Abstract
`Fairness, Accountability and Transparency in Machine Learning' is a new field of AI science and what sounds like its examination of conscience. Are the machines tainted by the sins of their imperfect creators? In this article I review a selection of FAT/ML research aimed at ensuring fairness in some of the critical aspects of human existence. On the example of AI algorithms advising the US justice system, I demonstrate a simple statistical procedure of assessing bias in decision making, highlighting the importance of careful understanding of data and statistical concepts. Finally, I describe how FAT/ML tries to reconcile the machine transgressions in the best of possible, counterfactual reality. Should we absolve the machines and let them go and make the world a better place? I hope you will be able to answer this question yourself.
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