Houman B. Shadab (New York Law School) has posted “Metasoftware: Building Blocks for Legal Technology” on SSRN. Here is the abstract:

This Article develops a novel concept in information technology called metasoftware. It then applies the concept of metasoftware to developing legal technology.

Metasoftware enables users to create the software of their choosing and stands in sharp contrast to traditional, functional software that is intended for a particular purpose or a defined range of tasks. Functional software is the default type of software that is currently produced and includes word processing, email, social networking, enterprise resource management, online marketplaces, and video game software. Metasoftware, by contrast, is not functional. Metasoftware presents the user with a blank slate upon which to build functional software.

I argue that software is metasoftware to that extent that (1) it enables users to build user interface elements, workflow logic, and perform database operations, (2) provides connectivity with external data and software systems, and (3) is able to be stored and run independently from the platform that is used to build the software. In its purest form, metasoftware enables its users to build any functional software (given the existing state of technology), integrate with all open software platforms, and be hosted and run in the environment of the user’s choosing without being bound to a particular vendor or other proprietary software platform.

My identification of metasoftware contributes to the academic literature on information systems (and technology). Metasoftware is a hitherto unrecognized category of software for analysis in terms of several foundational lines of information technology research including user acceptance and usage, diffusion within an organization, and impact on organizational innovation and success (e.g., business performance).

I analyze three types of metasoftware platforms to determine how metasoftware characteristics are implemented in each and important inherent tradeoffs. These platforms are those closely tied to major producers of cloud-based software platforms, standalone proprietary “no code” software builder platforms, and open source visual development platforms.

This Article also describes how metasoftware platforms can be used to build functional legal technology and analyzes how the tradeoffs between different types of metasoftware platforms turn impact how each type of platform should be approached as building blocks for legaltech software. I focus on four major categories of legaltech as illustrative of the potential for metasoftware to build functional software: legal research, legal matter management, contract automation, and a variety of applications of artificial intelligence.

Jesús Fernández-Villaverde (U Penn – Depart of Econ; NBER) has posted “Has Machine Learning Rendered Simple Rules Obsolete?” on SSRN. Here is the abstract:

Epstein (1995) defended the superiority of simple legal rules over complex, human-designed regulations. Has Epstein’s case for simple rules become obsolete with the arrival of artificial intelligence, and in particular machine learning (ML)? Can ML deliver better algorithmic rules than traditional simple legal rules? This paper argues that the answer to these question is “no.” I will build an argument based on three increasingly more serious barriers that ML faces to develop legal (or quasi-legal) algorithmic rules: data availability, the Lucas’ critique, and incentive compatibility in eliciting information. Thus, the case for simple legal rules is still sound even in a world with ML.

Recommended.

Matthijs M. Maas (University of Cambridge) has posted “Aligning AI Regulation to Sociotechnical Change” on SSRN. Here is the abstract:

How do we regulate a changing technology, with changing uses, in a changing world? This chapter argues that while existing (inter)national AI governance approaches are important, they are often siloed. Technology-centric approaches focus on individual AI applications; law-centric approaches emphasize AI’s effects on pre-existing legal fields or doctrines. This chapter argues that to foster a more systematic, functional and effective AI regulatory ecosystem, policy actors should instead complement these approaches with a regulatory perspective that emphasizes how, when, and why AI applications enable patterns of ‘sociotechnical change’. Drawing on theories from the emerging field of ‘TechLaw’, it explores how this perspective can provide informed, more nuanced, and actionable perspectives on AI regulation.

A focus on sociotechnical change can help analyze when and why AI applications actually do create a meaningful rationale for new regulation — and how they are consequently best approached as targets for regulatory intervention, considering not just the technology, but also six distinct ‘problem logics’ that appear around AI issues across domains. The chapter concludes by briefly reviewing concrete institutional and regulatory actions that can draw on this approach in order to improve the regulatory triage, tailoring, timing & responsiveness, and design of AI policy.

Daniel J. Gervais (Vanderbilt University – Law School) has posted “The Human Cause” on SSRN. Here is the abstract:

This paper argues that, although AI machines are increasingly able to produce outputs that facially qualify for copyright or patent protection, such outputs should not be protected by law when they have no identifiable human cause, that is, when the autonomy of the machine is such that it breaks the causal link between the output and one or more human creators or inventors. As a species, normatively we should seek to preserve incentives for human creativity and inventiveness, as these have been hallmarks of the higher mental faculties often used to define humanness. The paper also discussed situation where human and machines work together and how courts can apply the proposed approach.

Recommended.

Shaun Lim (National University of Singapore (NUS) – Faculty of Law) has posted “Judicial Decision-Making and Explainable Artificial Intelligence” ((2021) 33 Singapore Academy of Law Journal 280) on SSRN. Here is the abstract:

In light of rapid developments in legal technology, it is timely to begin considering whether, and if so how, artificial intelligence (AI) can replace judges. However, given that law plays a crucial role in maintaining societal order, that judges are a crucial part of ensuring the continued well-functioning of the law, and also that there are still many unknowns in the use and deployment of AI, it would be prudent to examine and understand exactly what roles judges play in the legal system, and how they do so, before we make any bold steps towards replacing judges with AI. This article examines the current and reasonably foreseeable state of AI to consider its capabilities, as well as the process by which judges make decisions and the duties they are subject to. This article will then consider whether or how AI, given its current and foreseeable state of development, may be used in judicial decision-making, and what safeguards may be required to ensure continued confidence in a well-functioning justice system.

