> You would need to publicize the weights and input data of the algorithm Again, I don't think that really tells you anything, and I'm telling you now there is

> You would need to publicize the weights and input data of the algorithm Again, I don't think that really tells you anything, and I'm telling you now there is _zero_ chance that these companies open source their training data (that's their secret sauce). But even if you could, what can you possibly do with this information that would be useful? It's completely inscrutable for laypeople, which means it will only be analyzed by ML-competent engineers and mathematicians. And if it's a deep-learning algorithm, it's completely unexplainable and will yield practically no useful insights. I don't think there is an "ideal" recommendation algorithm. There is no way to say "ah if we just tweak these weights, everything will be fixed!" Every single one has tradeoffs and will direct you towards filter bubbles. The problem is that many sites give you practically no other way to see content, which means you're constantly being manipulated by an algorithm that is itself learning from how you interact with what it proposed to you. That feedback loop is toxic, and steals user agency.