What do Russian trolls, Facebook, and US elections have to do with machine learning?
Recommendation engines are at the heart of the central feedback loop of social networks and the user-generated content (UGC) they create.
Users join the network and are recommended users and content with which to engage.
Recommendation engines can be gamed because they amplify the effects of thought bubbles.
The 2016 US presidential election showed how important it is to understand how recommendation engines work and the limitations and strengths they offer.
AI-based systems aren’t a panacea that only creates good things; rather, they offer a set of capabilities.