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What AI Orgs Can Do for Data Enrichment Workers
Data enrichment workers who clean, label, and moderate large sets of data are essential to machine learning (ML). Yet these workers often face poor working conditions and few labor protections, which not only impacts the wellbeing of data enrichment workers, but also affects the quality of the data AI technology is built on.

Partnership on AI (PAI) has launched a set of Data Enrichment Sourcing Guidelines for AI organizations to use to develop best practices with a positive impact on the lives of data enrichment workers. These resources have been put into practice by PAI Partner DeepMind, and documented in an accompanying case study and blog post.

This panel discussion moderated by Sonam Jindal, Program Lead for AI, Labor and the Economy will unpack why companies should be prioritizing responsible data enrichment practices, what this accomplishes, and what more we need to do, and through a real-world exploration of PAI Partner DeepMind’s process, challenges, and impact of putting the Guidelines into practice.

Dec 6, 2022 09:00 AM in Pacific Time (US and Canada)

Webinar is over, you cannot register now. If you have any questions, please contact Webinar host: Josh Pikus, PAI [he/him/his].