Many points raised here are valid concerns and should be addressed by the data scientists when designing the system.
Let's just not forget about the positives here: there is a company that openly uses term "A.I." and raised a lot of money. Am I the only one here waiting for the AI Winter to be over [1]? Maybe it's not the best A.I., yet, but they got the funding. Personally, I think that's great and I hope for others to come out of the closet.
The AI winter has been over for a couple years, we're in the middle of a torrid summer right now (triggered by the deep learning craze). There is a rush in the VC world to throw millions at any new AI startup, especially if it has "deep learning" in its pitch deck.
So far it has paid out, because large tech companies (Google, Facebook, Baidu, etc.) have been on a deep learning startup acqui-hiring spree. It might not last, though. Any company that bases its marketing on "AI" and subsequently fails to deliver is bringing us closer to the next AI winter.
Let's just not forget about the positives here: there is a company that openly uses term "A.I." and raised a lot of money. Am I the only one here waiting for the AI Winter to be over [1]? Maybe it's not the best A.I., yet, but they got the funding. Personally, I think that's great and I hope for others to come out of the closet.
[1] http://en.wikipedia.org/wiki/AI_winter