Academic Staff

Peer-Reviewed Articles

1. Gupta, A., Bansal, J., Kwok, J., Papyshev, G. Framework for Assessment of Non-Financial Concentration Risk. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (forthcoming).
2. Oldenberg, N., Papyshev, G. The Stories We Govern By: AI, Risk, and the Power of Imaginaries. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (forthcoming). 
3. Sharma, S., Wu, X., & Papyshev, G. (2025). Capacity‐Learning Paradox: How Hong Kong and Singapore's Crisis Responses Shape and Are Shaped by Policy Capacities. Review of Policy Research.
4. Qi, R., Papyshev, G., Tsai, K., Chan, A. B., & Hsiao, J. H. (2025). Whose Values Prevail? Bias in Large Language Model Value Alignment. Proceedings of the Annual Meeting of the Cognitive Science Society.
5. Papyshev, G. (2025). Reversing the logic of generative AI alignment: a pragmatic approach for public interest. Data & Policy.
6. Chan, K. J. D., Papyshev, G., & Yarime, M. (2024). Balancing the tradeoff between regulation and innovation for artificial intelligence: An analysis of top-down command and control and bottom-up self-regulatory approaches. Technology in Society.
7. Papyshev, G., & Chan, K. J. D. (2024). Fugazi regulation for AI: strategic tolerance for ethics washing. AI & Society.
8. Huang, L. T. L., Papyshev, G., & Wong, J. K. (2024). Democratizing value alignment: from authoritarian to democratic AI ethics. AI and Ethics.
9. Papyshev, G., Migliorini, S., “Developing a Liability Framework for Harms Arising from Specification Gaming”. International Joint Conference on Artificial Intelligence 2024 Workshop on AI Governance: Alignment, Morality, and Law.
10. Papyshev, G. (2024). Situated usage of generative AI in policy education: implications for teaching, learning, and research. Journal of Asian Public Policy.
11. Papyshev, G. (2024). Governing AI through interaction: situated actions as an informal mechanism for AI regulation. AI and Ethics.
12. Wu, X., Ma, L., Low, D., Sharma, S., Papyshev, G. (2023). Beyond Precautionary Principle: Policymaking under Uncertainty and Complexity. Policy Design and Practice.
13. Papyshev, G., & Yarime, M., (2023). "The State’s Role in Governing Artificial Intelligence: Development, Control, and Promotion through National Strategies," Policy Design and Practice.
14. Papyshev, G., & Yarime, M., (2022). "The Limitation of Ethics-Based Approaches to Regulating Artificial Intelligence: Regulatory Gifting in the Context of Russia," AI & Society.
15. Papyshev, G., & Yarime, M. (2021). Exploring city digital twins as policy tools: A task-based approach to generating synthetic data on urban mobility. Data & Policy.

Book Chapters

1. Papyshev, Gleb, and Masaru Yarime, "The Challenges of Industry Self-Regulation of AI in Emerging Economies: Implications of the Case of Russia for Public Policy and Institutional Development," in Mark Findlay, Ong Li Min and Zhang Wenxi, eds., Elgar Companion to Regulating AI and Big Data in Emerging Economies, Edward Elgar, 81-98 (2023).
2. Papyshev, Gleb, Chan, Keith.  “Corporate Digital Responsibility for AI: Towards a Disclosure Framework” in Thomas Walker, Dieter Gramlich, and Akram Sadati, eds., Artificial Intelligence, Finance, and Sustainability: Examining the Ethical and Social Implications and Opportunities, Palgrave Macmillan. (2024).