Algorithmic Bias: from discrimination discovery to fairness-aware data mining

Sata Hajaian, Carlos Castillo & Francesco Bianchi:

Algorithms and decision making based on Big Data have become pervasive in all aspects of our daily (offline and online) lives, as they have become essential tools in personal finance, health care, hiring, housing, education, and policies. Data and algorithms determine the media we consume, the stories we read, the people we meet, the places we visit, but also whether we get a job, or whether our loan request is approved. It is therefore of societal and ethical importance to ask whether these algorithms can be discriminative on grounds, such as gender, ethnicity, marital or health status. It turns out that the answer is positive: for instance, recent studies have shown that Google’s online advertising system displayed ads for high-income jobs to men much more often than it did to women; and ads for arrest records were significantly more likely to show up on searches for distinctively black names or a historically black fraternity.