"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"

Computer vision technology has lower accuracy rates for black females

Image-generation algorithms are regurgitating the same sexist, racist ideas that exist on the internet.

Discusses harms of racial policing practices, potential effects of data driven technologies & opportunities for activism

“It’s almost an imperative, I think, to drive that diversity,” she said. “Diversity from a gender perspective, but also from other perspectives such as age, race, ethnicity, geography, and many others, because we’re seeing AI is such a powerful technology, and we need to make sure it is equitable.”

Perhaps without even noticing, you have read about data racism several times in the news in the past months. What is it? This blog seeks to explain - in the context of an emerging strand of work at the European Network Against Racism exploring racism in the digital space.

Racism is a systemic issue that pervades every aspect of life in the United States and around the world. In recent months, its corrosive…

As we hand over decision-making regarding social issues to automated systems developed by profit-driven corporates, not only are we allowing our social concerns to be dictated by the profit incentive, but we are also handing over moral and ethical questions to the corporate world, argues ABEBA BIRHANE

Proctored exams have a bias toward students from racial minorities and other disadvantaged groups.

Tools like GPT-3 are stunningly good, but they feed on the cesspits of the internet. How can we make them safe for the public to actually use? § Sometimes, to reckon with the effects of biased training data is to realize that the app shouldn't be built. That without human supervision, there is no way to stop the app from saying problematic stuff to its users, and that it's unacceptable to let it do so.

The use of artificial intelligence (AI) presents risks to equality, potentially embedding bias and discrimination. Auditing tools are often promised as a solution. However our new research, which examines tools for auditing AI used in recruitment, finds these tools are often inadequate in ensuring compliance with UK Equality Law, good governance and best practice. We argue in this report that a more comprehensive approach than technical auditing is needed to safeguard equality in the use of AI for hiring, which shapes access to work. Here, we present first steps which could be taken to achieve this. We also publish a prototype AI Equality Impact Assessment which we plan to develop and pilot.

Automated decision making threatens to disproportionately impact society’s most vulnerable communities living at the intersection of economic and social marginalization. The report discusses