Royal Society report shows white students twice as likely as black students to achieve top Stem degrees

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.

"Why aren't there more Black workers in tech, and why is progress so slow?"

Gender equality can seem like one big homogeneous bowl of intentions demonstrating that we care about women. A better structure for change centers on the perspective, needs and experience of Black women. Today’s common trickle-down approach is not working; a “trickle up” or “follow up” paradigm would be more effective.

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.

Interviews with diversity managers and internal data obtained by Recode indicate that Black Amazon employees are promoted less frequently and are rated more harshly than non-Black peers.

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.

Government considers shelving service again as figures suggest evidence of growing inequality. “The excuse is likely to be that businesses are badly hit right now but actually, it is employees, especially women and minorities, who have been badly hit.”

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