Artur Ziganshin
Master of Philosophy · PhD of Philosophy
Research Interests
My research investigates the epistemic and ethical foundations of artificial intelligence, focusing on three interconnected questions: What conditions must AI systems satisfy to produce genuine knowledge? How should ethical constraints be integrated into AI architecture? And how do we preserve meaningful human agency in the face of increasing automation?
Education
PhD of Philosophy
Master of Philosophy (MPhil)
Research Areas
Epistemology of AI — process reliabilism, epistemic risk, machine testimony
Philosophy of Language & AI — meaning, reference, semantic grounding
AI Ethics — human dignity, fairness, consent, autonomy
Philosophy of Mind & AI — consciousness, understanding, agency
Political Philosophy of AI — governance, regulation, democratic oversight
Publications
All papers available as open-access preprints on PhilArchive.
Ziganshin, A. (2025). "Epistemic Risk Surfaces in Large Language Models." PhilArchive preprint.
Ziganshin, A. (2025). "The Grounding Problem in Neural Language Models." PhilArchive preprint.
Ziganshin, A. (2025). "Ethical Architecture: Design Principles for Normative AI." PhilArchive preprint.
Ziganshin, A. (2025). "Human Dignity and Automated Decision-Making." PhilArchive preprint.
Ziganshin, A. (2025). "Process Reliabilism and Machine Testimony." PhilArchive preprint.
Ziganshin, A. (2025). "The Chinese Room Revisited: LLMs and Understanding." PhilArchive preprint.
Ziganshin, A. (2025). "Democratic Oversight of AI Systems." PhilArchive preprint.
Skills & Languages
Languages: Russian (native), English (professional proficiency)
Technical: Python, data analysis, LLM evaluation, LaTeX
Research tools: Zotero, PhilPapers, PhilArchive, arXiv
Professional Activities
Independent AI philosophy researcher
Founder, Kazan Philosophical Society
Author, The Epistemic Mirror (weekly newsletter)