The Research
Focus
This research project empirically tested what Canadians deem acceptable in the context of FRT applications used by private sector actors, focusing on attitudes towards, preferences with respect to, hopes for, and concerns about the use of FRT, as well as the policy-relevant aspects of their acceptance of FRT use by private sector actors.
The central research question is: what factors predict support for the use of FRT by private sector actors?
The findings from this research have implications for the adoption of FRT by the private sector and for the development of governing legislation and the regulation of its use.
Scoping Review
The scoping review identifies and synthesizes the state of knowledge surrounding the question of public perceptions of private sector use of facial recognition technology (FRT) following a scoping review methodology. Drawing on research literature published since 2002, primarily focused on the private sector but incorporating cross-sectoral insights where relevant, we identify how public perceptions of private sector use of FRT have been investigated and understood.
Survey
This document reports on the results of a survey of 2828 Canadian residents, from all provinces and in both official languages, focused on public perceptions of emerging uses of FRT in private sector settings. After preliminary demographic questions including gender, age, race, province and community type, citizenship, education, and income, respondents were asked for their perspective on six FRT implementation scenarios (workplace security, airline boarding, unlocking a smartphone, banking, hotel access, and work-from-home monitoring) and for their response to 29 statements related to a hypothetical FRT banking application. The central results from this survey are that consumers will adopt systems that are easy to understand and use, and that integrate well with their current technology. If their friends and family adopt these systems, if they trust their bank, and feel such systems make for a better banking experience, they will also be more likely to adopt them. However, if they feel FRT technology puts them or their money at risk, they will reject its use. To analyze the survey data, structural equation modelling will be used. Structural equation modelling is a method for representing, estimating, and testing a network of relationships between variables that allows for the simultaneous estimation of all hypothesized relationships. It is an appropriate and valuable technique in the current context of acceptance of a new technology such as FRT. Data analysis activities such as variable grouping and respondent grouping will also be conducted. The independent variables (e.g., age, gender, income, education, etc.) will be analyzed against support for and acceptance of private sector use of FRT.
Summary
This document synthesizes the results from the scoping review and survey, and places this research in the broader context of FRT, private sector applications, and public perceptions.
Other Outputs
"Knowledge translation" (KT) activities serve to make the outputs from this project, and their implications, accessible to a wider audience. The KT outputs include:
General interest articles
Both of these draft articles are pending publication.
Public Presentations
- ITLP: (delivered January 25 2023 at UCLA). See: ITLP Tech Talk January 25 2023 - Creeping Normality (text) and ITLP Tech Talk January 25 2023 - Creeping Normality (slides)
- Continuing Ed: (delivered March 2 2023 at the University of Regina). See Facial recognition technology: Should you be concerned? (slides)
- CSIP: (delivered March 31 2023 at the University of Regina). See The creeping normality of facial recognition technology (slides)
Executive Education Workshop Curriculum
Project Team
Justin Longo PhD
Associate Professor, Johnson Shoyama School of Public Policy, University of Regina
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Justin Longo (@giustinolongo) is an Associate Professor at the Johnson Shoyama Graduate School of Public Policy at the University of Regina, and a former Research Chair in Digital Governance. He has a PhD in public policy and public administration from the University of Victoria (2013) where he researched the use of enterprise social collaboration platforms inside government policy analysis settings. Following postdoctoral work in open governance at the Gov Lab@NYU and Arizona State University, his current research focuses on the social, organizational, and political implications of advancing technology. From the impact of the “sharing economy” on social and governance arrangements to the unanticipated consequences of policy analytics, new ways of organizing work, and the evolving relationship between citizens and the state, the profound changes of the digital era provide the foundation for considering the trajectory of our shared future.
Temofe Isaac Akaba
Research Associate and PhD Candidate, Digital Governance Lab, Johnson Shoyama Graduate School of Public Policy
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Temofe Isaac Akaba is a Research Associate and PhD Candidate at the Digital Governance Lab, Johnson Shoyama Graduate School of Public Policy. He holds a master’s degree in E-Governance Technologies and Services from Tallinn University of Technology (Estonia), and a bachelor’s degree in Business Administration from the University of Benin (Nigeria). Temofe’s current research is focused on exploring the adoption and implementation of service design in Canada’s public sector. He’s generally interested in research relating to Innovative technology adoption and implementation within the Public Sector.
Yasmine Wafa
PhD Student, Johnson Shoyama Graduate School of Public Policy
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Yasmine Wafa is a PhD Student in JSGS. She is a deputy director at CCR2P – R2P & Women’s Rights division. She is also passionate about sustainability and has spent 2020 volunteering as a senior SDG Coordinator with the UN. Her research interests focus on teleworking, digitalization, and big data.
Mehrdad Safaei
Data and Artificial Intelligence Program Analyst, Digital Academy, Canada School of Public Service, Government of Canada
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Mehrdad Safaei is a Data and Artificial Intelligence Program Analyst at Digital Academy, Canada School of Public Service, Government of Canada. He is also a research assistant at Simon Fraser University. His recent researches include tweeter sentiment analysis for “Attributions of Blame and Credit in Policy-Making” and using NLP algorithms to generate briefing notes “The end of the policy analyst? Investigating the capability of artificial intelligence to generate plausible, persuasive, and useful policy analysis”.
Prince Anim
Graduate Research Associate, Digital Governance Lab
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Prince Anim is a Graduate Research Associate in the Digital Governance Lab and holds a Master of Public Policy degree from JSGS. Before joining JSGS, Prince cofounded TransGov — Ghana’s first digital public engagement platform for engaging the public and monitoring developmental projects. He also worked as an Executive Intern at the Digital Strategy and Operations Department of the Government of Saskatchewan. He is interested in government’s use of technology to support the quality of life of its people.
Tanushree Das
MPP candidate, Johnson Shoyama Graduate School of Public Policy
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Tanushree Das, a development practitioner from Bangladesh with an academic background in Information Technology, is an MPP candidate at JSGS. She has a bachelor’s degree in IT from Gujarat Technological University (India), earned under an ICCR scholarship. After working as a deputy manager (Microfinance) of BRAC, Bangladesh, she joins JSGS aiming to gain a deeper understanding of the inclusion of marginalized and excluded populations’ interests in the policy formulation process. Her research interests focus on the use of technology in social and governmental interventions and inclusive organizational development.