Professor of Robot Ethics, University of the West of England (UWE Bristol). Co-Founder, Bristol Robotics Laboratory. Chair, IEEE Standards Working Group P7001 (Transparency of Autonomous Systems). Member, World Economic Forum Global Future Council on Robotics and AI.
Alan Winfield is Professor of Robot Ethics at the University of the West of England (UWE Bristol) and a co-founder of the Bristol Robotics Laboratory, one of Europe's largest robotics research centers. He is internationally recognized for pioneering contributions to ethical robotics and the development of standards for transparency and accountability in AI. He chaired the IEEE Standards Working Group P7001, responsible for drafting the world's first standard on Transparency of Autonomous Systems.
His research focuses on the "Ethical Black Box," a specialized data recorder designed to make autonomous systems legally accountable and auditable after accidents. He served as a member of the UK's Advisory Board on AI and Robotics, contributed to the UK Parliament's reports on AI and ethics, and has been a leading voice at UNESCO, IEEE, and the European Commission in shaping global frameworks for trustworthy AI. He is the author of "Robotics: A Very Short Introduction" (Oxford University Press).
Winfield opened with the question regulators, customers, and courts are increasingly asking: when something goes wrong with an autonomous system, how do you prove what happened and why? His answer was the Ethical Black Box, an analogy to aviation's flight data recorder. Just as the NTSB reconstructs an aircraft accident from objective records, AI systems need a dedicated forensic layer that captures inputs, internal decisions, outputs, and context, stored in a tamper-resistant form that investigators can actually use.
The masterclass worked through the IEEE 7001 standard on Transparency of Autonomous Systems, explaining what "transparency" means at each stakeholder level: engineers need to trace decision chains; users need understandable explanations; regulators need audit-ready logs; and courts need records that can withstand adversarial challenge. Winfield distinguished this from the vague "explainability" that many systems claim, pointing out that a log file is only useful if investigators have the right tools and training to read it.
He ended with a practical implementation roadmap and an urgent policy ask: we need an AI Accident Investigation Bureau, an empowered independent body with subpoena power, analogous to aviation or rail safety agencies. Without it, even the best logging standards will go unused when something goes wrong. The three things participants left with: what to capture and why, how to align design with BS 8611 ethical guidance and IEEE 7001, and how to pilot accountability fast enough to matter before the next serious incident.
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