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Assessing Chile's Medical Claims Model: An AI Governance Metrics Deep Dive with Mariana Germán
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When governments create AI governance policy tools, how are they used in real-world situations? What does the process of assessing a machine learning model used by a government agency look like? In this episode of Privacy on the Ground, you’ll hear all about it from an insider: Mariana Germán, a researcher in the Ethical Algorithms Project at GobLab UAI, the public innovation laboratory at Chile’s Universidad Adolfo Ibáñez’s School of Government. Germán and the team at GobLab helped assess a machine learning model in development for use to help decide medical claims at Chile’s health agency, the Department of Social Security Superintendence or SUSESO. In this full interview recorded in September of 2024, Germán and World Privacy Forum Deputy Director Kate Kaye dig deep into the metrics and measurements used to assess the model and its risks of producing discriminatory decisions, discussing the caveats of the AI governance tools, measures and metrics themselves, and how they were applied.
Featured in this episode:
- Mariana Germán, researcher in the Ethical Algorithms Project at GobLab, the public innovation laboratory at Chile’s Universidad Adolfo Ibáñez’s School of Government
- WPF’s deputy director and Privacy on the Ground host and producer Kate Kaye
This episode of Privacy on the Ground features music by Maciej Sadowski. The Privacy on the Ground intro theme features music by Pangal.
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