I read the summaries and skimmed through the videos but couldn't find anything on ethics, fairness, transparency or data protection. Is there anything? If not,

I read the summaries and skimmed through the videos but couldn't find anything on ethics, fairness, transparency or data protection. Is there anything? If not, I really think that these topics should be addressed (even if only briefly) in any "field guide" to machine learning. Especially FB should give those some more attention after their numerous scandals and "mishaps". Now, before you downvote this or say "but this is just about the methods and tools" please take a moment to think about how much power ML models can have over people when deployed at FB scale. I would like to see at least a (brief) discussion of the following topics in such guides: - Data Provenance & Data Ethics (Can I use this? Should I?) - Data Protection & Security (How can I protect personal information when doing ML?) - Model Fairness (How can I ensure my model is fair and does not discriminate?) - Model Transparency (How can I explain the results of the model to users and colleagues?)