We Spy with Your Little Eyes: The Privacy Risks with Eye-Gaze Data and AI

This paper investigates the privacy risks of eye-tracking technology in modern devices like the Apple Vision Pro and VR headsets. Through a carefully designed study with human participants using such headsets, the researchers demonstrate that sensitive personal attributes – particularly sexual orientation, religious beliefs and political inclinations – can be inferred from anonymized eye-gaze data using even simple AI models, achieving prediction rates up to 69%. While eye-gaze data does not directly identify individuals and may not currently qualify as “personal data” under frameworks like the EU GDPR, rapidly advancing AI capabilities will make such inferences increasingly accurate, and proactive legal and technical safeguards – including differential privacy – to protect individuals is necessary before this regulatory gap is exploited.

Daniel Seng teaches and researches on information technology law and infocommunications law. Between 2001 and 2003, he was concurrently the Director of Research, Technology Law Development Group at the Singapore Academy of Law. He graduated with firsts from NUS and Oxford, where he received the Rupert Cross Prize in 1994. He received his doctoral degree from Stanford Law School, where he used machine learning, natural language processing and big data techniques to conduct research on copyright takedown notices. While he was at Stanford, he was a non-residential fellow with the Center for Legal Infomatics (CodeX). Daniel was previously a partner and head of the technology practice at Messrs Rajah & Tann. He was amicus curiae to the Court of Appeal of Singapore in the case of Chwee Kin Keong & Ors v Digilandmall.com Pte Ltd, the leading Singapore case on unilateral mistake in the digital environment.

Moderator: Benjamin Chen, Associate Professor & Director of the Law and Technology Centre, The University of Hong Kong Faculty of Law

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