As I see it, TA is just a specialized form of "descriptive statistics":
https://en.wikipedia.org/wiki/Descriptive_statistics
There is obviously nothing wrong in making such quantifications, just as it makes perfect sense to compute other descriptive statistics.
The issue arises when you wish to attribute
inferential value to such observations, like for instance when you wish to interpret it as a "premonition" of a future occurrence:
https://en.wikipedia.org/wiki/Statistical_inference
It's mainly a conceptual issue. Imho, attributing previsive value is, first of all, a crackpot nonsense conceptually, and, second, not supported by any sound statistical evidence (clearly if we exclude pseudo scientific inventions by charlatans and people with no solid statistical background).
This does
not mean anyway that it's "wrong" to use them to "decide" entries or other actions. In any case you entry is governed by price movement (and/or other observations) . So in case we model the price as a
random process, the "entry" (say for instance, the pair [price, time] ) too is going to be a random variable, and basing the entry on some TA computation is simply a
transformation of a random variable, resulting in another random variable. So there is nothing wrong in that, as essentially everybody is inevitably doing the same.
I would just argue that the terminology may be a bit misleading, especially for beginners. (Just as the term "stop loss" is misleading.) But these terminologies are typical of the field where there are so many entities trying to sell something and often do not mind to bend concepts and reason when it is convenient.