Project Details
Description
With the unprecedented impact of data science and machine learning in many aspects of our daily lives, such as healthcare, finance, education, and law, there is an urgent need to design ethical statistical learning algorithms that account for fairness and privacy. This project tackles the challenge of integrating ethical principles into the fabric of statistical learning. The approach prioritizes fairness by enhancing statistical algorithms to perform equitably, particularly in scenarios with limited sample sizes and where sensitive attributes are restricted by legal or societal norms. In parallel, this project addresses privacy by developing a general framework for studying the privacy-accuracy trade-off under new privacy constraints emerging with the advances in generative AI. The practical upshot of this work is the application of these methods to biomedical fields, accompanied by the release of open-source software, broadening the impact and encouraging ethical practices in statistical learning across various domains. This project promotes equitable and private data handling and provides research training opportunities to students.The research objective of this project is to develop rigorous statistical frameworks for ethical machine learning, with a focus on algorithmic fairness and data privacy. More specifically, the project will: (1) develop innovative statistical methods that ensure fairness in a finite-sample and distribution-free manner; (2) design algorithms that ensure fairness while complying with societal and legal constraints on sensitive data; (3) establish new frameworks to elucidate the trade-off between statistical accuracy and new privacy concepts in generative AI, including machine unlearning and copyright protection. Taken together, the outcome of this research will build a firm foundation of ethical statistical learning and shed light on the development of new theoretical understanding and practical methodology with algorithmic fairness and privacy guarantees.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Status | Active |
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Effective start/end date | 7/1/24 → 6/30/29 |
Funding
- National Science Foundation: $450,000.00
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