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Quantitative recidivism risk assessment can be used at the pretrial detention, trial, sentencing, and / or parole stage in the justice system. It has been criticized for what is measured, whether the predictions are more accurate than those made by humans, whether it creates or increases inequality and discrimination, and whether it compromises or violates other aspects of fairness. This criticism becomes even more topical with the arrival of the Artificial Intelligence (AI) Act. This article identifies and applies the relevant rules of the proposed AI Act in relation to quantitative recidivism risk assessment. It does so by focusing on the proposed rules for the quality of the data and the models used, on biases, and on the human oversight. It is concluded that legislation may consider requiring providers of high-risk AI systems to demonstrate that their solution performs significantly better than risk assessments based on simple models, and better than human assessment. Furthermore, there is no single answer to evaluate the performance of quantitative recidivism risk assessment tools that are or may be deployed in practice. Finally, three approaches of human oversight are discussed to correct for the negative effects of quantitative risk assessment: the optional, benchmark, and feedback approach.

AbstractThis research examines the impact of Chinese cultural values on the application of law on contractual damages. Following an experimental design, 43 in-depth interviews were conducted with Chinese judges in 13 cities and provinces across China. The data reveal two patterns. First, the judges took the cultural values into account when determining the amount of damages. Second, the consideration of cultural value factors reduced the judges' consideration of legal factors. The local cultural values did not change the Chinese judges' understanding of law. Instead, the judges compromised the legal requirements and cultural desires by using the discretion offered to them or by recommending mediation. The consideration of cultural values is not only the result of judges' personal preferences, but also of judges seeking social approval. The motivation of Chinese judges to obtain social approval may be enhanced by the assessment criteria and the institutional constraints of Chinese courts.

In this article, we test the extent to which decisions by the Ecuadorian Constitutional Court (ECC) are predicted by non-legal variables. Our theoretical argument proposes that not only the presence of public actors as plaintiffs—especially those working for the executive branch—but also political salience, i.e., the degree of importance attributed to a case by the government and public opinion, plays a crucial role in explaining the outcome of judicial decisions. Original data on all abstract review decisions issued by the ECC (2008–2016) is used to test our argument. We control for possible selection effects, incorporating a novel measure of the overall quality of argumentation and strength of cases brought before the ECC by both public and private parties, in the form of an expert survey. Consistent with our argument, the results show that even when controlling for a wide range of potential confounders, norms are more likely to be struck down by the ECC when (1) public officials claim unconstitutionality than when non-public parties do, and (2) cases are reported by media. In the light of the Ecuadorian case, we conclude that the formally powerful ECC is quite sensitive to governmental influence, even under an improved situation of de jure judicial protections.

This contribution explores the application of data science and artificial intelligence to legal research, more specifically an element that has not received much attention: the research infrastructure required to make such analysis possible. In recent years, EU law has become increasingly digitised and published in online databases such as EUR-Lex and HUDOC. However, the main barrier inhibiting legal scholars from analysing this information is lack of training in data analytics. Legal analytics software can mitigate this problem to an extent. However, current systems are dominated by the commercial sector. In addition, most systems focus on search of legal information but do not facilitate advanced visualisation and analytics. Finally, free to use systems that do provide such features are either too complex to use for general legal scholars, or are not rich enough in their analytics tools. In this paper, we motivate the case for building a software platform that addresses these limitations. Such software can provide a powerful platform for visualising and exploring connections and correlations in EU case law, helping to unravel the "DNA" behind EU legal systems. It will also serve to train researchers and students in schools and universities to analyse legal information using state-of-the-art methods in data science, without requiring technical proficiency in the underlying methods. We also suggest that the software should be powered by a data infrastructure and management paradigm following the seminal FAIR (Findable, Accessible, Interoperable and Reusable) principles.

This article reports the results of a comparative empirical legal study that analyzed (1) strategic behaviour by actors in insolvencies that is salient to insolvency judges and (2) how insolvency judges respond to such behaviour. After examining four different European countries, namely Italy, the Netherlands, Poland, and Portugal, the study reveals how differences regarding case allocation, judge – insolvency practitioner (IP) interaction, and remuneration and case financing can result in strategic behaviour on both the side of the judges and the IPs. From this, it follows that improving the efficiency and effectiveness is not merely a matter of implementing legislation and case law, but that it also requires a look into the dynamics between insolvency judges, IPs, and other actors in the insolvency process.

This article reports the results of a comparative empirical legal study that analyzed (1) strategic behaviour by actors in insolvencies that is salient to insolvency judges and (2) how insolvency judges respond to such behaviour. After examining four different European countries, namely Italy, the Netherlands, Poland, and Portugal, the study reveals how differences regarding case allocation, judge – insolvency practitioner (IP) interaction, and remuneration and case financing can result in strategic behaviour on both the side of the judges and the IPs. From this, it follows that improving the efficiency and effectiveness is not merely a matter of implementing legislation and case law, but that it also requires a look into the dynamics between insolvency judges, IPs, and other actors in the insolvency process.