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曹雪楠教授

曹雪楠教授

助理教授

Ph.D. (The Program of Literature) Duke University
M.Phil. (Humanities and Creative Writing) Hong Kong Baptist University
B.A. (Humanities-Communication Arts) Hong Kong Baptist University

关于 曹雪楠教授

曹雪楠於美国杜克大学毕业，现为香港中文大学文化与宗教系助理教授。曹雪楠专注研究新旧媒体的文化与社会关系，人工智能的运用及问责框架。

 

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  • 研究兴趣
    • Critical AI
    • Media Aesthetics
    • AI Accountability (Extrapolation)
    • Women Studies
    • Working-Class
    • World Literature
  • 近期研究计划
    1. “What Is ‘New?’ Evaluating GenAI Across Disciplines”
      -2024-2025, a workgroup funded by Research Institute for the Humanities

      From the project:
      How does a AI model claim novelty in its output? This is a main obstacle for developers of AI and a key question that humanities knows best how to answer. This workgroup evaluate the diversity and novelty measurement of Generative AI.

    2. Research on AI explanability and accountability, AI Extrapolation
      - 2023-4, funded by CUHK Faculty of Arts Direct Grant
      - 2024-6, funded by Hong Kong Research Grant Council, General Research Fund

      From the project:
      "Extrapolation describes how machine learning models can be clueless when encountering unfamiliar samples (i.e., samples outside a "convex hull" of their training sets). Consider a young and well-educated immigrant applying for a car loan. An automated system evaluates the loan request. Extrapolation might happen for an applicant because she is an immigrant, relatively young, and very well-educated – the model has not seen any profile of this kind. The model might not make a sound choice because the information about this applicant is not similar to the samples on which the model has been trained. Having a loan officer look over the model's decision would be reasonable. But in the use of AI systems, this common-sense approach is somehow lost, and so far, there is no requirement for AI models to report when they are clueless. How should we measure, classify, and make transparent the extent of AI cluelessness?"
      –"Clueless AI: Should AI Models Report to Us When They Are Clueless?" Montreal AI Ethics. May 19, 2022.

    3. "Monograph-in-progress on media improvisations and informational loss in China, Thriving on Deficits: Aesthetics of Inconspicuous Media Improvisations in China. 

      From the project:
      "Suppose, in a given historical period, the reader-critic of media was a schooled, but by no means erudite, working person of an ordinary household, not, in other words, trained by any disciplinary methodology. How would her experience differ in interacting with print objects and bits of digital information? …In contrast to the oft-celebrated theories of agency, identity, and connectivity crafted for university classrooms, her concerns—modest, often practical, and sometimes irrational and incoherent—can fetch enormous sympathy from people of lesser social standing. Such concerns have rarely been verified: they are felt but not uttered, or uttered in the circumstances not recorded, or recorded yet deemed irrelevant because of their location outside disciplinary and disciplined research…As a result, this reader-critic moves between the conventional categories such as propaganda, literature, and reporting, unbound to any." 
  • 其他
    1. Yale University, Postdoc at MacMillan Center of International and Area Studies
    2. Duke University, Fellow at Brain Cultures Lab
    3. The Chinese University of Hong Kong, Faculty of Arts Outstanding Teaching Award 2023