I have just uploaded a new paper on SSRN: ‘Procurement corruption and artificial intelligence: between the potential of enabling data architectures and the constraints of due process requirements’, to be published in S. Williams-Elegbe & J. Tillipman (eds), Routledge Handbook of Public Procurement Corruption (forthcoming). In this paper, I reflect on the potential improvements that using AI for anti-corruption purposes can practically have in the current (and foreseeable) context of AI development, (lack of) procurement and other data, and existing due process constraints on the automation or AI-support of corruption-related procurement decision-making (such as eg debarment/exclusion or the imposition of fines). The abstract is as follows:
This contribution argues that the expectations around the deployment of AI as an anti-corruption tool in procurement need to be tamed. It explores how the potential applications of AI replicate anti-corruption interventions by human officials and, as such, can only provide incremental improvements but not a significant transformation of anti-corruption oversight and enforcement architectures. It also stresses the constraints resulting from existing procurement data and the difficulties in creating better, unbiased datasets and algorithms in the future, which would also generate their own corruption risks. The contribution complements this technology-centred analysis with a critical assessment of the legal constraints based on due process rights applicable even when AI supports continued human intervention. This in turn requires a close consideration of the AI-human interaction, as well as a continuation of the controls applicable to human decision-making in corruption-prone activities. The contribution concludes, first, that prioritising improvements in procurement data capture, curation and interconnection is a necessary but insufficient step; and second, that investments in AI-based anti-corruption tools cannot substitute, but only complement, current anti-corruption approaches to procurement.
As always, feedback more than welcome. Not least, because I somehow managed to write this ahead of the submission deadline, so I would have time to adjust things ahead of publication. Thanks in advance: a.sanchez-graells@bristol.ac.uk.