On this episode, we dive into the changing conversation about race and ethnicity in medicine. We hear stories about why it’s harder for Black Americans to get kidney transplants, why “Asian” is too broad of a category when it comes to public health, and how we could collect better, more meaningful data.

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Philipp Brandt, Stefan Timmermans Sociological Science June 17, 2021 10.15195/v8.a10 Abstract We propose an abductive logic of scientific inference for quantitative research.

Sources say the company prioritizes anti-discrimination in its talking points, but not in its spending.

This piece is dedicated in honor of the lives lost in Atlanta, Georgia on March 16th, 2021 due to more senseless anti-Asian violence. All U.S. federal and state entities should disaggregate data on the Asian American and Pacific Islander (AAPI) community. Currently, reports divided by racial categories often conceal the major differences in the AAPI population. […]

This Essay asserts that in the United States racial segregation has and continues to play a central evolutionary role in the inequalities we see reproduced and

Artificial intelligence ethics teams are playing a greater role at tech companies and helping them deal with bias and fairness issues that have cropped up at companies such as Twitter.

Computer algorithms that scan everything from terror watch lists to eviction records spit out flawed tenant screening reports. And almost nobody is watching

Our investigation found major universities were using race as a predictor of student success and, in the process, steering Black kids away from the sciences

Some researchers are up in arms about a U.S. Census Bureau proposal to add privacy protections by manipulating numbers in the data most widely used for economic and demographic research

Just 6% of respondents said they ensure AI is used ethically and responsibly by making development teams diverse.

I have had the privilege of being at Google for the past six years. One of the most impressive things I’ve seen there was an Ethical AI…

A new study shows that leading AI models are 1.5 times more likely to flag tweets written by African Americans as "offensive" compared to other tweets.

The U.S. Census Bureau is undertaking a privacy overhaul. It’s not going well

The stakes are high when it comes to using machine learning in government. Building these three key considerations into your work should help you prevent your project from causing unintended harm.

Ana Brandusescu  (McGill University) Michael Canares (StepUp Consulting) Silvana Fumega (ILDA)   In June 2020, we had the opportunity to join a discussion on open contracting and inclusion organised by ...