Filter bubbles and targeted advertising

Over a decade ago, tech companies began using algorithms to personalize our experience of the web. Using sophisticated technology and vast amounts of consumer data, companies began to predict our tastes better than we could ourselves. In response, ecommerce expanded, and journalism adapted itself to the personalized attention economy. However, there was a hidden side effect, which Eli Pariser termed the filter bubble, which is the exclusion of other perspectives from our tech-assisted preferences. Raising many hard questions including data security, political propaganda, and the pervasiveness of digital junk food, filter bubbles reveal the future challenges of a personalized, automated web. Features such as media literacy questions and terms enhance this collection, encouraging readers to analyze reporting styles and devices.