Balancing Privacy and Trust: Prof. Jake Lee Explores Example-Based Learning in AI

On November 21st, 2024, Prof. Jake Lee, an assistant professor of the Department of Computer Science and School of Data Science, presented his seminar “Balancing Privacy and Trust in Example-Based Learning” at UNC Charlotte as part of the Center for TAIMing AI’s seminar series. In this seminar, Prof. Lee addressed the balance between privacy preservation and trustworthiness in example-based learning.

As AI technologies advance, there is a growing need for trustworthiness, specifically building AI while addressing safety, explainability, privacy, and fairness. Prof. Lee’s presentation examined example-based learning—a method where models learn from specific instances or cases rather than generalized rules—as an approach for AI applications. This approach not only enhances the explainability and efficiency of AI systems but also poses unique challenges related to privacy, specifically the risk of data misuse and the importance of robust privacy safeguards.

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