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PAT-AI: Privacy-Aware Transparency for AI in Singapore

Assistant Professor Yair Zick

National University of Singapore

Project Description

Recent years have seen an increasing push to make black-box algorithmic systems more transparent to various stakeholders. However, making systems more transparent runs the risk of making them more exposed to information leaks, e.g. private user information can be inferred via transparency reports. In this project we study how one might mitigate the effects of such leaks, and design novel transparency measures that are resistant to adversarial inference attacks.

Research Technical Areas

Game theory and economic paradigms

Machine learning

Privacy & transparency

Benefits to the society

AI Singapore and similar initiatives will potentially result in the widespread implementation of AI decision makers in high-stakes domains. Their decisions must be explained to stakeholders in a reasonable manner, while maintaining sufficient privacy guarantees for those users who might interact with the system. Our objective is to study this phenomenon, with the hope of ensuring the safe, transparent use of data and AI in the Singaporean context.

Team's Principal Investigator

Assistant Professor Yair Zick
School of Computing
National University of Singapore

Link to Profile

Principal Investigator’s Core Research Technical Areas

  • Game theory and economic paradigms
  • Machine learning
  • Security and privacy

Introduction of the Principal Investigator

Yair Zick is an assistant professor at the Department of Computer Science at the National University of Singapore. He obtained his PhD (mathematics) from Nanyang Technological University, Singapore in 2014, and a B.Sc (mathematics, “Amirim” honors program) from the Hebrew University of Jerusalem. His research interests include computational fair division, computational social choice, algorithmic game theory and algorithmic transparency. He is the recipient of the 2011 AAMAS Best Student Paper award, the 2014 Victor Lesser IFAAMAS Distinguished Dissertation award, the 2016 ACM EC Best Paper award, and the 2016 Singapore NRF Fellowship.

Recent Notable Awards

  • The 2017 NRF Fellowship (2017)
  • The ACM EC Best Paper Award (2016)
  • The IFAAMAS Victor Lesser Distinguished Dissertation Award (2014)

Team

Co-Principal Investigator

Asst. Prof. Reza Shokri

National University of Singapore

Research Areas:

  1. Machine learning
  2. Privacy
  3. Robustness
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