And it works most of the time, the autopilot keeps the car on the road and avoids danger. Except for that 0.01% when it fails and you have to react as quickly as if you have been driving all this time.
The quality of a system is always measured in how well it handles exceptions. (Control question: Try to come up with a single example of a good system that handle exceptions badly. Hint: give up because such systems do not exist)
So a autopilot driving car will handle the normal case extremely well, but when something unexpected happens a human driver is much better capable of performing a sensible action.
Big Data is about finding patterns, not conclusions.
Gary Taubes (author of "Good calories - bad calories" and "Why we get fat and what to do about it") is my favourite scientist because he just exhibit such a healthy, integrated "given that what we believe today is correct" attitude, e.g. being totally open to be proven incorrect. There is a saying "follow those that seek the truth, run from those that have claimed to found it", and Gary is most certainly a truth seeker in that respect.
For instance in the interview https://www.youtube.com/watch?..., he says during the first minutes "That's what we should believe until we have remarcable evidence to reject it" and "Don't take my word for it, anyone can try it out for themselves", without this being specifically emphasised or made a big point of, it is just his natural way of reasoning which I love so much.
And now to what triggered me to answer your post: I think it is later in that interview that he points out that observation studies can only be used to form hypothesis, dawing conclutions from them is wrong, you actually need to perform controlled experiments to do that.
"It's like deja vu all over again." -- Yogi Berra