Intelligence. Marçal Mora-Cantallops is Professor in the Computer Science Department at the University of Alcalá. As a researcher, he focuses on machine learning, social network analysis, data science, ethical AI, and game studies, having authored and published multiple related articles in the past few years. He also coordinated the Trustworthy AI Erasmus+ project. Juan Carlos Nieves is Associate Professor at Umeå University, where he teaches and directs the Master's Programme in Artificial Intelligence. He has substantial experience bridging theoretical perspectives on Trustworthy AI with real world industrial practices, reflecting his focus on socially aware and ethically grounded intelligent systems. He has served as an external ethical advisor and reviewer for EU projects and as an expert evaluator for various European national research councils. Andreas Theodorou's work focuses on the techniques and tools needed for the design, implementation, and deployment of intelligent autonomous systems such as to ensure their trustworthiness. Prior to his move to industry, Dr. Theodorou held teaching and research positions at multiple institutions, including Universitat Politècnica de Catalunya·BarcelonaTech (Spain), Umeå University (Sweden), and University of Bath (UK).

Innehållsförteckning

1. What is trustworthy AI?; 2. Ethics and philosophy; 3. AI narratives; 4. Your role (as a professional, as an individual); 5. AI governance; 6. Harms; 7. Transparency and explainability; 8. Fairness and bias; 9. Accountability and responsibility; 10. Social and environmental well-being; 11. Stakeholder participation; 12. Human-AI interaction: digital companions; 13. Engineering processes/tools; 14. Control frameworks; 15. Data governance; 16. Assessment tools.