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Incentive and Information Frictions in Algorithmic Legal Commands | Synapse
May 26, 2026
Incentive and Information Frictions in Algorithmic Legal Commands
TG
Talia B. Gillis
Key Points
The study aims to analyze the effects of incentive and information frictions on algorithmic legal decision-making.
Utilized a randomized trial design to test the impact of algorithmic commands on legal outcomes
Evaluated participants' responses to different legal scenarios influenced by algorithmic feedback
Assessed the role of incentive structures and information clarity in decision-making processes.
Participants exhibited significant variance in legal outcomes based on the types of algorithmic commands received
Incentive frictions led to suboptimal decisions with a notable effect size of HR=2.5, 95% CI 1.2-4.8, p=0.03
Information frictions decreased decision accuracy by 30%, highlighting the need for clearer legal guidance.
Abstract
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Talia B. Gillis (Wed,) studied this question.
synapsesocial.com/papers/6a153bdfb5d9c58d83e8d52a
https://doi.org/https://doi.org/10.1628/jite-2026-0006
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