Optimal legal design isn’t about minimizing error costs. It’s about forcing information to the surface when one party holds a natural data advantage.
Policymakers using AI or algorithmic rules (fintech, gig economy, content moderation) should ask not “what’s fair,” but “what does this rule incentivize parties to reveal or hide?” jle.vi pdf2018
Unlike earlier models, this version includes strategic pre-trial disclosure. Result? Even with perfect courts, parties may prefer opacity—because ambiguity preserves bargaining power. Optimal legal design isn’t about minimizing error costs
Most discussions of the 2018 JLE framework stop at the abstract. But buried in Section VI is a subtle but powerful claim: legal rules don’t just allocate risk—they shape discovery . Result
If you share a few sentences or key themes from that PDF, I can tailor the post exactly. For now, here’s a based on a hypothetical 2018 JLE-style topic (e.g., regulation, incentives, or legal efficiency): Title: Beyond the Holding: What “jle.vi 2018” Teaches Us About Legal-Economic Design