# kaal:claim:5541658-030

**Claim.** Because AI systems are predominantly developed in the West and trained mostly on Western data, their outputs are liable to carry cultural biases that inadequately represent non-Western cultures and the values inherent in them.

**Type.** mechanism  **Support.** argued

**Holds when.**

- AI systems deployed in non-Western legal systems
- training corpora dominated by Western sources

**Source quote.**

> Such western AI system domination can be further exacerbated through mostly western training data for AI systems. This may lead to cultural biases in AI outputs as non-western cultures and non-western values inherent in such cultures are inadequately represented.

**From.** Wulf A. Kaal, Morgan A. Gray, *The Evolving Role of Artificial Intelligence in Law* (2025), Limited Focus on Non-Western Legal Systems, page 32

**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.** Western training data bias  (family: ai-model-and-training-failure)

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

**Keywords.** cultural-bias, non-western-legal-systems, training-data, research-gaps

**Related claims.**

- specializes: https://wulfkaal.github.io/claims/4796714-011

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