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黃大倫教授

黃大倫教授

校長特聘助理教授

Ph.D. History and Philosophy of Science, University of Sydney
M.A. Philosophy, University of California, Riverside
M.S. Cognitive Neuroscience, National Yang Ming University

關於 黃大倫教授

Linus HUANG is a philosopher of cognitive science, technology, and artificial intelligence. He received his Ph.D. in History and Philosophy of Science from the University of Sydney and was a 2024 StarTrack Scholar at the Social Computing Lab, Microsoft Research Asia. His research explores issues in AI ethics and philosophy of cognitive science through the lens of embodied cognition, drawing on resources from philosophy, cognitive neuroscience, and computational science. He investigates methods for reducing bias in humans and AI, aligning AI with human values in a multicultural world, and the implications of computational neuroscience for understanding the human mind. Linus is co-author of Philosophy of Neuroscience (Cambridge University Press, 2022) with William Bechtel.

 

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  • Research Interests
    • AI Ethics
    • Philosophy of Cognitive Science
    • Human-AI Interaction
    • Implicit Bias
    • Algorithmic Bias
    • Value Alignment
    • Cultural Hegemony
    • Embodied Cognition
    • Gender Studies
  • Recent Research ProjectS
    • 2023-2025  Principal Investigator, Engineering Equity: How AI Can Help Reduce the Harm of Implicit Bias, RGC GRF.
  • Representative Publications
    Books
    • 2022    Bechtel, W., & Huang, L. T. Philosophy of Neuroscience. Cambridge: Cambridge University Press.
    Journal Articles
    1. 2025    Huang, L. T., Huang, T.-R. Generative Bias: Widespread, Unexpected, and Uninterpretable Biases in Generative Models and Their Implications. AI & Society.
    2. 2025    Sechman, M., & Huang, L. T. Towards a Mechanistic Account of Embodied Implicit Bias: Heterarchical Control Network and Its Implications for Intervention. Topoi: An International Review of Philosophy.
    3. 2024    Huang, L. T., Papyshev, G, & Wong, J. Democratizing Value Alignment: From Authoritarian to Democratic AI Ethics. AI and Ethics.           
    4. 2022    Huang, L. T., Chen, H.-Y., Lin, Y.-T., Huang, T.-R., Hung, T.-W. Ameliorating Algorithmic Bias, or Why Explainable AI Needs Feminist Philosophy. Feminist Philosophy Quarterly.
    5. 2021    Chen, H.-Y., Yu, L.-A., & Huang, L. T. To Mask or Not to Mask: Epistemic Injustice in the COVID-19 Pandemics. Techné: Research in Philosophy and Technology. 
    6. 2021    Huang, L. T. More Dynamical and More Symbiotic: Cortico-Striatal Models of Resolve, Suppression, and Routine Habit. Behavioral and Brain Sciences.
    7. 2021    Huang, L. T., Bich, L, & Bechtel, W. Model Organisms for Studying Decision-Making: A Phylogenetically Expanded Perspective. Philosophy of Science.
    8. 2021    Huang, L. T. Can massive modularity explain human intelligence? Information control problem and implications for cognitive architecture. Synthese.
    9. 2020    Lin, Y.-T., Hung, T.-W., & Huang, L. T. Engineering Equity: How AI Can Help Reduce the Harm of Implicit Bias. Philosophy & Technology.  
    10. 2020    Carruthers, G., Carls-Diamante, S., Huang L. T., Rosen, M., & Schier, E. How to operationalise consciousness. Australian Journal of Psychology, 71(4), 390-410.
    11. 2018    Schwitzgebel, E., Huang, L. T., Higgins, A., & Gonzalez-Cabrera, I. The insularity of Anglophone philosophy. Philosophical Papers, 47(1), 21-48.
    12. 2012    Schwitzgebel, E., Rust, J., Huang, L. T., Moore, A. T., & Coates, J. Ethicists’ courtesy at philosophy conferences. Philosophical Psychology, 25(3), 331–340.
  • OTHER PROJECTS, ACHIEVEMENTS, AND/OR AWARDS
    1. 2024    StarTrack Scholars Fellowship, Microsoft Research Asia
    2. 2021    Short-Term Research Fellowship, Alexander von Humboldt Institute for Internet and Society