Sofia Ranchordas (University of Groningen, Faculty of Law; Yale Law School – Information Society Project) has posted “Experimental Regulations for AI: Sandboxes for Morals and Mores” on SSRN. Here is the abstract:

Recent EU legislative and policy initiatives aim to offer flexible, innovation-friendly, and future-proof regulatory frameworks. Key examples are the EU Coordinated Plan on AI and the recently published EU AI Regulation Proposal which refer to the importance of experimenting with regulatory sandboxes so as to balance innovation in AI against its potential risks. Originally developed in the Fintech sector, regulatory sandboxes create a testbed for a selected number of innovative projects, by waiving otherwise applicable rules, guiding compliance, or customizing enforcement. Despite the burgeoning literature on regulatory sandboxes and the regulation of AI, the legal, methodological, and ethical challenges of regulatory sandboxes have remained understudied. This exploratory article delves into the some of the benefits and intricacies of employing experimental legal instruments in the context of the regulation of AI. This article’s contribution is twofold: first, it contextualizes the adoption of regulatory sandboxes in the broader discussion on experimental approaches to regulation; second, it offers a reflection on the steps ahead for the design and implementation of AI regulatory sandboxes.

Roxana Vatanparast (Harvard Kennedy School; University of Turin) has posted “The Code of Data Capital: A Distributional Analysis of Law in the Global Data Economy” (juridikum 1/2021 98-110 (2021)) on SSRN. Here is the abstract:

The data economy has become an integral part of the global economy. It plays a fundamental role in issues of economic distribution and inequality, which has much to do with the legal arrangements and entitlements that shape it. Yet data and data-driven technologies are often conceptualized in terms that do not seem adequate to capture the role they play in global distribution, or which overlook the law as a key mechanism shaping distributional outcomes. Using a law and political economy approach, this article argues that conceiving of data as capital that is coded by legal mechanisms allows new ways of imagining alternative distributions of the value it generates in the global economy today. The article maps some of the legal entitlements that shape the global data economy and its distributive effects, as well as proposals for alternatives. It concludes that analyses of the distributive effects of the global data economy ought to take into account the fundamental roles that both law and technology play in shaping those effects.

Michael A. Livermore (University of Virginia School of Law), Peter Beling (University of Virginia, Dept. of System & Information Engineering), Keith Carlson (Dartmouth College), Faraz Dadgostari (University of Virginia), Mauricio Guim (Instituto Tecnológico Autónomo de México (ITAM) – Law School), and Daniel Rockmore (Dartmouth College – Department of Mathematics; Dartmouth College – Department of Computer Science) have posted “Law Search In The Age Of The Algorithm” (2020 MICH. ST. L. REV. 1183) on SSRN. Here is the abstract:

The process of searching for relevant legal materials is fundamental to legal reasoning. However, despite its enormous practical and theoretical importance, law search has not been given significant attention by scholars. In this Article, we define the problem of law search and examine the consequences of new technologies capable of automating this core lawyerly task. We introduce a theory of law search in which legal relevance is a sociological phenomenon that leads to convergence over a shared set of legal materials and explore the normative stakes of law search. We examine ways in which law scholars can understand empirically the phenomenon of law search, argue that computational modeling is a valuable epistemic tool in this domain, and report the results from a multi-year, interdisciplinary effort to develop an advanced law search algorithm based on human-generated data. Finally, we explore how policymakers can manage the challenges posed by new machine learning-based search technologies.

Recommended.

Monika Zalnieriute (University of New South Wales – Faculty of Law) has posted “”Transparency-Washing” In The Digital Age: A Corporate Agenda of Procedural Fetishism” (Critical Analysis of Law, 8(1) 2021, Forthcoming) on SSRN. Here is the abstract:

Contemporary discourse on the regulation and governance of the digital environment has often focused on the procedural value of transparency. This article traces the prominence of the concept of transparency in contemporary regulatory debates to the corporate agenda of technology companies. Looking at the latest transparency initiatives of IBM, Google and Facebook, I introduce the concept of “transparency-washing,” whereby a focus on transparency acts as an obfuscation and redirection from more substantive and fundamental questions about the concentration of power, substantial policies and actions of technology behemoths. While the “ethics-washing” of the tech giants has become widely acknowledged, “transparency washing” presents a wider critique of corporate discourse and neoliberal governmentality based on procedural fetishism, which detracts from the questions of substantial accountability and obligations by diverting the attention to procedural micro-issues that have little chance of changing the political or legal status quo.

Frank A. Pasquale (Brooklyn Law School) has posted “The Resilient Fragility of Law” (Foreword to “Is Law Computable?: Critical Perspectives on Law and Artificial Intelligence” (Simon Deakin & Christopher Markou, eds., Hart Publishing, 2020)) on SSRN. Here is the abstract:

Are current legal processes computable? Given known limitations of computing likely to continue into the near and medium-term future, the answer for all but the simplest processes is: no. Should they become more computable? Some processes could benefit from further algorithmatization, statistical analysis, and quantitative valuation, but context is critical. For reductionist projects in computational law and legal automation (particularly those that seek to replace, rather than complement, legal practitioners), traces of the legal process are all too often mistaken for the process itself. The words in a complaint and an opinion, for instance, are taken to be the essence of the proceeding, and variables gleaned from decisionmakers’ past actions and affiliations are further used to predict their future actions. Such behavioristic approaches undervalue the resilient fragility of law—that is, the capacity of persons and institutions to creatively interpret language, reframe disputes, and find new patterns of cooperation. In diverse ways, the chapters in this volume reclaim and revalue law’s resilient fragility, identifying labor and judgment as the irreplaceable center of a humane legal system.