AI Predicts Corruption
Researchers from the University of Valladolid (Spain) have created a computer model based on neural networks that calculates the probability in Spanish provinces of corruption, as well as the conditions that favour it. This alert system confirms that the probabilities increase when the same party stays in government for more years.
The study, published in Social Indicators Research, does not mention the provinces most prone to corruption so as not to generate controversy, explains one of the authors, Ivan Pastor, who says, "A greater propensity or high probability does not imply corruption will actually happen."
The data indicate that the real estate tax, the exaggerated increase in the price of housing, the opening of bank branches and the creation of new companies are some of the variables that seem to induce public corruption, and when they are added together in a region, more rigorous control of public accounts might be warranted.