From Stanford Social Innovation Review, January 28, 2021
Very few people build data products because they want to promote racist or sexist ideas; however, it’s very easy to fall into these traps, particularly when we fail to question the widely held belief in the “objectivity of evidence.” A working understanding of how to incorporate equity into data products, and knowledge of practical tools that embed equity in your research and data, is essential for anyone conducting data analysis, or making decisions based on data analysis.
This session, led by Heather Krause, founder of Datassist and We All Count, provides you with several shocking real-world examples of mistakes made when using data that led to biased outcomes, and a seven-step framework for identifying inequity and hidden bias in the data product lifecycle. As interest in equity in data grows, this framework provides actionable steps for making changes in the way you and your team use data.
Registered attendees for Data on Purpose will have access to this session as part of their registration. If you are not already registered for Data on Purpose and would like to attend this session at no cost, please sign-up by filling out this short Google Form.
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