Live
- 2024 on track to be hottest year on record
- PM Modi’s visit to Solapur: Women applaud ‘Double-Engine’ government’s initiatives
- Nagarkurnool MLA Dr. Kuchukulla Rajesh Reddy Campaigning in Maharashtra Elections
- Wife Kills Husband with Her Lover: Details of Veldanda Murder Case Revealed by SP Gaikwad
- Strict Action on Violations of Food Rights: Telangana Food Commission Chairman Goli Srinivas Reddy
- Smooth Conduct of Group-3 Exams with Strict Security Measures: Collector Badavath Santosh
- Delhi HC orders cancellation of LOC issued against Ashneer Grover, wife
- Shami’s absence a major blow for India in BGT, says Paul Adams
- Will organize protests at borders if attack on minority Hindus in Bangladesh not stopped: Bengal LoP
- Dutch Ambassador Marisa Gerard Meets Telangana CM A. Revanth Reddy in Delhi
New AI system can predict corruption
Scientists have developed a new artificial intelligence system that can predict the likelihood of corruption in a government.
London: Scientists have developed a new artificial intelligence system that can predict the likelihood of corruption in a government.
The computer model based on neural networks developed by researchers from the University of Valladolid in Spain predicts provinces in which cases of corruption are more likely to appear, as well as the conditions that favour their appearance.
The system also confirms that the probabilities increase when the same party stays in government more number of years.
The study, published in the journal Social Indicators Research, does not mention the provinces most prone to corruption so as not to generate controversy. Researchers explained that "a greater propensity or high probability does not imply corruption will actually happen."
The data indicates that real estate tax, exaggerated increase in the price of housing, 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, it should be taken into account to carry out a more rigorous control of the public accounts.
