Three Laws

Chesterman on From Ethics to Law: Why, When, and How to Regulate AI @ProfChesterman @nus_law @Elgar_Law

Simon Chesterman, National University of Singapore Faculty of Law, is publishing From Ethics to Law: Why, When, and How to Regulate AI in The Handbook of the Ethics of AI (David J. Gunkel, ed., Edward Elgar Publishing, forthcoming). Here is the abstract.

The past decade has seen a proliferation of guides, frameworks, and principles put forward by states, industry, inter- and non-governmental organizations to address matters of AI ethics. These diverse efforts have led to a broad consensus on what norms might govern AI. Far less energy has gone into determining how these might be implemented — or if they are even necessary. This chapter focuses on the intersection of ethics and law, in particular discussing why regulation is necessary, when regulatory changes should be made, and how it might work in practice. Two specific areas for law reform address the weaponization and victimization of AI. Regulations aimed at general AI are particularly difficult in that they confront many ‘unknown unknowns’, but the threat of uncontrollable or uncontainable AI became more widely discussed with the spread of large language models such as ChatGPT in 2023. Additionally, however, there will be a need to prohibit some conduct in which increasingly lifelike machines are the victims — comparable, perhaps, to animal cruelty laws.

Download the essay from SSRN at the link.

Banchio on Reflections on a Legal Framework for Artificial Intelligence

Pablo Rafael Banchio, Facultad Interamericana de Ciencias Sociales (FICS), is publishing Reflections on a Legal Framework for Artificial Intelligence in Revista Doctrina Jurídica; Rivista Giurisprudenza e Diritto Comparato. Here is the abstract.

Objective: Dedicated to the preliminary exposition of the specificity of the legal regulation of the use and development of artificial intelligence, the analysis of various approaches to its definition and the peculiarities of the existing legislative initiatives to enshrine a comprehensive normative regulation of these technologies. Methods: Qualitative and with explanatory scope. Qualitative of the phenomenon to be studied in a comprehensive manner because it allows us to understand the complex world of artificial intelligence from the perspective of law. Explanatory because it focuses on explaining the phenomenon of virtual assistants and the need for regulatory capture; under what conditions it manifests itself, how it is created and how it gives meaning centered on people's lives. Other methods used are formal-logical and comparative-legal. Results: Conclusions are formulated on how to shape legislative support for the use and development of artificial intelligence in a coherent way, considering the specificity of its specific fields of application and balancing the interests of individuals, society, and the state. To respect adequate security and protection of individual rights and interests associated with the development of innovation for the benefit of society, enshrining a supreme principle of justice through universal, comprehensive, and anticipatory regulation. Scientific novelty: There is currently a global problem of an almost total absence of normative regulation, both legal and technical, of the foundations, conditions and peculiarities of the development, launch, operation, integration into other systems and control of the application of artificial intelligence technologies. Practical significance: Artificial intelligence is currently developing intensively, and we are participants in the gradual incorporation of virtual assistants into our lives to facilitate daily activities. An appropriate legal framework will facilitate this insertion, avoid risks associated with the new technologies under development and ensure that individual rights are respected and enforced.

Download the article from SSRN at the link.

Kaminski on Regulating the Risks of AI @MargotKaminski @BULawReview

Margot E. Kaminski, University of Colorado Law School; Yale Information Society Project; University of Colorado, Boulder, Silicon Flatirons Center for Law, Technology, and Enterprise, is publishing Regulating the Risks of AI in volume 103 of the Boston University Law Review. Here is the abstract.

Companies and governments now use Artificial Intelligence (AI) in a wide range of settings. But using AI leads to well-known risks—that is, not yet realized but potentially catastrophic future harms that arguably present challenges for a traditional liability model. It is thus unsurprising that lawmakers in both the United States and the European Union (EU) have turned to the tools of risk regulation for governing AI systems. This Article observes that constructing AI harms as risks is a choice with consequences. Risk regulation comes with its own policy baggage: a set of tools and troubles that have emerged in other fields. Moreover, there are at least four models for risk regulation, each with divergent goals and methods. Emerging conflicts over AI risk regulation illustrate the tensions that emerge when regulators employ one model of risk regulation, while stakeholders call for another. This Article is the first to examine and compare a number of recently proposed and enacted AI risk regulation regimes. It asks whether risk regulation is, in fact, the right approach. It closes with suggestions for addressing two types of shortcomings: failures to consider other tools in the risk regulation toolkit (including conditional licensing, liability, and design mandates), and shortcomings that stem from the nature of risk regulation itself (including the inherent difficulties of non-quantifiable harms, and the dearth of mechanisms for public or stakeholder input).

Download the article from SSRN at the link.

Brownsword on We the Robots? Regulating Artificial Intelligence and the Limits of the Law by Simon Chesterman (Book Review) @KCL_Law @ProfChesterman

Roger Brownsword, King's College London School of Law, has published Book Review: We the Robots? Regulating Artificial Intelligence and the Limits of the Law by Simon Chesterman at 2022 Singapore Journal of Legal Studies 252. Here is the abstract.

