France opens the way for tax verification via satellite. Through Google Maps (and artificial intelligence) we try to find crafty.
What if the tax authorities chose to fight tax evasion by exploiting the apps most used by people? Partially this is already happening, but the last trick, which came directly from France, puts on the board a decidedly innovative way to combat cunning. Trojan horse, in this case, It will be google maps, to literally use it to track down tax evaders even during their summer vacations. This, of course, assumes some kind of big brother on the whole group of taxpayers.
The eye depends on everything a person can do on vacation. This is to go to the pool, to the balcony with a picturesque view, to play tennis etc. Basically, any place can somehow To suggest a certain luxury in relation to the conditions of life announced. Google Maps, in all of this, is nothing more than a piece of curation tool. There is an algorithm at stake. More correctly, artificial intelligence.
Taxes and Google Maps: How to find tax evaders
The plan of the French Ministry of Economy is based on some kind of digital cooperation. Through Google Maps and automatic detection software, the goal is to identify illegal buildings and swimming pools, Identifying unsustainable luxury items for the people who use it. Items that will then be detected at high altitudes and monitored, to check whether or not they have been declared (and therefore taxable). If this is not the case, then the owner will have to settle his situation as soon as possible.
Therefore, technology and tax verification are becoming increasingly intertwined paths. France places great emphasis on cloud and hosting infrastructures, and on services to develop increasingly complex models of artificial intelligence applied to tax authorities. Google Maps is only a piece of the mosaic, given the same company Developed suitable “open source” tools very. The French strategy seems to have paid off: thanks to the new technology, the government has been able to identify clear differences between the data and the results using satellite images. Now it will be necessary to understand if some cleverness has already been found or whether the algorithm has walked on its own margin of error.
“Explorer. Devoted travel specialist. Web expert. Organizer. Social media geek. Coffee enthusiast. Extreme troublemaker. Food trailblazer. Total bacon buff.”