My research focuses on what we can do today to ensure that developments in AI are safe and beneficial in the long-term.

Selected publications:

• Whittlestone J., and Clarke, S. (forthcoming). AI Challenges for Society and Ethics. Forthcoming in the Oxford Handbook of AI Governance, Oxford University Press.

• Gruetzemacher, R. and Whittlestone, J. (2021). The Transformative Potential of Artificial Intelligence. Futures.

• Whittlestone, J., and Clark, J. (2021). Why and How Governments Should Monitor AI Development. https://arxiv.org/pdf/2108.12427.pdf

• Cave, S., Whittlestone, J., Nyrup, R., O hEigeartaigh, S. S., and Calvo, R. (2021). The Ethics of Using AI in Pandemic Management. Forthcoming in a BMJ and WHO Special Issue on AI and COVID-19.

• Whittlestone, J., Crosby, M. and Arulkumaran, K. (2021). The Societal Implications of Advances in Deep Reinforcement Learning. Journal of Artificial Intelligence Research, 70, 1003-1030

• Cremer, C. Z., & Whittlestone, J. (2021). Artificial Canaries: Early Warning Signs for Anticipatory and Democratic Governance of AI. International Journal Of Interactive Multimedia And Artificial Intelligence, 6 (Special Issue on Artificial Intelligence, Paving the Way to the Future), 100-109. http://doi.org/10.9781/ijimai.2021.02.011

• Cremer, C. Z., and Whittlestone, J. (2020). Canaries in Technology Mines: Warning Signs of Transformative Progress in AI. Evaluating Progress in AI Workshop, ECAI 2020 (Won Best Paper Award)

• Tzachor, A., Whittlestone, J., Sundaram, L., and O hEigeartaigh, S. S. (2020). AI in a crisis needs ethics with urgency. Nature Machine Intelligence.

• Hernandez-Orallo, J., Martinez-Plumed, F., Avin, S., Whittlestone, J. and O hEigeartaigh, S. S. (2020). AI Paradigms and AI Safety: Mapping Artefacts and Techniques to Safety Issues. 24th European Conference on Artificial Intelligence (ECAI 2020)

• O hEigeartaigh, S. S., Whittlestone, J., Yang, L., Zeng, Y. and Zhe, L. (2020). Overcoming Barriers to Cross-Cultural Cooperation in AI Ethics and Governance. Philosophy and Technology.

• Prunkl, C. and Whittlestone, J. (2020). Beyond Near- and Long-Term: Towards a Clearer Account of Research Priorities in AI Ethics and Society. Forthcoming in Proceedings of the 2020 AAAI/ACM Conference on AI, Ethics, and Society.

• Gruetzemacher, R. and Whittlestone, J. (2019). Defining and Unpacking Transformative AI. arXiv preprint.

• Whittlestone, J. and Ovadya, A. (2019). The tension between openness and prudence in responsible AI research. NeurIPS 2019 Joint Workshop on AI for Social Good.

• Ovadya, A. and Whittlestone, J. (2019). Reducing malicious use of synthetic media research: considerations and potential release practices for machine learning. arXiv preprint.

• Nyrup, R., Whittlestone, J. and Cave, S. (2019). Why Value Judgements Should Not Be Automated. Evidence submitted to the Committee on Standards in Public Life.

• Whittlestone, J. Vold, K. and Alexandrova, A. (2019). The potential harms of online targeting. Evidence submitted to the UK Centre for Data Ethics and Innovation.

• Whittlestone, J. and Vold, K. (2019). Privacy, autonomy and personalised targeting: rethinking how personal data is used. IE Report on Data, Privacy and the Individual.

• Whittlestone, J. Nyrup, R. Alexandrova, A. and Cave, S. (2019). The role and limits of principles in AI ethics: towards a focus on tensions. Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society.

• Whittlestone, J. Nyrup, R. Alexandrova, A. Dihal, K. Cave, S. (2019). Ethical and societal implications

  of algorithms, data, and artificial intelligence: a roadmap for research. London: Nuffield Foundation.

• Vold, K., Whittlestone, J., Bahanda, A., and Cave, S. (2018). The ethics of AI and data-driven targeting. Report commissioned by the UK Government’s new Centre for Data Ethics and Innovation.