Canada, like many jurisdictions in the United States, is grappling with the growing usage of facial recognition technology in the private and public sectors. This technology is being deployed at a rapid pace in airports, retail stores, social media platforms, and by law enforcement – with little oversight from the government.
To help address this challenge, I organized a tech policy case study on the regulation of facial recognition technology with Canadian members of parliament – The Honorable Greg Fergus and Matthew Green. Both sit on the House of Commons’ Standing Committee on Access to Information, Privacy, and Ethics (ETHI) Committee and I served as a legislative aide to them through the Parliamentary Internship Programme before joining CITP. Our goal for the session was to put policymakers in conversation with subject matter experts.
The core problem is that there is lack of accountability in the use of facial recognition technology that excarbates historical forms of discrimination and puts marginalized communities at risk for a wide range of harms. For instance, a recent story describes the fate of three black men who were wrongfully arrested because of being misidentified by facial recognition software. As the Canadian Civil Liberties Association argues, the police’s use of facial recognition technology, notably provided by the New York-based company, Clearview AI, “points to a larger crisis in police accountability when acquiring and using emerging surveillance tools.”
A number of academics and researchers – such as DAIR Instititute’s Timnit Gebru and the Algorithmic Justice League’s Joy Buolamwini, who documented the missclassification of darker-skinned women in a recent paper – are bringing attention to the discriminatory algorithms associated with facial recognition that have put racialized people, women, and members of the LGBTIQ community, at greater risk of false identification.
Meanwhile, Canadian officials are beginning to tackle the real world consequences of the use of facial recognition. A year ago, the Office of the Privacy Commissioner found that Clearview AI, had scraped billions of images of people from from the internet in what “represented mass surveillance and was a clear violation of the privacy rights of Canadians.”
Following that investigation, Clearview AI stopped providing services to the Canadian market, including the Royal Canadian Mounted Police. In light of these findings and the absence of dedicated legislation, the ETHI Committee began studying the uses of facial recognition technology in May 2021, and has recently resumed this work by focusing on the use by various levels of government in Canada, law enforcement agencies, and private corporations.
The CITP case study session on March 24, began with a presentation by Angelina Wang, a graduate affiliate of CITP, who provided a technical overview where she explained the different functions and harms associated with this technology. Following Wang’s presentation, I provided a regulatory overview of how U.S. lawmakers have addressed facial recognition by noting the different legislative strategies deployed for law enforcement, private, and public sector uses. We then had a substantive, free-flowing discussion with CITP researchers and the policymakers about the challenges and opportunities for different regulatory strategies.
Following CITP’s case study session, Wang and Dr. Elizabeth Anne Watkins, a CITP Fellow, were invited to testify before the ETHI committee in an April 4 hearing. Wang discussed the different tasks facial recognition technology can and cannot perform, how the models are created, why they are susceptible to adversarial attacks, and the ethical implications behind the creation of this technology. Dr. Watkins’ testimony provided an overview of the privacy, security, and safety concerns related to the private industry’s use of facial verification on workers as informed by her research. The committee is expected to report its findings by the end of May 2022.
We continue to do research on how Canada might regulate facial recognition technology and will publish those analyses in the coming months.
Are some forms of facial recognition acceptable, or is it all bad?
1:1 matching for authentication purposes, especially if carried out locally, seems less problematic.