Research areas


David Leslie is the Ethics Fellow within the public policy programme. He was a 2017-2018 Mellon-Sawyer Fellow in Technology and the Humanities at Boston University, where he concentrated on the ethics and politics of emerging media and computationally based innovation as well as on issues of accountability, explainability, transparency, and stakeholder participation in the governance of machine learning research and innovation.

He has also recently been appointed as a Fellow at MIT’s Dalai Lama Center for Ethics and Transformative Values. He has previously taught at Princeton’s University Center for Human Values (UCHV), where he also participated in the UCHV's 2017-2018 research collaboration with Princeton's Center for Information Technology Policy on "Technology Ethics, Political Philosophy and Human Values: Ethical Dilemmas in AI Governance."

Prior to teaching at Princeton, David held academic appointments at Yale’s programme in Ethics, Politics and Economics and at Harvard’s Committee on Degrees in Social Studies, where he received over a dozen teaching awards including the 2014 Stanley Hoffman Prize for Teaching Excellence. After receiving a Bachelor’s Degree from the University of Pennsylvania and an MPhil in Political Thought and Intellectual History from Cambridge University, he received his PhD from Yale.

His recent paper, “Machine Intelligence and the Ethical Grammar of Computability,” which explores the relationship of Alan Turing’s monumental work on combinatorial logic to his later thoughts on AI, was published in Springer-Verlag’s Synthese Library Series in the Philosophy of Science in a 2016 volume entitled, Fundamental Issues of Artificial Intelligence.

David’s recent and upcoming invited lectures, talks, and public appearances include:

  • ‘A Framework for Process Transparency in the Use of Automated Decision-Making Systems,’ STIS Guest Speaker Series Seminar, University of Edinburgh, 2019
  • ‘Building a Responsible Data Innovation Ecosystem from the Cultural Ground Up,’ Keynote Address to the Insurance Supper Club, UK, 2019
  • ‘The Co-Evolution of Exploitation and Power In an Age of Algorithmic Ubiquity,’ Panel Chair, Data Power Conference, Bremen University, Germany, 2019 
  • ‘The Fifth Face of Power: A Critique of Algorithmic Violence,’ Data Power Conference, Bremen University, Germany, 2019
  • ‘Self-Sovereign Identification as a Tool for Digital Identity Rights: Towards Empowering Individuals Online,’ (with Christina Hitrova), Data Power Conference, Bremen University, Germany, 2019
  • Expert Roundtable, Technology and Artificial Intelligence Commission (Sue Black OBE FBCS FRSA, Chair), Liberal Democrats, Parliament 2019 
  • ‘Critical Thresholds in the Prediction Society: New Frontiers in Data Ethics,’ ICO, Data Protection Practitioners Conference, 2019
  • ‘Project ExplAIn,” Panel Chair, ICO, Data Protection Practitioners Conference, 2019
  • ‘Alan Turing as Teacher: How Turing Taught Us to Count,’ Cambridge University, EiM2, Conference on Ethics and Mathematics, 2019
  • ‘Are We at a Tipping Point?,’ Oxford University Conference on AI and the Law, 2019
  • ‘Mapping Explainability: An Actionable Taxonomy for Explanable AI,’ ICO/Turing Institute Roundtable on Project ExplAIn, 2019
  • ‘Driving Responsible Innovation in a Complex Data Ecosystem,’ Biometrics and Forensics Ethics Group/Home Office Panel, 2019
  • Alan Turing, Greatest Person of the 20th Century, Radio Interviews: BBC Scotland; BBC Cornwall; BBC Oxford; BBC Coventry and Warwickshire; BBC Cambridge; BBC Solent; BBC Cumbria; BBC Three Counties, 2019
  • ‘Artificial Intelligence as a Global Public Utility and Gatekeeper Technology,’ The Alan Turing Institute, Data Ethics NHS Advisory Sub-Group, 2019
  • ‘De-automating the Crowd: Contesting the Degradation of Labour in a Microwork World,’ The Alan Turing Institute Workshop, Automating the Crowd: Who is the real Mechanical Turk?,’ 2019
  • ‘From Black Box to Bottleneck and Back Again: Principles-Based Regulation in the Age of Machine Learning,’ Financial Conduct Authority/IOSCO Workshop on AI and Ethics, 2018

Research interests

David's current research focuses on digital ethics, algorithmic accountability, explainability, and the social and ethical impacts of machine learning and data-driven innovations. In his wider research, David studies the moral and ethical implications of emerging technologies. In particular, he is keen to question how the biospherically and geohistorically ramifying scope of contemporary scientific innovation (in areas ranging from AI and synthetic biology to nanotechnology and geoengineering) is putting pressure on the conventional action-orienting categories and norms by which humans, at present, regulate their behaviour.