https://thenextweb.com/artificial-intelligence/2020/06/05/how-to-detect-unwanted-bias-in-machine-learning-models/

In 2016, the World Economic Forum claimed we are experiencing the fourth wave of the Industrial Revolution: automation using cyber-physical systems. Key elements of this wave include machine intelligence, blockchain-based decentralized governance, and genome editing. As has been the case with previous waves, these technologies reduce the need for human labor but pose new ethical challenges, especially for artificial intelligence development companies and their clients.

The purpose of this article is to review recent ideas on detecting and mitigating unwanted bias in machine learning models. We will discuss recently created guidelines around trustworthy AI, review examples of AI bias arising from both model choice and underlying societal bias, suggest business and technical practices to detect and mitigate biased AI, and discuss legal obligations as they currently exist under the GDPR and where they might develop in the future.