To generate this effect a program has to identify, that the photos are almost identical, that there are smiling people in them and then find a way to stitch the two photos together. I think that qualifies as AI.
It's AI in the sense that a pocket calculator from 1980 is AI. It doesn't know what it's doing, can only perform a limited range of calculations under tight constraints, has no awareness of whether or not the result is meaningful, and unless the authors went seriously overboard developing the suite, cannot learn from what it has done to improve the process.
It's pretty likely that the techniques being used fall under the term AI as used by people in the field. Actually, I'd be quite surprised if that wasn't the case.
Well, I am afraid that we are discussing semantics. The functions performed by the software, like facial recognition, are classical AI problems. Granted the software is certainly not any kind of general intelligence, and probably not even cutting edge AI, but it does still perform pattern recognition in unstructured data etc.
Ironically, parsing semantics is also a classic AI problem.
Twenty years ago what your phone is doing now was called AI. Now you call it "search engine" and "voice recognition". In the mind of people from outside the field, "AI" means "things computers can't do". The moment they are able to do something, it stops being called "AI" and becomes mundane.
It does, but in the article, the author is clearly using a grander sense of "AI" where computers are making autonomous decisions without our knowledge rather than just a clever heuristic. This is not that AI.