The NYPD uses biometric technologies such as facial recognition to identify crime suspects, but dark-skinned people are misidentified 40% of the time. To imagine a future where we don't deploy facial recognition & policing, #ForFreedoms & @ai4theppl launched #HeartRecognition: pic.twitter.com/5dnmxZAFLv— For Freedoms (@forfreedoms) June 21, 2021

Many of the issues discussed about data & racial inequality have been the focus by numerous organizations. This is a list of these organisations (largely US based)

Call for more transparency on how such tools are used in public services as 20 councils stop using computer algorithms. The Home Office recently stopped using an algorithm to help decide visa applications after allegations that it contained “entrenched racism”.

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.

Inaction makes you part of the problem. § In the UK, as protesters fill Hyde Park today, many are aware that while systemic racism may not result in as many horrific deaths of black people at the hands of police as in the US, racism is still pervasive within our society and politics.

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.