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New paper: testing legal decision-making at scale

30 October 2018 by John Pearson

Today, our paper on legal decision-making goes online at Nature Human Behaviour. You can read more about the genesis of the project here. Briefly, we used a large-scale survey approach based on randomly generated legal cases to show three things:

1. It’s possible to estimate (using Bayesian hierarchical models) how groups of individuals weight different types of legal evidence, even when not all individuals see not all of the evidence combinations.
2. Prospective jurors (mTurk participants) assigned some weight to the accusation itself. That is, they rated these cases as a little convincing even when no evidence for guilt was presented. The more seriousness the crime, the higher that rating.
3. Participants with legal training focused entirely on the evidence, but their overall ratings of case strength were still correlated with how serious the crime was.

We think this is the start of a pretty interesting line of research. It’s by no means the end of the story, and follow-up studies are in progress. But we’re excited at the potential to bring this kind of “high-throughput” statistical approach to an important social question. We see it as a complement to traditional approaches like laboratory experiments, interviews, and mock trials.

Coverage at Duke Research, reposted at futurity.org.

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