A new paper from the MIT Media Lab’s Joy Buolamwini shows that three commercial facial-analysis programs demonstrate gender and skin-type biases, and suggests a new, more accurate method for evaluating the performance of such machine-learning systems.

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

Britain must urgently regulate how companies use artificial intelligence (AI) at work, unions said on Thursday, warning of widespread discrimination if the technology is left unchecked.

What are data and technology? How do they impact Black lives in our health systems?

Companies pledged money and support for people of color. But some say they still face a hostile work environment for speaking out or simply doing their jobs.

Mobile applications aided by artificial intelligence may help migrants better address their physical and mental health.

How many times have you seen an all-female and black and ethnic minority (BME) panel talking about technology? For many people their first time would have been the Shuri Network launch last July. The Shuri Network was launched in 2019 to support women of colour in NHS digital health develop the skills and confidence to progress into senior leadership positions and help NHS leadership teams more closely represent the diversity of their workforce.

Computer vision technology has lower accuracy rates for black females

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.

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

Machine learning programs trained with patients’ own reports find problems that doctors miss—especially in Black people. Full study here: https://go.nature.com/3pnOwWP

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

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

Mapping a child's digital footprint across England's state education landscape. Policy recommendations for building a rights' respecting digital environment

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.

A growing number of firms are using artificial intelligence to pass or fail jobseekers.

"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"

“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.”

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

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

Machines can discriminate in harmful ways. Here's how we fix the problem

Many of the public and private services we use are now digital. The move to digital is likely to increase as technology becomes more embedded in our lives. But what does this mean for how essential public services understand who is using, or indeed not using, them and why? § Data about the protected characteristics of people using these services isn’t currently collected andstatistics aren’t published in a consistent or collective way. This means it is harder tofind out who is excluded from using these services and why.

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.