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Comparative analysis reveals accountability gaps in AI systems for global grain supply chains, indicating need for regulation.
AI systems now drive operational decisions in global grain supply chains, yet no jurisdiction requires enterprises to prove who decided what, when, and on what basis. This paper identifies a "four-layer accountability void": (1) a definition void, where concepts such as algorithmic collusion lack stable application to AI; (2) a regulatory void, where the EU AI Act, CFTC, and China's algorithmic governance each fail to classify grain trading AI as a subject of oversight; (3) an enforcement void, with zero publicly reported regulatory actions worldwide; and (4) a precedent void, with no court judgment or arbitration award on point. Through comparative analysis across seven jurisdictions and scenario-based stress testing, the paper documents how major trading houses have deployed AI while no regime exists for decision-level accountability. The analysis is diagnostic, intended to define the problem for regulators, legal scholars, and industry participants.
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Li et al. (2026) studied this question.
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