Dr Robert Smith

Why organisations work with Robert Smith

• He is a working AI researcher with more than 100 peer-reviewed papers, not a consultant translating other people’s science. When a board asks how a model actually behaves, he can answer at the level of the maths.
• His book Rage Inside the Machine sets out a specific thesis on why algorithmic bias is structural rather than incidental. It gives leadership teams a shared vocabulary for the risk before they have to defend a hiring, credit, or pricing decision.
• He has built and deployed AI inside organisations where failure is expensive: NASA, Boeing, Airbus, the Bank of England, the UK Competition and Markets Authority. The reference points are operational, not theoretical.
• He led AI and data science at Digital Catapult, the UK government’s deep tech innovation centre. He has seen what separates the firms that move beyond pilots from the ones that stall.
• As a Founding Trustee of We and AI and a Senior Fellow at UCL, his independence on responsible AI is institutional, not positional. That matters when the audience needs a voice that does not sell the technology.

Biography highlights

• Author, Rage Inside the Machine: The Prejudice of Algorithms and How to Stop the Internet Making Bigots of Us All (Bloomsbury Business). Shortlisted, UK Business Book Awards, Specialist category.
• Former Director of AI and Data Science, Digital Catapult.
• Senior Honorary Fellow, Computer Science Faculty, University College London. Co-founder, UCL Centre for Decision-Making Uncertainty.
• Founding Trustee, We and AI.
• Author of over 100 peer-reviewed papers in artificial intelligence, with a focus on evolutionary computation, knowledge representation, and machine learning.
• Applied AI work for NASA, Boeing, Airbus, BT, the European Union, the Bank of England, the UK Competition and Markets Authority, and US national laboratories.

Biography

The history of artificial intelligence is older than most boardrooms assume, and so are the design choices that made today’s models prone to bias. That is the argument running through Robert Smith’s work as a complexity scientist, and it is the reason serious organisations book him when they need an AI conversation that holds up under scrutiny.

Smith spent more than three decades inside applied AI before the current wave of public attention. He built systems for NASA, Boeing, Airbus, BT, the Bank of England, the UK Competition and Markets Authority, the European Union, and US national laboratories at Los Alamos and Oak Ridge. He went on to lead AI and data science at Digital Catapult, the UK’s deep tech innovation centre, where the question shifted from research to deployment at scale.

His book Rage Inside the Machine, published by Bloomsbury Business and shortlisted for the UK Business Book Awards, traces algorithmic bias back through the intellectual history of computing. The case is technical, not rhetorical: apparently neutral data and models can encode prior injustice across hiring, credit, insurance, policing, and content moderation. He gives leadership audiences a way to interrogate their own systems without needing to read the code.

Smith holds a PhD, is a Fellow of the Royal Society of Arts, a Senior Honorary Fellow at UCL Computer Science where he co-founded the Centre for Decision-Making Uncertainty, and a Founding Trustee of We and AI. He has more than 100 peer-reviewed papers to his name and has presented at Google, the UK Financial Conduct Authority, and corporate, academic, and policy venues internationally.

Key speaking topics

• Artificial intelligence and generative AI
• AI ethics and responsible technology
• Algorithmic bias and governance
• Digital transformation
• Data analytics
• Future of technology
• Risk management

Ideal for

• Boards and executive committees signing off on enterprise AI strategy
• CTOs, CIOs, Chief Data Officers, and heads of AI looking for a credible external voice on governance and bias
• Risk, compliance, and regulatory leaders in financial services, insurance, healthcare, and public sector
• Senior HR and people leaders deploying AI in hiring, performance, or workforce decisions

Audience outcomes

• A clearer view of where bias actually originates inside their AI systems, with examples drawn from peer-reviewed research and operational deployments.
• A working language for board-level conversations about AI risk, beyond the vendor pitch and the headline.
• Specific questions executives can put to their data science teams and external suppliers to test whether claims about model behaviour are defensible.
• A grounded sense of where AI is genuinely creating value in regulated environments, and where it is creating exposure.
• A perspective on responsible AI that comes from a working scientist and trustee of an independent charity, not from a platform vendor.