I'd like to see a serious investigation and discussion around the recommendation engines used to rank content added here.

Something is seriously wrong with youtube's algorithm, whether in the technical implementation or how it deals with spam/unintended consequences.

Kids watching cartoons get recommended messed up stuff (e.g. https://www.reddit.com/r/OutOfTheLoop/comments/65rkxv/what_i... ), watch a single Jordan Peterson video and youtube will recommend you every fringe alt-right anti-feminism video it can find for months... It is toxic, causes real harm, normalizes extremist viewpoints and is shifting the Overton window in politics.

I'm not advocating censorship in any way, my concern is if algorithms/implementation bias what people see towards what will get the strongest reaction it is at least in a similar class of harm as censorship...

I have a hunch this is a natural consequence of using something like UCB (upper confidence bound) for contextual bandits to rank results when the feature vectors are using broad user / video clusters. Are explore vs exploit reinforcement learning algorithms used in production very susceptible to adversarial spam? Any evidence of fringe videos paying for viewbots etc...