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<A+> Algorithms 101: Feminist Data
2020 Webinars by Women at the Table as part of the <A+> Alliance initiative:

FEMINIST DATA
For policy makers on the sidelines of the UN Data Forum

Where does traditional data collection go wrong? From a feminist point of view, what would inclusive data collection look like
Before, During, and After data is gathered? What would a methodology be to create this? How can governments (and other actors) ensure / facilitate the collection and use of inclusive and gender-responsive data ?
Join us as we discuss these questions with our special guests in this webinar focused on feminist data and policy.

Join us for the entire webinar series!

Affirmative Action Algorithms on the 3rd November at 1600 -1715 CET / 1000-1115 EDT
What are the most current technical and design approaches to unbiasing algorithms? What methodologies and environments are needed to mitigate bias? What would algorithms or Automated Decision-Making systems that actively correct for bias (rather than only mitigate bias) look like?
With Nyalleng Moorosi from Google AI, Paola Villarreal Head of Data Science National Council Science & Development, Mexico, Elisa Celis from Yale University.

AI, Social Protection & Procurement on the 17th November at 1600 -1715 CET / 1000-1115 EDT
How can private and public sector AI be leveraged to ensure AI and ADM are unbiased? How can procurement be used to incentivise inclusion and influence of feminists in the conception, budgeting, design, deployment, and monitoring of AI & ADM systems?

Algo 101: The Frontline on the 1st December at 1600 -1715 CET / 1000-1115 EDT
How is bias mitigated or amplified by underlying social protection assumptions, or development aid assumptions in AI / Automated Decision-Making systems? What would an Automated Decision-Making social protection system look like if designed with a feminist perspective?
With Jensine Larsen from World Pulse, David Kelleher from Gender at Work

Moderated by Caitlin Kraft-Buchman, Women at the Table

Oct 20, 2020 04:00 PM in Zurich

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