Epistemic Responsibility in Generative AI
An examination of how knowledge synthesis in LLMs challenges traditional notions of authorship, verification, and intellectual accountability in academic publishing.
About & Research Focus
Prof. Chen's work bridges the gap between natural language processing and philosophical epistemology. He investigates how machine learning models construct, verify, and propagate knowledge, with a particular focus on bias mitigation and interpretability in large language models.
Currently directing the Oxford Digital Knowledge Lab, he oversees cross-disciplinary research into automated fact-checking, semantic knowledge representation, and ethical AI deployment in educational platforms.
Areas of Expertise
Featured Contributions
Semantic Drift in Multilingual Knowledge Graphs
How cultural and linguistic context shifts meaning across translation layers, and strategies for preserving conceptual integrity in global encyclopedias.
The Architecture of Trust: Verifying AI-Generated Citations
Proposed frameworks for real-time source validation and traceability in automated research assistants and educational tools.
Beyond Bias: Structural Fairness in Algorithmic Curation
Moving past surface-level diversity metrics to address systemic representation gaps in knowledge organization and retrieval systems.