3 Aug, 2023
This CIFAR AI Insights Policy Brief explores how federated learning (FL) may be implemented. The authors discuss findings from document review, expert interviews, a validation workshop, and a survey of solutions to privacy, ethics and security challenges raised by FL. In evaluating solutions to potential challenges, they focus on a proportionate response to realized risks, specifically the frequency and magnitude of harm caused by ethical, privacy, and security breaches of health data. They discuss the trade-offs between protections and the utility of data for FL and recommend enabling governance models.
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Program Manager, AI & Society, CIFAR
CIFAR is a registered charitable organization supported by the governments of Canada, Alberta and Quebec, as well as foundations, individuals, corporations and Canadian and international partner organizations.