kaal:claim:5541658-031

Experimental studies suggest risks such as bias amplification from judicial AI, but there is little empirical data on how those risks actually manifest in operational courtrooms, which leaves practical integration guidelines undeveloped.

Source quote, verbatim

While experimental studies suggest risks like bias amplification, there is little empirical data on how these risks manifest in operational judicial settings.

From

Wulf A. Kaal, Morgan A. Gray, The Evolving Role of Artificial Intelligence in Law (2025), Insufficient Exploration of Real-World Judicial AI Applications, p. 33
https://ssrn.com/abstract=5541658 · source PDF

Cite as

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

Holds when

the gap between experimental and deployed judicial AI systems

Classification

failuresupport: arguedfailure: absent real-world deployment evidencefamily: research-design-limitationempirical-evidence

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