We recognize that data sources we have access to can differ significantly from what occurs in the real world or not fully represent marginalized communities. We understand that this can reinforce existing biases that are embedded in these datasets.
We commit to taking the time to assess and balance any datasets we are using to minimize how much we push biases downstream. We will design for those closest to the margins who have the highest barriers to access, which includes those who are mono-lingual, have low-literacy, be a senior citizen, be justice-involved people, are immigrants, are black or latino*,* have limited internet access or live with a range of disabilities.
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