In January 2018, scientists from Valladolid, Spain brought a piece of inspiring news to anticorruption advocates: they created an artificial intelligence (AI) system that can predict in which Spanish provinces are at higher risk for corruption, and also identifies the variables that are associated with greater corruption (including the real estate tax, inflated housing prices, the opening of bank branches, and the establishment of new companies, among others). This is hardly the first example of computer technology being used in the fight against corruption. Governments, international organizations, and civil society organizations have already been mining “big data” (see, for example, here and here) and using mobile apps to encourage reporting (see, for example, here and here). What makes the recent Spanish innovation notable is its use of AI.

AI is a cluster of technologies that are distinct in their ability to “learn,” rather than relying solely on the instructions specified in advance by human programmers. AI systems come in several types, including “machine learning” (in which a computer analyzes large quantities of data to identify patterns, which in turn enables the machine to perform tasks and make predictions when confronted with new information) and more advanced “deep learning” systems that can find patterns in unstructured data – in hundreds of thousands of dimensions – and can obtain something resembling human cognitive capabilities, though capable of making predictions beyond normal human capacity.

AI is a potentially transformative technology in many fields, including anticorruption. Consider three examples of the anticorruption potential of AI systems:

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