Three Laws Blog: Law and Artificial Intelligence

Zeleznikow on Whether Artificial Intelligence and Online Dispute Resolution Can Enhance Efficiency and Effectiveneness In Courts @VicUniWgtn

John Zeleznikow, Victoria University, is publishing Can Artificial Intelligence and Online Dispute Resolution Enhance Efficiency and Effectiveness in Courts in volume 8 of International Journal for Court Administration (May 2017). Here is the abstract.

The growing rise in the number of self-represented litigants has negative implications for both the court system and access to justice. The expanding use of Artificial Intelligence and the World Wide Web has led to the development and use of Online Dispute Resolution. In this article, we investigate a number of systems in Australian Family Law that enhance Alternative Dispute Resolution and Access to Justice. We discuss how a hybrid system that incorporates advice about Best Alternatives to Negotiated Agreements (BATNAs) and potential trade-offs as well as allowing online communication can enhance access to justice.

Download the article from SSRN at the link.

Alschner and Skougarevskiy on Whether Robots Can Write Treaties @w_alschner

Wolfgang Alschner, University of Ottawa, Common Law Section, and Dmitriy Skougarevskiy, Graduate Institute of International and Development Studies (IHEID), Department of Economics, Students; European University at St. Petersburg (EUSP), have published Can Robots Write Treaties? Using Recurrent Neural Networks to Draft International Investment Agreements at JURIX: Legal Knowledge and Information Systems 119 (F. Bex and S. Villata, eds., IOS Press, 2016).

Negotiating international investment agreements is costly, complex, and prone to power asymmetries. Would it then not make sense to let computers do part of the work? In this contribution, we train a character-level recurrent neural network (RNN) to write international investment agreements. Benefiting from the formulaic nature of treaty language, the RNN generates texts of lawyer-like quality on the article-level, but fails to compose treaties in a legally sensible manner. By embedding RNNs in a user-controlled pipeline we overcome this problem. First, users can specify the treaty content categories ex ante on which the RNN is trained. Second, the pipeline allows a filtering of output ex post by identifying output that corresponds most closely to a user-selected treaty design benchmark. The result is an improved system that produces meaningful texts with legally sensible composition. We test the pipeline by comparing predicted treaties to actually concluded ones and by verifying that our filter captures latent policy preferences by predicting the outcome of current investment treaty negotiations between China and the United States.

Download the essay from SSRN at the link.

Hildebrandt on Law As Computation in the Era of Artificial Legal Intelligence: Speaking Law To the Power of Statistics @mireillemoret

Mireille Hildebrandt, Vrije Universiteit Brussel; Radboud University, has published Law As Computation in the Era of Artificial Legal Intelligence. Speaking Law to the Power of Statistics. Here is the abstract.

The idea of artificial legal intelligence stems from a previous wave of artificial intelligence, then called jurimetrics. It was based on an algorithmic understanding of law, celebrating logic as the sole ingredient for proper legal argumentation. However, as Holmes noted, the life of the law is experience rather than merely logic. Machine learning, which determines the current wave of artificial intelligence, is built on a data-driven machine experience. The resulting artificial legal intelligence may be far more successful in terms predicting the content of positive law. In this article, I discuss the assumptions of law and the rule of law and confront them with those of computational systems. As a twin paper to my Chorley lecture on Law as Information, this should inform the extent to which artificial legal intelligence provides for responsible innovation in legal decision making.

Download the article from SSRN at the link.