That is literally what the article describes, though, in Papua New Guinea. And it describes why states in Nigeria have such a strong incentive to fake their population numbers, that it's impossible to achieve an accurate national total.
I do think the headline exaggerates, I doubt "a lot" are fake, but some do seem to be.
If you pick any country and look at proxies that have significant cost associated with them, at relative population levels of verified locations, the population of the world differs pretty radically from the claims most countries put out.
If you don't have independent verification free from censorial pressures and legal repercussions, then you get propaganda. This is human nature, whether it stems from abuse of power or wanting to tell a story that's aspirational or from blatant incompetence or corruption.
Population numbers fall under the "lies, damned lies, and statistics" umbrella.
Can you provide an example that shows a radically different population count?
>If you don't have independent verification free from censorial pressures and legal repercussions, then you get propaganda
Always?
How would you perform a census without massive amounts of money and cooperation from the government?
Some people claim that China's population is half of what the officials claim.
I'm sure the various high-end intelligence agencies have a much better view on this than the public does. All kinds of ways of cross-checking the numbers, all by doing things they'll be doing in their normal course of events.
A normal person could probably do a decent job with an AI that isn't too biased in the direction of "trust gov numbers above all else" and tracking down and correlating some statistics too obscure and too difficult to fake. (Example: Using statistical population sampling methodology on some popular internet service or something.) The main problem there being literally no matter what they do and how careful they are, they'd never be able to convince anyone of their numbers.
The problem with trying to measure this as a normal person is that you don't have enough access to different types of measurements to build good models of sample bias and selection artifacts.