For several years, the public administration has been working hard to introduce technology into its platforms and services, with the aim of improving the user experience by making all these procedures simpler and faster. We have seen this with the creation of apps, websites and the possibility of carrying out more processes virtually, and as it could not be otherwise, the Government also plans to take advantage of the benefits of Artificial Intelligence.
It was only a few weeks ago that Minister Escrivá explained that they planned use AI to alleviate the effects of mass retirements of civil servants over the next 10 years through this technology, but Spain’s intentions do not stop here.
And as they announced at the end of May, the The Tax Agency presented a manual in which they outline their strategy to implement AI in their services. Until now, the systems used by the Treasury to approve or reject model 100, however, when some type of discrepancy is detected, a human inspector comes into play to analyze the case.
Well now, the Tax Agency wants to give you more tools to your teamand they pretend use AI for data matching used to detect fraudThe objective of this new system, which will integrate this technology, is to “encourage and simplify compliance with tax obligations for those obliged to pay, and, on the other hand, ensure that the data declared by those obliged to pay are of higher quality and contain fewer errors.”
Hence It will not only be a tool to hunt down those who try to deceive the Treasurybut during the Income Tax Return, users also We will take advantage of the advantages that this technology offers us to do it without errors.
This document, in turn, states that it guarantees the protection of taxpayers’ data and respects the legal system, in addition to ensuring on numerous occasions that There will always be a person responsible for the operation of the AI.
For now, the document does not show many more details or a date to implement these systems, but the Tax Agency has reported that They are going to begin the development and training process with “multidisciplinary teams” made up of business experts, data scientists and computer scientists.
