MDLs rely, for legitimacy, on the notion that the individual litigant calls the shots. That fact justifies a system that affords MDL litigants few, if any, safeguards, even while furnishing class members in class actions elaborate procedural protections. In this Chapter, we zero in on litigant autonomy in MDLs. We explain why autonomy matters, dissect its components, and evaluate how much autonomy MDL litigants seem to have in practice. We then turn to a necessary component of that autonomy: information. We review data from a recent survey indicating litigants felt confused and uninformed regarding their suits. In light of that evidence, we assess what transferee courts are doing to keep litigants up-to-date and well informed. We then furnish the results of our own empirical analysis of court-run MDL websites, which are often extolled, including by judges, as a key venue for client-court communication. Unfortunately, our analysis reveals deep and pervasive deficits with respect to usability and relevance. If this is where case-related communication is supposed to be happening, then litigant confusion is unsurprising. We close with recommendations for courts seeking to harness simple technology to promote better communication. Improved MDL websites aren’t a panacea. But they might promote the autonomy interests of litigants—and light a path for future reform.

Court-connected ODR has already shown itself capable of dramatically improving access to justice by eliminating barriers rooted in the fact that courts traditionally resolve disputes only during certain hours, in particular physical places, and only through face-to-face proceedings. Given the centrality of courthouses to our system of justice, too many Americans have discovered their rights are too difficult or costly to exercise. As court-connected ODR systems spread, offering more inclusive types of dispute resolution services, people will soon find themselves with the law and the courts at their fingertips. But robust access to justice requires more than just raw, low-cost opportunities to resolve disputes. Existing ODR platforms seek to replicate in-person procedures, simplifying and clarifying steps where possible, but litigants without representation still proceed without experience, expertise, guardrails, or the ability to gauge risk or likely outcomes. Injecting ODR with a dose of data science has the potential to address many of these shortfalls. Enhanced ODR is unlikely to render representation obsolete, but it can dramatically reduce the gap between the “haves” and the “have nots” and, on some dimensions—where machines can outperform humans—next generation platforms may be a significant improvement.

The legal services market is commonly thought of as divided into two “hemispheres”—PeopleLaw, which serves individuals and small businesses, and BigLaw, which serves corporated clients. The last few decades have seen an increasing concentration of resources within the legal profession toward the latter, to the alleged detriment of the former. At the same time, the costs of accessing legal representation exceed the financial resources of many ordinary citizens and small businesses, compromising their access to the legal system. We ask: Will the adoption of new digital technologies lead to a levelling of the playing field between the PeopleLaw and BigLaw sectors? We consider this in three related dimensions. First, for users of legal services: Will technology deliver reductions in cost sufficient to enable affordable access to the legal system for consumer clients whose legal needs are currently unmet? Second, for legal services firms: Will the deployment of technology to capture economies of scale mean that firms delivering legal services across the two segments become more similar? And third, for the structure of the legal services market: Will the pursuit of economies of scale trigger consolidation that leads both segments toward a more concentrated market structure?

Smart cities require trusted governance and engaged citizens, especially governance of intelligence and intelligence-enabled control. In some very important respects, smart cities should remain dumb, and that will take governance. This introduction provides an overview of the book’s aims, structure, and contributions of individual chapters.

This case study focuses on smart tech deployment and governance in Philadelphia. In 2019, the City of Philadelphia launched a new smart city initiative, SmartCityPHL. SmartCityPHL includes a roadmap of strategies, processes, and plans for deployment. In many ways, the new initiative is remarkable. It is ambitious yet pragmatic; it outlines a set of guiding principles along with deliberative and participatory processes; it is broadly inclusive of people and values – as reflected in its simple definition of a smart city: “a city that uses integrated information and communication technology to support the economic, social, and environmental goals of its community.” On its face, and perhaps in comparison with other smart city initiatives, SmartCityPHL provides an exciting roadmap. But the 2019 initiative was not the first smart city project in Philadelphia. There is, in fact, a long history of Philadelphians turning to supposedly smart technology to solve community problems.

This chapter outlines a forward-looking, intelligent approach to thinking through and evaluating supposedly smart systems. First, it clarifies that it is not the city that is smart. Rather, smartness is better understood and evaluated in terms of affordances supposedly smart tools provide actual people. Who gains what kinds of intelligence? For what purposes? Subject to what governance? Second, it identifies and addresses key challenges to intelligent governance in smart city projects. Cities must move beyond a transactional mindset, appreciate how smart systems become an integral part of the built environment, and develop appropriate governance. Third, it proposes an approach to smart city governance grounded in local, contextual norms and scaffolded by key questions to ask throughout smart city planning, procurement, implementation, and management processes. This approach is importantly not oriented around Elinor Ostrom’s famous design principles, but rather a shared set of evaluative questions to guide decision-making.

