The federal government quietly tested facial recognition technology on millions of unsuspecting travellers at Toronto’s Pearson International Airport in 2016. The six-month initiative, meant to pick out people the Canada Border Services Agency suspected might try to enter the country using fake identification, is detailed in a document obtained by The Globe and Mail through a freedom of information request. The project is the largest known government deployment of the technology in Canada to date. (Globe and Mail)
Here are some experts from McGill University that can provide comment on this issue:
Ignacio Cofone, Assistant Professor and Norton Rose Fulbright Faculty Scholar, Faculty of Law
“Facial recognition is inescapable, invisible, and ubiquitous, making it the most invasive surveillance mechanism ever invented. Although airports are already high-surveillance spaces where people should have low expectations of privacy, implementing facial recognition implies a significant departure from current practices. It should only be implemented if there is a certainty that a significant security payoff exists to compensate for its risks, and that the measure is not simply part of a security theater.”
Ignacio Cofone is an Assistant Professor in the Faculty of Law, where he teaches artificial intelligence law, business associations and privacy law. His research explores how the law should adapt to technological and social change with a focus on privacy and algorithmic decision-making. In his latest projects, he proposes how to evaluate harm in privacy class actions and how to prevent algorithmic discrimination.
ignacio.cofone [at] mcgill.ca (English, Spanish)
Benjamin Fung, Full Professor, School of Information Studies
“The question here is how to achieve a balance between national security and personal privacy. One should ask what additional information the CBSA can get via this new artificial intelligence program compared to the traditional immigration and customs procedure. It is important to note that the CBSA keeps an entry record of every visitor and has access to pictures of some visitors even without the facial recognition system. Thus, the only piece of new information that the CBSA can get from this system is the live facial pictures of travelers. If the CBSA only uses the pictures for a specific purpose and then permanently discards the pictures within a short period of time, then the privacy risk is low. This could be a good balance between national security and personal privacy.”
Benjamin Fung is a Full Professor in the School of Information Studies and holds the Canada Research Chair in Data Mining for Cybersecurity. He has over 90 refereed publications that span the research areas of data mining, privacy protection, cyberforensics, services computing, and building engineering.
ben.fung [at] mcgill.ca (English)
Sonja Solomun, PhD candidate, Department of Art History & Communications and Research Director, Centre for Media, Technology and Democracy
“Facial recognition seduces governments into deploying a technology that has been repeatedly proven to discriminate and into believing that national security is a worthwhile tradeoff for individual privacy. This misses the mark: the deployment of facial recognition in public is a collective harm because it exacerbates the power imbalance between those deploying it and those most vulnerable to its use. These are fundamental threats to democracy.”
Sonja Solomun is a PhD candidate in the Department of Art History & Communications Studies and serves as the Research Director of the Centre for Media, Technology and Democracy at the Max Bell School of Public Policy. Her work focuses on the histories and politics of platforms, platform governance, and most recently, climate justice and artificial intelligence.
sonja.solomun [at] mcgill.ca (English)