I am an Assistant Professor at the Department of Security Studies, Charles University, Prague.
I am interested in safe machine learning and the means to achieve it. Most of my works deal with inductive inference in various learning frameworks. I tend to believe that the formal study of inductive inference is important for the safety of artificial intelligence.
I collaborate with Vit Stritecky, my colleague from Charles, and John Symons from The University of Kansas. I am also a fellow at the Center for Cyber-Social Dynamics at KU.
My ORCID is 0000-0003-4199-645X.
You can contact me at petr [dot] spelda [at] fsv [dot] cuni [dot] cz
No-Regret Learning Supports Voters’ Competence, Social Epistemology (forthcoming). DOI:10.1080/02691728.2023.2252763, with Vit Stritecky and John Symons.
Expanding Observability via Human-Machine Cooperation, Axiomathes/Global Philosophy (2022). DOI:10.1007/s10516-022-09636-0, with Vit Stritecky.
Human Induction in Machine Learning: A Survey of the Nexus, ACM Computing Surveys (2021). DOI:10.1145/3444691, with Vit Stritecky.
What Can Artificial Intelligence Do for Scientific Realism?, Axiomathes/Global Philosophy (2020). DOI:10.1007/s10516-020-09480-0, with Vit Stritecky.
The Future of Human-Artificial Intelligence Nexus and its Environmental Costs, Futures (2020). DOI:10.1016/j.futures.2020.102531, with Vit Stritecky.
Machine learning, inductive reasoning, and reliability of generalisations, AI & SOCIETY (2020). DOI:10.1007/s00146-018-0860-6.
A paper on Transformers’ in-context learning
A paper on computable PAC learning
A paper on no-regret machine learning lifecycle
A paper on the lottery ticket hypothesis (about neural networks) and modern theories of inductive inference
An Analysis of the Electronic Jihad’s Activity in the Social Media Environment, Czech Journal of International Relations (2017), with Vit Stritecky.
Establishing the Complexity of the Islamic State’s Visual Propaganda, Central European Journal of International and Security Studies (2017), with Vit Stritecky.
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