Ho, Huang & Chang on Machine Learning Comparative Law

Han‐Wei Ho (IIAS), Patrick Chung-Chia Huang (U Chicago Law, students), and Yun-chien Chang (IIAS) have posted “Machine Learning Comparative Law” (Cambridge Handbook of Comparative Law, Siems and Yap eds. (2023)) on SSRN. Here is the abstract:

Comparative lawyers are interested in similarities between legal systems. Artificial intelligence offers a new approach to understanding legal families. This chapter introduces machine-learning methods useful in empirical comparative law, a nascent field. This chapter provides a step-by-step guide to evaluating and developing legal family theories using machine-learning algorithms. We briefly survey existing empirical comparative law data sets, then demonstrate how to visually explore these using a data set one of us compiled. We introduce popular and powerful algorithms of service to comparative law scholars, including dissimilarity coefficients, dimension reduction, clustering, and classification. The unsupervised machine-learning method enables researchers to develop a legal family scheme without the interference from existing schemes developed by human intelligence, thus providing as a powerful tool to test comparative law theories. The supervised machine-learning method enables researchers to start with a baseline scheme (developed by human or artificial intelligence) and then extend it to previously unstudied jurisdictions.

Colangelo on European Proposal for a Data Act – A First Assessment

Giuseppe Colangelo (University of Basilicata; Stanford Law School; LUISS) has posted “European Proposal for a Data Act – A First Assessment” (CERRE Evaluation Paper 2022) on SSRN. Here is the abstract:

On 23 February 2022, the European Commission unveiled its proposal for a Data Act (DA). As declared in the Impact Assessment, the DA complements two other major instruments shaping the European single market for data, such as the Data Governance Act and the Digital Markets Act (DMA), and is a key pillar of the European Strategy for Data in which the Commission announced the establishment of EU-wide common, interoperable data spaces in strategic sectors to overcome legal and technical barriers to data sharing.

To contribute to the current policy debate, the paper provides a first assessment of the tabled DA and will suggest possible improvements for the ongoing legislative negotiations.