The Difficult Reception of Rigorous Descriptive Social Science in the Law

Mutual disdain is an effective border patrol at the demarcation lines between disciplines. Social scientists tend to react with disdain when they observe how their findings are routinely stripped of all the caveats, assumptions and careful limitations once they travel into law. Likewise, lawyers tend to react with disdain when they read all the laborious proofs and checks for what looks to them like a minuscule detail in a much larger picture. But mutual disdain comes at a high price. All cross-border intellectual trade is stifled. This paper explores the social science/law border from the legal side. The natural barriers turn out to be significant, but not insurmountable. Specifically the paper looks at the challenges of integrating rigorous descriptive social science into the application of the law in force by courts and administrative authorities. This is where the gap is most difficult to bridge. The main impediments are implicit value judgments inherent in models, conceptual languages and strictly controlled ways of generating empirical evidence; the difference between explanation, hypothesis testing and prediction, on the one hand, and decision-making, on the other; the ensuing difference between theoretical and practical reasoning, and the judicial tradition of engaging in holistic thinking; last but not least, the strife of the legal system for autonomy, in order to maintain its viability. If a legal academic assumes the position of an outside observer, she may entirely ignore all these concerns and simply follow the methodological standards of descriptive social science. This is, for instance, what most of law and economics does. The legal academic may, instead, choose to contribute to the making of new law. She will then find it advisable to partly ignore the strictures of rigorous methodology in order to be open to more aspects of the regulatory issue. But it is not difficult, at least, to follow the standards of the social sciences for analysing the core problem. The integration is most difficult if an academic does doctrinal work. But it is precisely here where the division of intellectual labour between legal practice and legal academia is most important. Academics who themselves are versatile in the respective social science translate the decisive insights into suggestions for a better reading of statutory provisions or case law.law and economics, law and statistics, explanation vs. decision-making, practical reasoning, psychology of judicial decision-making

Expert Decision Making: A Fuzzy-Trace Theory Perspective

This is the author accepted manuscript. The final version is available from Routledge via the ISBN in this recor

Iudex Calculat: The ECJ's Quest for Power

Judicial Independence is a crucial aspect of the rule of law and the concept of separation of powers. It gives judges considerable leeway in interpreting and thereby modifying the constitution. In this paper, the role of the European Court of Justice (ECJ) as an actor in the strategic game played between the other actors on the European level as well as actors on the nation-state level (the respective governments, but also national courts, corporate actors and individuals) is inquired into. After describing the changes of the ECJs competence that have occurred since 1953, an attempt at explaining them is undertaken. It is shown that the ECJ has been able to bring about implicit constitutional change because its members are constrained less stringently than most supreme court judges on the nationstate level. It is furthermore shown that lower court judges have incentives to cooperate with the ECJ sometimes to the detriment of national supreme court judges.European Court of Justice, Economic Analysis of Court Behavior, Implicit and Explicit Constitutional Change, Preliminary Reference Procedure, Positive Constitutional Economics,

Machines Like Me: A Proposal on the Admissibility of Artificially Intelligent Expert Testimony

With the rapidly expanding sophistication of artificial intelligence systems, their reliability, and cost-effectiveness for solving problems, the current trend of admitting testimony based on artificially intelligent (AI) systems is only likely to grow. In that context, it is imperative for us to ask what rules of evidence judges today should use relating to such evidence. To answer that question, we provide an in-depth review of expert systems, machine learning systems, and neural networks. Based on that analysis, we contend that evidence from only certain types of AI systems meet the requirements for admissibility, while other systems do not. The break in admissible/inadmissible AI evidence is a function of the opaqueness of the underlying computational methodology of the AI system and the court’s ability to assess that methodology. The admission of AI evidence also requires us to navigate pitfalls including the difficulty of explaining AI systems’ methodology and issues as to the right to confront witnesses. Based on our analysis, we offer several policy proposals that would address weaknesses or lack of clarity in the current system. First, in light of the long-standing concern that jurors would allow expertise to overcome their own assessment of the evidence and blindly agree with the “infallible” result of advanced-computing AI, we propose that jury instruction commissions, judicial panels, circuits, or other parties who draft instructions consider adopting a cautionary instruction for AI-based evidence. Such an instruction should remind jurors that the AI-based evidence is solely one part of the analysis, the opinions so generated are only as good as the underlying analytical methodology, and ultimately, the decision to accept or reject the evidence, in whole or in part, should remain with the jury alone. Second, as we have concluded that the admission of AI-based evidence depends largely on the computational methodology underlying the analysis, we propose for AI evidence to be admissible, the underlying methodology must be transparent because the judicial assessment of AI technology relies on the ability to understand how it functions

On Logic in the Law: Something, but not All

In 1880, when Oliver Wendell Holmes (later to be a Justice of the U.S. Supreme Court) criticized the logical theology of law articulated by Christopher Columbus Langdell (the first Dean of Harvard Law School), neither Holmes nor Langdell was aware of the revolution in logic that had begun, the year before, with Frege\u27s Begriffsschrift. But there is an important element of truth in Holmes\u27s insistence that a legal system cannot be adequately understood as a system of axioms and corollaries ; and this element of truth is not obviated by the more powerful logical techniques that are now available

Small, alone and poor: a merciless portrait of insolvent French firms, 2007-2010

This empirical paper investigates the path to bankruptcy for a sample of French firms in default, in particular the decision to file a petition for bankruptcy, the arbitrage between rescuing and liquidation and the effective survival. The procedure is depicted as a sequence of three steps in which judges play a crucial role as they decide whether a company is insolvent or not and determine whether an insolvent company deserves to be rescued or, on the contrary, should be liquidated, the market having the last word since the effective success depends on the capability of the firm to recover from the judicial proceedings. We test different hypotheses about the variables influencing each possibility which include i) the role of the market in the firm's health, ii) the influence of financial structures, iii) the importance of corporate governance and iv) the inherent corporate factors of probable survival. Using three linked LOGIT models, our first finding is that the probability to default depends mainly on the market. Secondly the probability to be rescued depends essentially on the financial structure. Finally, the probability for the firm to remain in business in the long term is largely influenced by the market and profitability. Our results also support the idea that governance, size and resources are the main determinants of exit from the market or success of any company.Insolvency, bankruptcy, firm default, financial indicators, size, logit models.

The Hidden Inconsistencies Introduced by Predictive Algorithms in Judicial Decision Making

Algorithms, from simple automation to machine learning, have been introduced into judicial contexts to ostensibly increase the consistency and efficiency of legal decision making. In this paper, we describe four types of inconsistencies introduced by risk prediction algorithms. These inconsistencies threaten to violate the principle of treating similar cases similarly and often arise from the need to operationalize legal concepts and human behavior into specific measures that enable the building and evaluation of predictive algorithms. These inconsistencies, however, are likely to be hidden from their end-users: judges, parole officers, lawyers, and other decision-makers. We describe the inconsistencies, their sources, and propose various possible indicators and solutions. We also consider the issue of inconsistencies due to the use of algorithms in light of current trends towards more autonomous algorithms and less human-understandable behavioral big data. We conclude by discussing judges and lawyers' duties of technological ("algorithmic") competence and call for greater alignment between the evaluation of predictive algorithms and corresponding judicial goals