Found 10 bookmarks
Custom sorting
Deb Raji on Twitter
Deb Raji on Twitter
These are the four most popular misconceptions people have about race & gender bias in algorithms.I'm wary of wading into this conversation again, but it's important to acknowledge the research that refutes each point, despite it feeling counter-intuitive.Let me clarify.👇🏾 https://t.co/WdzmnGLaFm— Deb Raji (@rajiinio) March 27, 2021
tgyateng69·twitter.com·
Deb Raji on Twitter
How Data Can Map and Make Racial Inequality More Visible (If Done Responsibly) | by The GovLab | Data Stewards Network | Medium
How Data Can Map and Make Racial Inequality More Visible (If Done Responsibly) | by The GovLab | Data Stewards Network | Medium
Racism is a systemic issue that pervades every aspect of life in the United States and around the world. In recent months, its corrosive…
·medium.com·
How Data Can Map and Make Racial Inequality More Visible (If Done Responsibly) | by The GovLab | Data Stewards Network | Medium
Hidden in Plain Sight — Reconsidering the Use of Race Correction in Clinical Algorithms | NEJM
Hidden in Plain Sight — Reconsidering the Use of Race Correction in Clinical Algorithms | NEJM
"By embedding race into the basic data and decisions of health care, these algorithms propagate race-based medicine. Many of these race-adjusted algorithms guide decisions in ways that may direct more attention or resources to white patients than to members of racial and ethnic minorities"
tgyateng69·nejm.org·
Hidden in Plain Sight — Reconsidering the Use of Race Correction in Clinical Algorithms | NEJM
The dividing line: how we represent race in data – The ODI
The dividing line: how we represent race in data – The ODI
The point of this essay is to encourage a critical approach to the relationship between race and data. It points to three questions that anyone working with data should ask if they are going to be collecting and using data about race. § If we are not careful, data can divide and sort us in exactly the sort of essentialising ways that the colonial idea of race supported. But if researchers ask the right questions, and know their history, we can use data to advocate for racial justice.
·theodi.org·
The dividing line: how we represent race in data – The ODI