4 of 6

To cite this article, we see that "according to the June 4 report... there is a 99.99 percent match of the male in the video clip to a known photo of Anwar based on facial recognition analysis."

A 99.99% match does not mean a 99.99% chance that this is him. For instance, if (a) the analysis checked 10,000 different things to determine a match and (b) this particular analysis found that 9,999 of those things did match then (c) we would have a 99.99% match.

Saying that there is a 99.99% chance that the face in the video belongs to a specific person would need to check how many different faces could have matched with the same type of analysis. If 1 person could have matched out of 100, then we have a 1% chance that this is the right face based on the analysis alone. (Other information could later narrow it down further.) Saying that the analysis is 99.99% chance this is the right person means that roughly 1 out of every 10,000 people could match in the same way. More gritty details below.

Using Bayes' law, we see that the probability that the matching man is the same man in the video is:

``````(The prior probability that the man was in the video *
the probability that a video of him would give a 99.99% match to his face) /
(The prior probability that it was another man in the video *
the probability that a video of another man would give a 99.99% match to his face)
``````

To get an idea of the likelihood of this person being the one in the video, we'd have to look at the accuracy and recall of this face matching system (i.e. a ballpark estimate for probabilities 2 and 4 in the above formula).

On the other hand, to say that

This means that A and B is the same person

Is not an equivalent statement without additional justification. However, it seems to be from a different source.