Hilary Evans Cameron

Faculty

Refugee Credibility

Which Assumptions Underlie Adjudicators’ Conclusions that Refugee Claimants are Lying? A Canadian case study SSHRC 2021-24.

Hilary Evans Cameron & Sean Rehaag LFO 2019.The Meet Gary team is made up of refugee lawyers and refugee law researchers. We have decades of collective experience representing claimants before the Refugee Board and studying how Board members make their decisions.

An old courthouse stands tall against cloudy skies.

Artificial Intelligence for a Reduction of False Denials in Refugee Claims

Publications

Artificial Intelligence for a Reduction of False Denials in Refugee Claims Hilary Evans Cameron & Avi Goldfarb & Leah Morris, “Artificial Intelligence for a Reduction of False Denials in Refugee Claims” (2022) 35:1 Journal of Refugee Studies 493. View Article

Colourful strings of code on a black computer screen.

Ryerson and UofT Professors Are Researching How AI Could Change Refugee Law

Media Articles

Ryerson and UofT Professors Are Researching How AI Could Change Refugee Law Minh Truong, Ryerson and UofT Professors Are Researching How AI Could Change Refugee Law (November 2020), online: The Eyeopener. View Article

A pair of glasses sitting on the keyboard of a computer with coding programs open, the image is blurry except through the lenses of the glasses.

Machine Learning Makes Uncertainty Visible. Can It Help Reduce False Denials of Refugee Claims?

Media Articles

Machine Learning Makes Uncertainty Visible. Can It Help Reduce False Denials of Refugee Claims? Jovana Jankovic, Machine Learning Makes Uncertainty Visible. Can It Help Reduce False Denials of Refugee Claims? (October, 2020), online: University of Toronto. View Article