AFAIK we don't have a single reliable mechanism of action to reliably detect lying. ML won't change that - without a known mechanism of action, how can you define reliable features to train on?
Heck, the concept of lying itself is a philosophical minefield. No way they solved that. This thing, as stated in the article, just relies on physiological indicators and muscular activity. So it is a polygraph with a shiny layer of buzzwords sprayed on.
All in all, just another worrying piece of news from Hungary.
They don't really need to detect lying, they need to detect deception. Which is different, and, I'm pretty sure, possible to detect in most cases with advanced enough technology.
No offense, but you have no background in science/logic, do you? Of course I didn't say that. One cannot prove that something doesn't exist. That's why I didn't write it.
Please take a step back and look at all the replies to you. They all essentially say the same: We don't know of any reliably objective measurement for measuring lying. Humans can sometimes do that intuitively, yes, but to my knowledge there hasn't been a single successful attempt of a generalization of detection. That's why state of the art means using trained humans, like the airport security in Israel.
Without a mechanism to detect lying without using humans, no amount of statistics (which ML boils down to) can help you. ML can't change the fact that you don't know if the data point is a signal or just noise. Without knowing what the signals look like, ML can't calculate the noise away.
Even simpler: For ML you need a dataset with people lying and people saying the thruth. That's what you train the model on. But we have no way of building that dataset, because, to my knowledge, we don't have a way to reliably build up this dataset: We can't reliably detect if someone is lying.
All in all, just another worrying piece of news from Hungary.