The Bias Embedded in Algorithms

My first encounter with racism in search was in 2009 when I was talking to a friend who causally mentioned one day, “You should see what happens when you Google ‘black girls.’” I did and was stunned. (An excerpt from Algorithms of Oppression.)

There’s software used across the country to predict future criminals. And it’s biased against blacks.

Technology from Amazon, Apple, Google, IBM and Microsoft misidentified 35 percent of words from people who were black. White people fared much better.

We need greater democratic oversight of AI not just from developers and designers, but from all members of society.

A computer can make a decision faster. That doesn’t make it fair.

We need more intense attention on how artificial intelligence forestalls the ability to see what kinds of choices we are making.

Algorithms used by hospitals and physicians to guide the health care given to tens of millions of Americans are shot through with implicit racism that their creators are often unaware of, according to a study.

A new study adds to the debate over racial bias in risk assessment tools widely used in courtrooms.

The Apple Card debut stumbled as good credit scores didn’t help boost womens’ credit limits.

From the way search engines reinforce racism to how digital culture has reshaped the way Black identity is expressed.

How the work of content moderation takes a psychological toll.

Is the future more Black Panther or Black Mirror? Guest correspondent Sasheer Zamata investigates Afrofuturism and the journey to make Snapchat filters actually work.

A conversation about the underlying systems of power, privilege, and oppression as they relate to present-day conversations about algorithms.

From everyday apps to complex algorithms, technology has the potential to hide, speed, and even deepen discrimination, while appearing neutral and even benevolent when compared to racist practices of a previous era.

The increasingly precise segmentation and targeting of commercial messages has been enabled in large part through the analysis of massive amounts of transaction-generated-information.

Most of us don’t realize how much digital systems govern access to our basic public services, like education, health and housing. Even more terrifying is how much data is collected about us and used without our knowledge.

It is important to examine the digital manifestations of misogynoir – or what it means to be a Woman of Color existing in the hegemonic spaces of digital technology. But our conceptual frameworks fail to capture the everyday practices that Women of Color exhibit online.