Interpreting logs, the Tesla story

Did you see the NY Times review by John Broder, which was critical about the Tesla Model S? Tesla CEO Elon Musk was not pleased. They are not arguing over interpretations or anecdotal recollections of experiences, instead they are arguing over basic facts — things that are supposed to be indisputable in an environment with cameras, sensors and instantly searchable logs.

The conflicting accounts — both described in detail — carry a lesson for those of us involved in log interpretation. Data is supposed to be the authoritative alternative to memory, which is selective in its recollection. As Bianca Bosker said, “In Tesla-gate, Big Data hasn’t made good on its promise to deliver a Big Truth. It’s only fueled a Big Fight.”

This is a familiar scenario if you have picked through logs as a forensic exercise. We can (within limitations) try and answer four of the five W questions – Who, What, When and Where, but the fifth one -Why- is elusive and brings the analyst of the realm of guesswork.

The Tesla story is interesting because interested observers are trying to deduce why the reporter was driving around the parking lot – to find the charger receptacle or to deliberately drain the battery and make for a bad review. Alas the data alone cannot answer this question.

In other words, relying on data alone, big data included, to plumb human intention is fraught with difficulty. An analyst needs context.