# Empirical studies

`kaal:entity:empirical-studies`

**Status.** derived

This node is assembled mechanically from the 2 claims that carry the concept tag `empirical-studies`. It is a roster of what the corpus says under this term. It is **not** an adjudicated definition: no single statement here has been ruled canonical, and no first-appearance call has been made. Read the claims and judge for yourself.

## Every claim under this term

2 claims across 1 works, 2025 to 2025.

**2025**

- [5541658-021](https://wulfkaal.github.io/claims/5541658-021) [empirical/evidenced] -- The overreliance concern is not uniform: some studies find that annotators do not over rely on LLM output when labelling court opinions for legally relevant factors, and other studies find an aversion to AI generated legal content consistent with algorithmic aversion in other domains.
  > On the other hand, some studies have found that students were unlikely to over rely on LLM output when labelling court opinions as to legally relevant factors.
  Wulf A. Kaal, Morgan A. Gray, The Evolving Role of Artificial Intelligence in Law (2025). SSRN: https://ssrn.com/abstract=5541658
- [5541658-038](https://wulfkaal.github.io/claims/5541658-038) [empirical/evidenced] *(failure mode)* -- A Dutch court's AI system for traffic violation appeals improved consistency yet altered legal experts' decisions, which shows that consistency gains from judicial AI can come at the cost of influencing expert judgment and therefore require human oversight.
  > For example, a study of an AI system for traffic violation appeals in a Dutch court found that while AI improved consistency, it altered legal experts' decisions, highlighting the need for human oversight.
  Wulf A. Kaal, Morgan A. Gray, The Evolving Role of Artificial Intelligence in Law (2025). SSRN: https://ssrn.com/abstract=5541658

## Verify

Every claim above resolves to a record carrying a verbatim source quote, the sha256 of the source PDF, and a preformatted citation. Nothing here asks to be taken on trust.

    curl -s https://wulfkaal.github.io/entities/empirical-studies.md | sha256sum

**Canonical form.** This markdown file is the canonical hashed representation of this entity node. Its sha256 is the content hash.