Artificial Intelligence as an Anti-Corruption Tool (AI-ACT) -- Potentials and Pitfalls for Top-down and Bottom-up Approaches
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Abstract (arXiv)
Corruption continues to be one of the biggest societal challenges of our time. New hope is placed in Artificial Intelligence (AI) to serve as an unbiased anti-corruption agent. Ever more available (open) government data paired with unprecedented performance of such algorithms render AI the next frontier in anti-corruption. Summarizing existing efforts to use AI-based anti-corruption tools (AI-ACT), we introduce a conceptual framework to advance research and policy. It outlines why AI presents a unique tool for top-down and bottom-up anti-corruption approaches. For both approaches, we outline in detail how AI-ACT present different potentials and pitfalls for (a) input data, (b) algorithmic design, and (c) institutional implementation. Finally, we venture a look into the future and flesh out key questions that need to be addressed to develop AI-ACT while considering citizens' views, hence putting "society in the loop".
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 6 of its 106 references that are in the map. First posted on arXiv 23 Feb 2021.
Builds on
6 of 106 references.
References · 6
- 2017Explanation in Artificial Intelligence: Insights from the Social Sciencescited by 1,201
- 2017Society-in-the-Loop: Programming the Algorithmic Social Contractcited by 35
- 2015Botivist: Calling Volunteers to Action Using Online Botscited by 7
- 2018AI for the Common Good?! Pitfalls, challenges, and Ethics Pen-Testingcited by 4
- 2017Predicting Financial Crime: Augmenting the Predictive Policing Arsenalcited by 2
- 2020Artificial Intelligence for EU Decision-Making. Effects on Citizens Perceptions of Input, Throughput and Output Legitimacycited by 1
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Citing papers per year: 2021: 1.
1 paper.