An Evidence-Based Approach to Private Ordering

Abstract

Private ordering – where private actors regulate, enforce, and resolve disputes on their own – has in recent years expanded across business, commercial, and financial sectors. Parties have economic and reputational incentives to take this approach over adjudication by the courts. Parties may prefer private ordering for reasons of process, substance, or both. Even when disputes come before them, courts often defer to parties’ private ordering. Their rationale is that the parties possess a stronger understanding of their intentions than do the courts. This strong assumption, however, depends on parties’ knowledge and relative bargaining strength. In many instances, parties operate under incomplete or imperfect information; additional information could allow parties to enter into more efficient and more fair agreements ex ante, while better informing courts’ approach to adjudicating disputes arising from private ordering ex post. The emergence of artificial intelligence (AI) in legal technology – specifically, in its ability to analyse vast amounts of data – can help advance this augmented informational objective. If made broadly accessible, AI has the potential to equalize information and bargaining power between parties. An empirical evaluation of the validity of assumptions that underpin the general support for private ordering can also be instructive for judges. For this reason, courts have an important role to play in the evolution of private law. Their ability to understand and harness AI can lead in the short term to more effective judicial oversight with respect to private ordering. Over the long term, courts can empower parties to make more informed choices when interacting with one another, reducing inefficiencies and rents.