In this course, experts Mareisha Reese and Mary-Frances Winters explore the importance of equity in data practices to ensure fair, unbiased, and inclusive outcomes. It highlights how inequities in data collection, analysis, and reporting can perpetuate harm and skew results, particularly in areas like healthcare, HR, and AI applications. Learners will uncover sources of bias, such as sampling and algorithmic bias, and discover practical strategies to address these challenges. Through discussions on equity-focused methodologies and the role of AI and data ethicists, participants will gain tools and insights to incorporate equity into their data projects. By the end, learners will be equipped to create more just and inclusive data practices in their organizations.
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