#### Stuart France

##### Active member

Yesterday I also had a Zoom with a real person with a PhD in AI. Subject: the analysis of visitor data. After an hour we agreed that AI has nothing to offer over and above what can be done with traditional statistical methods. For example, we have a run of 100 days of visitor counts from some site. Ask AI "what do you make of that?" This kind of open question implies actual thinking, actual understanding. Would AI think of calculating median, mean, standard deviation, then do it, then start looking for "something". As a starting point, are the daily numbers credible? The Tower of London will be in a different footfall league to OFD. What if the mean and median are about the same, or not? What does that tell you? Suppose one particular date had a count which was three SDs above the mean? Is it reasonable to expect a few really wacky results within a run of 100 due to pure chance and natural variability? Suppose that date was a Saturday, which means seeing the need and bothering to check the weekday this date corresponds to? Suppose we have hourly totals as well as daily ones. Suppose all the excess activity occurred between 10am-3pm, or alternatively if it occurred between 2am-6am, then what would that suggest? Did it happen in June or December? Do we have comparative data for any other paths nearby or a car park, and were they affected or not on that date? Do we know anything about the weather then? And so forth.

Interpretation requires understanding wider contexts, deep knowledge of how the world operates, and in particular the human world, in search of plausible explanations of some value or interest to a client. These are far away from the kind of questions like "[what is a] cave" or "how do you tie a bowline knot" which are basically look-ups on encyclopaedic websites like Wikipedia or what Google does.