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Using the examples of three AI-based anti-corruption tools from Brazil\u2014risk estimation of corrupt behaviour in public procurement, among public officials, and of female straw candidates in electoral contests\u2014it illustrates how unfairness can emerge at the infrastructural, individual, and institutional levels. The article draws on interviews with law enforcement officials directly involved in the development of anti-corruption tools, as well as academic and grey literature, including official reports and dissertations on the tools used as examples. Potential sources of unfairness include problematic data, statistical learning issues, the personal values and beliefs of developers and users, and the governance and practices within the organisations in which these tools are created and deployed. The findings suggest that the tools analysed were trained using inputs from past anti-corruption procedures and practices and based on common sense assumptions about corruption, which are not necessarily free from unfair disproportionality and discrimination. In designing the ACTs, the developers did not reflect on the risks of unfairness, nor did they prioritise the use of specific technological solutions to identify and mitigate\u00a0this type of problem. Although the tools analysed do not make automated decisions and only support human action, their algorithms are not open to external scrutiny.<\/jats:p>","DOI":"10.1007\/s11023-024-09688-8","type":"journal-article","created":{"date-parts":[[2024,7,3]],"date-time":"2024-07-03T17:02:00Z","timestamp":1720026120000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Unfairness in AI Anti-Corruption Tools: Main Drivers and Consequences"],"prefix":"10.1007","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2229-986X","authenticated-orcid":false,"given":"Fernanda","family":"Odilla","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,7,3]]},"reference":[{"key":"9688_CR1","unstructured":"Aarvik, P. (2019). 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