This is a really good article on the different things data scientists need to consider. This might seem like a post limited to AI specialists, but it is very accessible and will be useful even to a much wider readership. The advice here is useful not only for machine learning but for thinking and cognition in general. How isthe data biased? What's missing from the data? How are the characters in the data represented?