kaal:position:2026-07-31-7158

Understanding agent governance technology approaches presents the following source proposition: Agent artificial intelligence (AI) automates AI using the reasoning power of large language models (LLMs) to make decisions without human intervention. This proposition is pertinent to Kaal's source-bound claim that The Shenzhen courts illustrate a workable three step human-in-the-loop design for generative judicial AI: the judge decides first, the LLM generates the supporting reasoning, and the judge then revises that output to finalize the judgment. The proposed response is an extension: the relationship should remain limited to the retrieved source proposition and the mapped Kaal claim unless fuller source review supports a broader conclusion.

• The response is limited to the retrieved source proposition and mapped Kaal claim unless fuller source review supports a broader conclusion.
• External evidence level: abstract indexed.
• Mapping review tier: moderate-confidence claim review.
• Primary mapping confidence: 0.4854.
• The source-to-claim mapping remains explicitly ambiguous and is published with that limitation.

Understanding agent governance technology approaches

kaal:claim:5541658-010
Wulf A. Kaal, Morgan A. Gray, The Evolving Role of Artificial Intelligence in Law (2025). SSRN: https://ssrn.com/abstract=5541658
Source PDF sha256: e543a2d698fcd522d4d02e034cc9ee1344d0015d2c824b40b9e05ab7c0728c60

Evidence: abstract indexed
Review tier: moderate-confidence claim review
Mapping confidence: 0.4854
Mapping ambiguous: true

ai-and-agentshistorical-responsescholarly-literaturecrossref

Affirmed in kaal-review:2026-07-31:streaming-etl-0008 on 2026-07-31. Review record.

Canonical markdown sha256: 325aa1d1f268c3b4516505cdbe30bd212076ad8d34dc3849022257dc4364d9d5
curl -s https://wulfkaal.github.io/positions/2026-07-31-7158.md | sha256sum