Legislating Neuroscience: The Case of Juvenile Justice

Neuroscientific evidence is increasingly being introduced in legal contexts, and neurolaw scholarship is correspondingly on the rise. Yet absent from neurolaw research to date are extended examinations of neuroscience in legislative domains. This Article begins to fill that gap with a focus on the illustrative case of neuroscience and juvenile justice in state legislatures. Such examination reveals distinctions between lab neuroscience, lobbyist neuroscience, and legislator neuroscience. As neuroscience narratives are constructed in the policy stream, normative questions arise. Without courtroom evidentiary rules to guide the use of neuroscience in legislatures, these questions are complicated. For instance, to what extent should lobbyists and legislators adhere to the complexities and caveats of laboratory science? How much should lawmakers simplify and reformulate the scientific findings to achieve desired policy ends? The Article argues that the construction of neuroscience narratives is necessary and desirable, but if the narratives diverge too greatly from actual research findings, they may ultimately undermine the efficacy of the neuroscience in policymaking

Neuroscience, Artificial Intelligence, and the Case Against Solitary Confinement

Prolonged solitary confinement remains in widespread use in the United States despite many legal challenges. A difficulty when making the legal case against solitary confinement is proffering sufficiently systematic and precise evidence of the detrimental effects of the practice on inmates\u27 mental health. Given this need for further evidence, this Article explores how neuroscience and artificial intelligence (AI) might provide new evidence of the effects of solitary confinement on the human brain. This Article argues that both neuroscience and AI are promising in their potential ability to present courts with new types of evidence on the effects of solitary confinement on inmates\u27 brain circuitry. But at present, neither field has collected the type of evidence that is likely to tip the scales against solitary confinement and end the practice. This Article concludes that ending the entrenched practice of solitary confinement will likely require both traditional and novel forms of evidence. In exploring the potential effects of neuroscientific evidence on support for solitary confinement, the Article reports results from an Associate Professor of Law and McKnight Presidential Fellow, University original online experiment with a group of 250 ideologically conservative participants. The analysis finds that the introduction of brain injury reduced conservatives\u27 support for solitary confinement but not to the extent that is likely to make a policy impact. The Article argues that future, more individualized brain evidence may be of greater use, but at present neuroscience is limited in its ability to systematically measure the brain changes that inmates experience in solitary confinement. This Article then turns to AI and argues that it could be developed to provide litigators and inmates with the ability to more effectively document the detrimental effects of solitary confinement. Looking to the future, the Article lays out a vision for an AI system called Helios, named after the Homeric sun god believed to see and hear everything. The Article envisions Helios as a self-learning AI system with a mission to help inmates and their attorneys gather more systematic evidence of the effects of solitary confinement on inmate health. Helios is also a platform on which additional inmate services might one day be provided. The Article describes how Helios must be carefully designed, with particular attention given to privacy concerns. This Article is organized in seven parts. Part I describes the historical and contemporary use of solitary confinement in the United States, highlighting the known effects of solitary confinement on inmates. Part II summarizes recent constitutional challenges to the practice of solitary confinement. Part III explores the potential for integrating neuroscientific evidence into these legal challenges to solitary confinement. Part IV discusses a new online experiment to explore whether neuroscience might change public opinion on solitary confinement. In Part V, the Article transitions to a consideration of AI. The Article proposes a self-learning system, Helios, and describes how the system would operate. Part VI turns to a series of challenging ethical and legal questions about the design and implementation of Helios. Part VII briefly concludes

Brain Scans as Evidence: Truths, Proofs, Lies, and Lessons

This contribution to the Brain Sciences in the Courtroom Symposium identifies and discusses issues important to admissibility determinations when courts confront brain-scan evidence. Through the vehicle of the landmark 2010 federal criminal trial U.S. v. Semrau (which considered, for the first time, the admissibility of brain scans for lie detection purposes) this article highlights critical evidentiary issues involving: 1) experimental design; 2) ecological and external validity; 3) subject compliance with researcher instructions; 4) false positives; and 5) drawing inferences about individuals from group data. The article’s lessons are broadly applicable to the new wave of neurolaw cases now being seen in U.S. courts

The Failure of Youth Sports Concussion Laws and the Limits of Legislating Health Education

Legislatures have increasingly turned to education-based strategies to address significant public health challenges, despite unclear efficacy of statutory mandated education. In this Article, we examine the recent and rapid adoption of youth sports concussion laws as a lens to explore the limits of education based legislative intervention models. In less than 10 years, all 50 states adopted a youth sports concussion statute—and each law mandates concussion education for coaches and/or student athletes. This expansive, expensive intervention was designed to reduce concussion incidence and improve concussion care. But based on a review of 54 peer-reviewed studies, we argue that concussion education has not, and likely will not, produce the desired public health outcomes

Sorting Guilty Minds

Because punishable guilt requires that bad thoughts accompany bad acts, the Model Penal Code (MPC) typically requires that jurors infer the past mental state of a criminal defendant. More specifically, jurors must sort that mental state into one of four specific categories - purposeful, knowing, reckless, or negligent - which in turn defines the nature of the crime and the extent of the punishment. The MPC therefore assumes that ordinary people naturally sort mental states into these four categories with a high degree of accuracy, or at least can reliably do so when properly instructed. It also assumes that ordinary people will order these categories of mental state, by increasing amount of punishment, in the same severity hierarchy that the MPC prescribes. The MPC, now turning 50 years old, has previously escaped the scrutiny of comprehensive empirical research on these assumptions underlying its culpability architecture. Our new empirical studies, reported here, find that most of the mens rea assumptions embedded in the MPC are reasonably accurate as a behavioral matter. Even without the aid of the MPC definitions, subjects were able to regularly and accurately distinguish among purposeful, negligent, and blameless conduct. Nevertheless, our subjects failed to distinguish reliably between knowing and reckless conduct. This failure can have significant sentencing consequences in some types of crimes, especially homicide

Decoding Guilty Minds

A central tenet of Anglo-American penal law is that in order for an actor to be found criminally liable, a proscribed act must be accompanied by a guilty mind. While it is easy to understand the importance of this principle in theory, in practice it requires jurors and judges to decide what a person was thinking months or years earlier at the time of the alleged offense, either about the results of his conduct or about some elemental fact (such as whether the briefcase he is carrying contains drugs). Despite the central importance of this task in the administration of criminal justice, there has been very little research investigating how people go about making these decisions, and how these decisions relate to their intuitions about culpability. Understanding the cognitive mechanisms that govern this task is important for the law, not only to explore the possibility of systemic biases and errors in attributions of culpability but also to probe the intuitions that underlie them. In a set of six exploratory studies reported here, we examine the way in which individuals infer others’ legally relevant mental states about elemental facts, using the framework established over fifty years ago by the Model Penal Code (“MPC”). The widely adopted MPC framework delineates and defines the four now-familiar culpable mental states: purpose, knowledge, recklessness, and negligence. Our studies reveal that with little to no training, jury-eligible Americans can apply the MPC framework in a manner that is largely congruent with the basic assumptions of the MPC’s mental state hierarchy. However, our results also indicate that subjects’ intuitions about the level of culpability warranting criminal punishment diverge significantly from prevailing legal practice; subjects tend to regard recklessness as a sufficient basis for punishment under circumstances where the legislatures and courts tend to require knowledge