People who live under a rule of law typically want their laws to work. At their strongest, laws cause people to refrain from doing what they otherwise would have done and act in favor of the law. This is “legal constraint.” If a law doesn’t do what is intended, there is a good chance that it is because of a failure of constraint. When people knowingly commit crimes, they have failed to be legally constrained. When judges reach results they favor because they did not pay due regard to the law that applies to their cases, they have failed to be constrained too. This is why political commentators frequently complain that a law “lacks teeth” or that judges are “activists.” But legal constraint is not just the stuff of political sniping. Legal philosophers, too, have a keen interest in it. In this chapter, I will first discuss how the insights of twentieth-century jurisprudence set the parameters for the empirical study of legal constraint. Thereafter, I will show how experimental methods are particularly well suited to this study. Finally, I will review the literature in experimental jurisprudence that bears upon legal constraint.

The complexity involved in developing and deploying artificial intelligence (AI) systems in high-stakes scenarios may result in a “liability gap,” under which it becomes unclear who is responsible when things go awry. Scholarly and policy debates about the gap and its potential solutions have largely been theoretical, with little effort put into understanding the general public’s views on the subject. In this chapter, we present two empirical studies exploring laypeople’s perceptions of responsibility for AI-caused harm. First, we study the proposal to grant legal personhood to AI systems and show that it may conflict with laypeople’s policy preferences. Second, we investigate how people divide legal responsibility between users and developers of machines in a variety of situations and find that, while both are expected to pay legal damages, laypeople anticipate developers to bear the largest share of the liability in most cases. Our examples demonstrate how empirical research can help inform future AI regulation and provide novel lines of research to ensure that this transformative technology is regulated and deployed in a more democratic manner.

Determining proximate causation is crucial for decisions about legal liability, but how judges select proximate causes is a notoriously disputed issue. Knobe and Shapiro (2020) recently argued that the perceived (ab)normality of causal factors explains both laypeople’s and legal experts’ causal selection patterns. While a large body of psychological research shows that people indeed often select abnormal factors as most important, this research has focused on a very narrow set of scenarios: two simultaneously occurring but independent causes that either conjunctively or disjunctively bring about some outcome. We here explore whether normality also guides causal selection in structures that may be more typical of many legal scenarios: successively occurring causes that are themselves causally connected (causal chains). Comparing effects of both statistical and prescriptive abnormality on causal selection in chains, we only find a tendency to select abnormal causes for manipulations of prescriptive but not statistical normality. Moreover, judgments about the counterfactual relevance of causes or about their suitability as targets of intervention were only moderately correlated with causal selection patterns. The interplay between causal structure and different kinds of (ab)normality in people’s reasoning about proximate causation may thus be more complex than is currently recognized.

As part of the legal test for bias, the courts have created a fictional fair-minded observer (the FMO) to act as a conduit for reasonable public perception. A number of scholars have raised concerns that the FMO bears no resemblance to an average member of the public or reasonably reflects general public opinion. This chapter presents our original empirical pilot study on expert versus lay attitudes to judicial bias. The study compares responses of legal insiders (lawyers and judges) and nonlegal experts with a basic understanding of the law (law students) to leading cases on judicial recusal. We use vignettes based on real cases from England, Australia, and Canada that dealt with different claims of judicial bias (covering issues of race, prejudgment, and more). The study may allow us to draw conclusions about the similarities and differences between legal experts and laypeople in relation to the perception of judicial bias, and we suggest ways the full study can address methodological limitations in the pilot that would allow us to draw those conclusions with greater confidence.

Legal outcomes often depend on whether conduct is reasonable. But how do we judge what is reasonable? What are the relevant criteria? Legal theorists have long debated these questions. This chapter outlines some of the leading theories. It then describes recent experimental work probing whether those theories align with lay judgments of what is reasonable. The findings indicate that reasonableness is best understood as a hybrid concept – a product of multiple inputs. Working from this perspective, the chapter raises important additional questions about reasonableness – questions that experimental jurisprudence is well suited to explore.

This research paper aims to experimentally analyze how iusnaturalist and iuspositivist legal theories influence legal operators’ decisions when there are conflicts between law and morality, as well as to show that they interact and are codependently defined by other cognitive variables as a complex system.

Corporatism refers to the tradition of constitutional theories that argue that self-organized bodies, such as universities, churches, or labour unions, are independent and important components of a constitutional order. While in the twentieth-century corporatism became associated primarily with economic actors, a central question in corporatist theory was the broader constitutional status of non-state associations and organizations that had their own political powers to govern their members and engage in quasi-legislative activity. In arguing for the independent legitimacy of such diverse corporate actors, proponents of corporatism were united in criticizing more liberal visions of constitutionalism for its abstraction and formalism. Many corporatist theorists thus advocated a sort of societal constitutionalism, where constitutional norms are embodied in diverse institutions that are more proximate to individuals than the state – ranging from major professional and economic associations to a variety of civil society groups. This chapter analyses corporatism both as a tradition in constitutional theory and as an empirical phenomenon that arose in the interwar and post-war periods. It argues that corporatist ideas can contribute to a theory of democratic constitutionalism that emphasizes the importance of organized collective power, and not just the problem of regulating state coercion or distributing formal rights.