[sphere and ash]

There are statements made above that the probability of a match is so high that one may be “100% convinced,” or that the match shown for all six subjects may be as high as “99.9999%” or even “84-97%.” All of these estimates reflect a misunderstanding of probability, which I will attempt to explain below. But let me declare my bias from the outset: I am not convinced the stereoview depicts “six learned gents,” let alone the Knickerbocker Club.

All probabilities have a margin of error. Most people are aware of this when they see political polling: when one candidate leads in the polls 51-49, but the polling organization discloses a 3% margin of error, it is understood that the race is a statistical tie.

What we need to know is the margin of error for the facial recognition software used. The problem is that the software maker determines a margin of error using the same photographic process and type (say, a mug shot or passport photograph), similar lighting, contemporaneous images, etc. And what we have here are different photographic processes (salt, albumen, and, I believe, a silver gelatin copy photograph), with very different lighting (outdoor versus studio), taken many years apart, with limited visual information (these are group photographs taken from a distance where the ears are not visible, etc.), and where the original poster has altered the shadows in the photographs using another software program prior to analysis.

To give you some idea of how high the margin of error may be in this case, consider that a Google search shows estimates for facial recognition for African-American women may be higher than 35%. And that is with all the commonalities and without the difficulties cited above. I would be stunned if the margin of error here were not much higher. One can’t speak of meaningful probabilities in the presence of such a high margin of error. You’re asking the software to do something for which it was not designed and not tested.