The uses of algorithms discussed in the first part of this article vary widely: from hiring decisions to bail assignment, to political campaigns and military intelligence.
Across all these applications of machine learning methods, there is a common thread: Data on individuals is used to treat different individuals differently. In the past, broadly speaking, such commercial and government activities used to target everyone in a given population more or less similarly—the same advertisements, the same prices, the same political slogans. More and more now, everyone gets personalized advertisements, personalized prices, and personalized political messages. New inequalities are created and new fragmentations of discourse are introduced.
Is that a problem? Well, it depends. I will discuss two types of concerns. The first type, relevant in particular to news and political messaging, is that the differentiation of messages is by itself a source of problems.