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Non-Ableist Data Science
Data science is increasingly important in producing knowledge and technologies that impact us daily. How we analyze data, design analysis tools, deploy algorithmic systems, and publish data-driven conclusions matters to real lives. When data science ignores variations and disparities in the human experience, it can bias decision-making and outcomes that negatively affect people with disabilities.

In this hands-on workshop, we adopt an equity lens to ask how data scientists can confront ableism, which is systemic bias that privileges people with “typical” abilities. Our breakout teams will be guided through the following activities: (1) explore data science as a practice that includes planning, building, and deploying; (2) identify patterns of ability-based bias in data science; (3) analyze particular cases of ableism in data science; and (4) develop tools that can guide data science practitioners in avoiding the most common ableist pitfalls.

Chair: Anat Caspi (University of Washington)

Jan 26, 2022 12:30 PM in Pacific Time (US and Canada)

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