What is Data Equity?
And why should we care about it?
In the wake of racial unrest in the last year and a half, there have been renewed conversations around race, bias, and equity in all facets of society. As companies roll out new technology around facial recognition, policing, housing, immigration, healthcare, and education, we often hide behind their proprietary algorithms and soothing “objectivity”. However it’s a false sense of security — the algorithms themselves are encoded with bias, from the people who designed them to the historical data they’re trained on.
LA Tech4Good brought a panel on Elevating Data Equity in Practice to Data Con LA 2021. Rachel Whaley, LA Tech4Good’s Data Equity Program Manager, moderated the discussion with panelists Dr. Eboni Dotson, Maria Khan, Kathryn Wolterman, and Eva Pereira. All are leading work for data equity in their sectors and have participated in LA Tech4Good’s data equity workshops. Below is a summary of the topics covered and insightful perspectives the panelists shared.
Defining data equity
To frame the discussion, Whaley started with a definition of data equity: “Data is a thing we make and put to use. We can make and use it differently.” She noted that data is not inherently objective — at each phase someone made decisions, who to sample, how to collect it, how to…
