Volume 2026, No. 1 – Wisconsin Law Review – UW–Madison

Table of Contents Articles Contract Law and Civil Justice in Local Courts Cathy Hwang & Justin Weinstein-Tull Most American contract law disputes take place in the shadows, unnoticed by commentators, scholars, and casebooks. These disputes—often heard by lay judges in local courts that do not publish their opinions—account for more than 80 percent of total contract disputes. Using state-level filing data and original interviews with local court judges, this Article unearths, for the first time, this vitally important yet understudied world. Our findings provide a blueprint for new research on local courts and contract law, with wide-ranging implications for theory and practice. This Article makes three contributions to the literature. First, we identify what we call “values-driven adjudication.” Through interviews, we find that local court judges know relatively little about legal concepts like unconscionability, parol evidence, and canons of construction—principles that scholars, lawyers, and students have always believed form the basis of contract law adjudication. Instead, local court judges rely on broader values of fairness, commitment to mediation, fidelity to law (as they understand the law to be), and community norms. Second, while values-driven adjudication might cause concern at first glance, we find that many of the broader ideas local judges instinctively rely on vindicate contract law’s underlying values. Local judges may not know the contours of the doctrine of unconscionability, for example, but they do care that contracts are fair. They may not know that efficiency motivates some contract law doctrines, but they do attempt to mediate contract law disputes in ways that avoid appeals. Finally, we consider the wide-ranging implications of these findings for contract theory, contract design, civil justice, and judicial education, and we call for more research on this shrouded but vitally important world of local courts. Preempting Drug Price Reform Shweta Kumar Over the past decade, a number of states have attempted to lower prescription drug costs. State efforts to regulate drug prices range from price gouging laws to drug importation, pharmacy benefit manager regulations, and price transparency efforts. Prescription Drug Affordability Boards (PDABs) in particular have recently become popular, with at least twelve states having enacted PDAB legislation and seventeen more now considering the same. PDABs are state-established entities that assess the affordability of high-cost prescription drugs, and some have authority to set upper payment limits (UPLs) on those drugs. However, most of the costliest drugs that are subject to PDAB review enjoy patent and FDA market exclusivities afforded by federal law. As such, the UPLs set by PDABs have triggered concerns about preemption by the federal patent and drug regulatory regimes. In 2024, Amgen, the manufacturer of ENBREL, a drug selected for review by the Colorado PDAB, challenged the constitutionality of the Colorado PDAB. Amgen presented patent preemption as one of its key arguments, arguing that permitting a state to limit the prices of patented drugs impermissibly interferes with the design and objectives of federal patent law. While the district court dismissed the challenge for lack of standing, the case is currently on appeal to the Federal Circuit. This case presents the Federal Circuit with a rare opportunity to revisit its interpretation of the scope of patent preemption from a prior holding—Biotechnology Industry Organization v. District of Columbia (BIO v. D.C.), in which the court held that a D.C. law that prohibited the sale of patented prescription drugs at an “excessive price” was preempted because it created an unconstitutional obstacle to the rewards and incentives established by Congress under the Patent Act. This Article argues that PDABs are currently the strongest state-level intervention to address the public health crisis precipitated by high prescription drug prices—and are therefore essential. Lessons Learned? COVID’s Continued Impact on Remote Work Disability Accommodations D’Andra Millsap Shu One bright spot in the devastation of the COVID-19 pandemic is broader acceptance of remote work. Although disabled people are still underemployed compared to the rest of the population, they are currently working at record levels—due directly to remote work allowing more of them to enter the labor force. But significantly more disabled workers need to work remotely and are unable to secure that accommodation. Eager to “return to normal” and do away with remote work, many employers are denying remote work requests, even from disabled workers who cannot otherwise do their jobs. Historically, employers have been able to deny remote work accommodation requests with near impunity from courts, which overwhelmingly sided with employers. Courts often did so based on faulty evidentiary practices, such as assuming that only exceedingly rarely could any job be done at home. But COVID laid that assumption bare. Commentators and scholars speculate that COVID’s mass remote work experiment will surely change how courts assess claims based on denying remote work accommodation requests. But is that speculation accurate? This Article presents data to answer that question. It provides empirical analysis based on all 151 federal remote work accommodation cases from 2023 and 2024. In some small respects, courts have changed their ways, but far too many are still making the same mistakes in analyzing these claims—even with all COVID has taught us. Many courts, it seems, have not learned any lessons. Unbundling AI Openness Parth Nobel, Alan Z. Rozenshtein & Chinmayi Sharma The debate over AI openness—whether to make components of an artificial intelligence system available for public inspection and modification—forces policymakers to balance innovation, democratized access, safety, and national security. By inviting startups and researchers into the fold, it enables independent oversight and inclusive collaboration. But technology giants can also use it to entrench their own power, while adversaries can use it to shortcut years and billions of dollars in building systems, like China’s DeepSeek, that rival our own. How we govern AI openness today will shape the future of AI and America’s role in it. Policymakers and scholars grasp the stakes of AI openness, but the debate is trapped in a flawed premise: that AI is either “open” or “closed.” This dangerous oversimplification—inherited from the world of open source software—belies the complex calculus at the heart of AI openness. Unlike traditional software, AI is a composite technology built on a stack of discrete components—from compute to labor—controlled by different stakeholders with competing interests. Each component’s openness is neither a binary choice nor inherently desirable. Effective governance demands a nuanced understanding of how the relative openness of each component serves some goals while undermining others. Only then can we determine the trade-offs we are willing to make and how we hope to achieve them. This Article aims to equip policymakers with the analytical toolkit to do just that. First, it introduces a novel taxonomy of “differential openness,” untangling AI into its constituent components and illustrating how each one has its own spectrum of openness. Second, it uses this taxonomy to systematically analyze how each component’s relative openness necessitates intricate trade-offs both within and between policy goals. Third, it operationalizes these insights by advancing a research agenda that shows how law can be analyzed and refined to support more precise configurations of component openness. AI openness is neither all or nothing nor inherently good or evil—it is a tool that must be wielded with precision if it has any hope of serving the public interest.