Smart Marketing advocates claim that by collecting data from monitoring online activity to determine behavioral habits and personal preferences, companies can better serve individual interests. However, algorithms perform data collection and analysis of variables like media consumption, browsing history, and social media sharing, to manage groups and connect networks of people.
Often, expected characteristics are inaccurate and assign people to undesirable social affiliations. This act of grouping consumers into a generic profile has direct effects on the individual’s exposure to diverse media. Resulting in news feeds and inboxes filled with a single viewpoint, which results in a narrow perspective on issues.
Programmers design algorithms to strategically determine what media to generate for segments of a consumer base that it will find worthwhile, and ideally, shareable. This is problematic because reducing people to a unit of analysis is systematic discrimination and for many socio-economic groups, detrimental to equality and the expansion of knowledge.
For example, Facebook uses algorithms to determine segments of a user’s connected friends that will show various posts based on prior engagement metrics including, liking, and sharing of similar content. Again, this limits users’ exposure to alternative viewpoints that may benefit the individual by expanding awareness of important social and political issues.