Artificial Intelligence in Customs Risk Management: A Conceptual Framework for Balancing Trade Facilitation, Revenue Protection, and Algorithmic Accountability
DOI:
https://doi.org/10.70568/ujfiiai.3.1.5Keywords:
Customs risk management, Trade facilitation, Artificial intelligence, Revenue protection, Algorithmic accountability, Public sectorAbstract
The customs administrations around the world are under a continuous pressure to facilitate the trade and, at the same time, to protect the revenue and the security of the borders. The artificial intelligence (AI) is considered as a promising tool to solve this dilemma, because the AI can improve the selection of the risky shipments and reduce the physical inspection of the compliant shipments. The objective of this paper is to develop a conceptual framework that explains how the AI-driven risk management can affect the performance of the customs administrations, and what are the conditions that make this effect positive. The paper follows a conceptual research design based on a structured integrative review of the literature on the customs risk management, the AI in the public sector, the dynamic capabilities, and the algorithmic accountability. The proposed framework connects the data foundations and the AI capability of the customs administration with the AI-driven risk management, and it links the AI-driven risk management with three outcomes, which are the trade facilitation, the revenue protection, and the trust of the traders. Moreover, the framework suggests that the human-AI collaboration and the algorithmic accountability play a moderating role. Five propositions were developed to guide the future empirical research. The paper contributes to the literature by integrating the technical view of the customs risk management with the public governance view of the AI, and it provides a practical guidance for the customs administrations in the developing countries, including Jordan.
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