Digital discrimination is becoming a serious problem, as more and more decisions are delegated to systems increasingly based on artificial intelligence techniques such as machine learning. Although a significant amount of research has been undertaken from different disciplinary angles to understand this challenge—from computer science to law to sociology— none of these fields have been able to resolve the problem on their own terms. We propose a synergistic approach that allows us to explore bias and discrimination in AI by supplementing technical literature with social, legal, and ethical perspectives.
How do we ensure that tools such as machine learning do not displace important social values? Evaluating the appropriateness of an algorithm requires understanding the domain space in which it will operate.