We welcome Mihaly Fazekas, assistant professor at the Central European University, Department of Public Policy, who works on a range of topics related to corruption. The interview covers how how his own personal experience with bad public infrastructure inspired him to conduct corruption research, why he believes that corruption research would benefit from a better understanding of what are actually ymeasuring when we study corruption and the importance of investigative journalism (for example the invesgtative journalism center direct36; https://www.direkt36.hu/en/). Mihaly then makes a compelling pitch why public procurement offers a relevant and interesting subject for corruption researchers. The enf of the interview deals with the intersection between big data, technology and corruption, such as whether new corruption risks emanate from Artificial Intelligence and how AI conversely might be used to fight corruption.
Concrete examples mentioned: the e-procurement portal Dozorro in Ukraine: https://oecd-opsi.org/innovations/dozorro/
Mihaly’s pick of the podcast: the classic computer game civilization II: https://civilization.com/de-DE/civilization-2/
Further reading on AI and anti-corruption:
Fazekas, M., & Kocsis, G. (2020). Uncovering high-level corruption: cross-national objective corruption risk indicators using public procurement data. British Journal of Political Science, 50(1), 155-164.
Abdou, A., Basdevant, O., David-Barrett, E., & Fazekas, M. (2022). Assessing Vulnerabilities to Corruption in Public Procurement and Their Price Impact. IMF Working Papers, 2022(094). https://www.elibrary.imf.org/view/journals/001/2022/094/article-A001-en.xml
Adam, I., & Fazekas, M. (2021). Are emerging technologies helping win the fight against corruption? A review of the state of evidence. Information Economics and Policy, 57, 100950. https://www.sciencedirect.com/science/article/pii/S016762452100038X
Köbis, N., Starke, C., & Rahwan, I. (2022). The promise and perils of using artificial intelligence to fight corruption. Nature Machine Intelligence, 4(5), 418-424. https://www.nature.com/articles/s42256-022-00489-1.epdf?sharing_token=EdeuqUBk2oKscPxws-8D8tRgN0jAjWel9jnR3ZoTv0MSvwdFseOcM6qa-7nxQYsZYARiqghH2fBcU3_YVcnprrGjCkjAT_ckOEcdYz5UF1qnHidcuHymvw9CuowLifDJHoE1fGJ8XeL2AP-YJttRiF8JbxMcwgUWCUAzAK5ZbBE%3D
I think episode 0 is deleted or somehow have a problem. I cannot download it or listen to it while I downloaded episodes 1 and 2 successfully. BTW thank you for good content you provided!
The common way to standardise is incidents per thousand which ‘disadvantages states like Wyoming over California’. Apparently. Otherwise an interesting topic with some insight into the complexity of measuring Criminal Justice