# kaal:claim:5541658-016

**Claim.** Keeping judges ultimately accountable through a human-in-the-loop review of AI generated reasoning, as practiced in Shenzhen, does not fully resolve the accountability problem in AI assisted adjudication.

**Type.** failure  **Support.** argued

**Holds when.**

- judicial settings where AI drafts or supports reasoning that a human judge then reviews

**Source quote.**

> Shenzhen case study illustrates that judges retain ultimate accountability, revising AI-generated reasoning to ensure accurate judgments, but this human-in-the-loop approach does not fully resolve the issue.

**From.** Wulf A. Kaal, Morgan A. Gray, *The Evolving Role of Artificial Intelligence in Law* (2025), Accountability in AI Judicial Functions, page 22

**Cite as.** Wulf A. Kaal, Morgan A. Gray, The Evolving Role of Artificial Intelligence in Law (2025). SSRN: https://ssrn.com/abstract=5541658

**Verify.** sha256 of source PDF `e543a2d698fcd522d4d02e034cc9ee1344d0015d2c824b40b9e05ab7c0728c60` at https://raw.githubusercontent.com/wulfkaal/Academic-Papers/main/papers/pdf/Kaal%20and%20Gray%20-%202025%20-%20The%20Evolving%20Role%20of%20Artificial%20Intelligence%20in%20Law.pdf

**Failure mode.** incomplete accountability under human-in-the-loop  (family: ai-oversight-and-alignment-gap)

**Topics.** ai-and-agents, law-and-legal-systems

**Keywords.** accountability, human-in-the-loop, judicial-ai, liability

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