Natural language processing techniques promise to automate an activity that lies at the core of many tasks performed by lawyers, namely the extraction and processing of information from unstructured text. The relevant methods are thought to be a key ingredient for both current and future legal tech applications. This chapter provides a non-technical overview of the current state of NLP techniques, focusing on their promise and potential pitfalls in the context of legal tech applications. It argues that, while NLP-powered legal tech can be expected to outperform humans in specific categories of tasks that play to the strengths of current ML techniques, there are severe obstacles to deploying these tools in other contexts, most importantly in tasks that require the equivalent of legal reasoning.

Compared to other highly skilled labour markets, the legal profession has been slow to adopt technological changes, but lawyers have been downright speedy compared to courts. Courts already generate voluminous amounts of data, but restrict access to it. The private sector, recognizing how legal data can help its clients, willingly incurs the costs to gather this data and develop proprietary tools to analyze it. As this trend continues, access to justice will worsen, further benefitting wealthier clients over opposing litigants as well as the courts, for no other reason than that courts will lag in their ability to efficaciously decide judicial matters. The judiciary—across all levels—could reverse this trend. The first step is to develop a more robust institutional framework for making court data publicly available. The second step is a willingness among courts to analyze this data when issuing decisions, both procedural and sustantive. Doing so requires courts to develop core competencies in existing and emerging legal technology. Democratizing access to judicial data will diminish the advantage currently enjoyed by affluent litigants, but accrue to the benefit of everyone else—including courts themselves.

This chapter examines the case of institutional design for urban data governance in the City of Seattle as a collective action problem, referencing three prominent theoretical frameworks for examining institutional change and institutional economics. This work centers on the Governing Knowledge Commons (GKC) framework, which is adapted from Elinor Ostrom’s Institutional Analysis and Development (IAD) framework for natural resource commons and developed to study institutional arrangements for overcoming various social dilemmas associated with sharing and producing information, innovation, and creative works. Furthermore, this chapter notes the foundational integration of the IAD framework with Oliver Williamson’s transaction cost economics (TCE), highlighting the role of transaction costs in understanding the externalities associated with the governance of data.

Although proponents of online dispute resolution systems proclaim that their innovations will expand access to justice for so-called “simple cases,” evidence of how the technology actually operates and who is benefitting from it demonstrates just the opposite. Resolution of some disputes may be more expeditious and user interface more intuitive. But in order to achieve this, parties generally do not receive meaningful information about their rights and defenses. The opacity of the technology (ODR code is not public and unlike court appearance its proceedings are private) means that due process defects and systemic biases are difficult to identify and address. Worse still, the “simple cases” argument for ODR assumes that the dollar value of a dispute is a reasonable proxy for its complexity and significance to the parties. This assumption is contradicted by well established research on procedural justice. Moreover, recent empirical studies show that low money value cases, which dominate state court dockets, are for the most part debt collection proceedings brought by well-represented private creditors or public creditors (including courts themselves, which increasingly depend on fines and fees for their operating budget). Defendants in these proceedings are overwhelmingly unrepresented individuals. What ODR offers in these settings is not access to justice for ordinary people, but rather a powerful accelerated collection and compliance technology for private creditors and the state. This chapter examines the design features of ODR and connects them to the ideology of tech evangelism that drives deregulation and market capture, the aspirations of the alternative dispute resolution movement, and hostility to the adversary system that has made strange bedfellows of traditional proponents of access to justice and tech profiteers. The chapter closes with an analysis of front-end standards for courts and bar regulators to consider to ensure that technology marketed in the name of access to justice actually serves the legal needs of ordinary people.

Pittsburgh is arguably one of the great twentieth-century urban success stories, but in the twenty-first century, Pittsburgh is unexceptional. That makes Pittsburgh a good case for examining governance of smart city technology, because Pittsburgh is neither behind some imaginary urban technology curve nor ahead of it. Like many cities, it doesn’t aspire to be celebrated as a “smart city”; instead, it merely hopes to do well, even to thrive. Pittsburgh has steadily accumulated and deployed a broad range of technology systems as part of its public administration practice, celebrating its advances as often and as much as it might. The case study documents what might be referred to as “ordinary” or “normal” governance of smart city technology and governance via smart city technology. The chapter offers a broad historical take on ICTs and smart technologies in Pittsburgh. It also dives more deeply into some specific examples. Its research and presentation are pluralistic in tone, style, and method.

Smart cities require much more than smart tech. Cities need trusted governance and engaged citizens. Integrating surveillance, AI, automation, and smart tech within basic infrastructure, as well as public and private services and spaces, raises a complex set of ethical, economic, political, social, and technological questions that requires systematic study and careful deliberation. Throughout this book, authors have asked contextual research questions and explored compelling but often distinct answers guided by the shared structure of the GKC framework. The Conclusion discusses some of the key themes across chapters in this volume, considering lessons learned and implications for future research.