'Computer Says No': Was Your Mortgage Application Rejected Unfairly?. Issue 108 (30th July 2020)

• Record Type: Journal Article
• Authors: Werpachowska, Agnieszka
• Is Part Of: Wilmott. Volume 2020:Issue 108(2020)
• Page Start: 54
• Page End: 61
• Publication Date: 2020-07-30
• Subjects: AI -- machine learning -- fairness -- machine bias -- racism -- Bayesian inference; Finance -- Periodicals; Financial services industry -- Periodicals; 332
• DOI: 10.1002/wilm.10858
• Languages: English
• ISSNs: 1540-6962

Abstract

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.