Human-Centered Data Science Lab
We are a research group at the University of Toronto working in public interest technology, pairing technical, computational methods with critical, interpretive inquiry in areas such as child welfare, housing, healthcare, and higher education.
Our work runs along four lines. We audit the systems already in use, build alternatives with the communities and workers affected by them, test whether those systems work on terms those communities help set, and study the policies that decide which systems get used at all.
Auditing and theorizing the algorithmic systems already running inside public institutions.
Building alternatives, tools, and datasets with the communities and workers who use them.
Testing whether those systems work, against criteria the affected communities set.
Shaping the rules that decide which systems exist, and under what oversight.
Current Research
Child Welfare
Long-term fieldwork on how caseworkers and predictive risk models interact, and the harms that follow.
AI Governance
How governments procure, register, and answer for the algorithms they deploy in public services.
Health
Building and auditing predictive tools for clinical and population health with the communities they affect.
Fairness and Language
How governments procure, register, and answer for the algorithms they deploy in public services.
Supported at the University of Toronto
Join the lab
We are a research group at the University of Toronto working in public interest technology, pairing technical, computational methods with critical, interpretive inquiry in areas such as child welfare, housing, healthcare, and higher education.
We are a research group at the University of Toronto working in public interest technology, pairing technical, computational methods with critical, interpretive inquiry in areas such as child welfare, housing, healthcare, and higher education.
