# kaal:claim:5541658-015

**Claim.** Transparent, explainable models such as those built for the European Court of Human Rights, which paired 97% accuracy with digestible explanations, provide the design template for addressing legal AI's transparency problem.

**Type.** design  **Support.** evidenced

**Holds when.**

- systems using computational models of argument to generate legally grounded explanations

**Source quote.**

> Transparent, explainable AI models, such as those developed for the ECHR, which achieved 97% accuracy with digestible explanations, offer a model for addressing these concerns.

**From.** Wulf A. Kaal, Morgan A. Gray, *The Evolving Role of Artificial Intelligence in Law* (2025), Transparency and Interpretability, 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

**Topics.** ai-and-agents, disclosure

**Keywords.** explainable-ai, echr, transparency, design-template

**Canonical form.** This markdown file is the canonical hashed representation of the claim. Its sha256 is the content hash used for attestation.