Ethics, regulation and human oversight in the implementation of AI for compliance: evidence from a systematic review
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Abstract
The incorporation of artificial intelligence systems into anti-corruption compliance programs has significantly transformed risk detection, prevention, and control mechanisms by introducing hybrid models that combine algorithmic automation and human oversight. This transformation is especially relevant in highly regulated legal contexts, where AI-assisted decisions can affect accountability, the protection of fundamental rights, and institutional legitimacy. Within this framework, the objective of this article was to identify the ethical and regulatory challenges that arise from the implementation of hybrid human-AI systems in compliance programs, based on the available scientific evidence. To this end, a systematic review article was developed, following the PRISMA 2020 guidelines, by identifying, selecting, and critically analyzing studies published in peer-reviewed scientific journals between 2021 and 2026. The results revealed the presence of recurring challenges, such as algorithmic bias, decision opacity, dilution of accountability, regulatory fragmentation, and limitations in the effectiveness of human oversight. Furthermore, governance proposals and mitigation strategies focused on the explainability, auditability, and socio-technical integration of the systems were identified. In conclusion, the review highlights that the effectiveness of human-AI hybrid systems in compliance programs depends not only on their technical design but also on the existence of operational ethical and regulatory frameworks that coherently link automation with meaningful human control
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