Artificial Intelligence as an Anti-Corruption Tool (AI-ACT) – Potentials and Pitfalls for Top-down and Bottom-up Approaches
release_dfivhoyskncpnawo6oplgn6744
by
Nils Köbis, Christopher Starke, Iyad Rahwan
2021
Abstract
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".
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