The algorithmic feedback loop

Users keep encountering similar content because the algorithms keep recommending it to us. As this feedback loop continues, no new information is added; the algorithm is designed to recommend content that affirms what it construes as your taste.

Reduced to component parts, culture can now be recombined and optimized to drive user engagement. This threatens to starve culture of the resources to generate new ideas, new possibilities. 

If you want to freeze culture, the first step is to reduce it to data. And if you want to maintain the frozen status quo, algorithms trained on people’s past behaviors and tastes would be the best tools.

The goal of a recommendation algorithm isn’t to surprise or shock but to affirm. The process looks a lot like prediction, but it’s merely repetition. The result is more of the same: a present that looks like the past and a future that isn’t one. 

Grafton Tanner, writing in Real Life Magazine