Debates about the law, regulation, and governance of robots, artificial intelligence ('AI'), and machine learning have been dominated by voices from North America, Europe, and Australia. While Singapore has hosted conferences at which these matters have been discussed, and while it is clearly an interested party in relation to these debates, a distinctively Singaporean voice has yet to be heard—or, at any rate, it had not been heard prior to the publication of Simon Chesterman’s stimulating book.

Download the review from SSRN at the link.

Craig on The Relational Robot: A Normative Lens for AI Legal Normality (Review of Ryan Abbott, The Reasonable Robot) @craigcarys @DrRyanAbbott

Carys Craig, Osgoode Hall Law School, is publishing The Relational Robot: A Normative Lens for AI Legal Neutrality (Reviewing Ryan Abbott, The Reasonable Robot, Cambridge University Press, 2020) in the Jerusalem Review of Legal Studies (2022). Here is the abstract.

In his impactful book, "The Reasonable Robot" (Cambridge UP, 2020), Ryan Abbott proposes a new guiding tenet for the law’s regulation of Artificial Intelligence: AI legal neutrality. This would establish, as a principled starting point, the default position that “the law should not discriminate between AI and human behaviour.” In this Review Essay, I suggest that AI legal neutrality, as conceived by Abbott, is an interesting proposition but a potentially dangerous default principle with which to equip law for the emerging realities of AI. When we scratch beneath the surface, this concept of neutrality or equal treatment is too focused on the individual person/thing, and too reliant on analogical reasoning and false equivalence. It is therefore too far removed from the normative underpinnings of law, its subjects, and its teleology. Instead, I argue, we need a more substantive notion of law’s technological neutrality—one that looks to the law’s normative objectives to set the default. The place to start, I suggest, is not with a legal neutrality that, by design, disregards the inherent differences between humans and robots and their respective behaviors; on the contrary, we need to be fully attentive to the dynamics of human-robot relations in social context – and alert to the dangers of overlooking differences. Rights and responsibilities should be allocated with a clear view to the relationships and subjectivities they shape and the social values they advance. In Part II, I outline Abbott’s argument in respect of legal neutrality and its application to intellectual property law. I then compare its implications in the patent law sphere to its potential significance in the copyright context. In Part III, I sketch an alternative approach to understanding technological neutrality and law, concerned with consistency in pursuit of normative objectives rather than formal non-discrimination between technologies. I conclude by proposing a relational approach to regulating robots, which would, I believe, bring a much-needed normative lens to the pursuit of legal neutrality.

Download the review from SSRN at the link.

Kop on the EU Artificial Intelligence Act: The European Approach to AI @AIRechtNL @StanfordLaw

Mauritz Kop, Stanford Law School; AIRecht, has published EU Artificial Intelligence Act: The European Approach to AI. Here is the abstract.

On 21 April 2021, the European Commission presented the Artificial Intelligence Act. This Stanford Law School contribution lists the main points of the proposed regulatory framework for AI. The draft regulation seeks to codify the high standards of the EU trustworthy AI paradigm. It sets out core horizontal rules for the development, trade and use of AI-driven products, services and systems within the territory of the EU, that apply to all industries. The EU AI Act introduces a sophisticated ‘product safety regime’ constructed around a set of 4 risk categories. It imposes requirements for market entrance and certification of High-Risk AI Systems through a mandatory CE-marking procedure. This pre-market conformity regime also applies to machine learning training, testing and validation datasets. The AI Act draft combines a risk-based approach based on the pyramid of criticality, with a modern, layered enforcement mechanism. This means that as risk increases, stricter rules apply. Applications with an unacceptable risk are banned. Fines for violation of the rules can be up to 6% of global turnover for companies. The EC aims to prevent the rules from stifling innovation and hindering the creation of a flourishing AI ecosystem in Europe, by introducing legal sandboxes that afford breathing room to AI developers. The new European rules will forever change the way AI is formed. Pursuing trustworthy AI by design seems like a sensible strategy, wherever you are in the world.

Download the article from SSRN at the link.

Cyman, Gromova, and Juchnevicius on Regulation of AI in BRICS and the EU

D. Cyman, Elizaveta Gromova, and E. Juchnevicius have published Regulation of Artificial Intelligence in BRICS and the European Union at 8 BRICS Law Journal 86 (2021). Here is the abstract.

Global digitization and the emergence of Artificial Intelligence-based technologies pose challenges for all countries. The BRICS and European Union countries are no exception. BRICS as well as the European Union seek to strengthen their positions as leading actors on the world stage. At the present time, an essential means of doing so is for BRICS and the EU to implement smart policy and create suitable conditions for the development of digital technologies, including AI. For this reason, one of the most important tasks for BRICS and the EU is to develop an adequate approach to the regulation of AI-based technologies. This research paper is an analysis of the current approaches to the regulation of AI at the BRICS group level, in each of the BRICS countries, and in the European Union. The analysis is based on the application of comparative and formal juridical analysis of the legislation of the selected countries on AI and other digital technologies. The results of the analysis lead the authors to conclude that it is necessary to design ageneral approach to the regulation of these technologies for the BRICS countries similar to the approach chosen in the EU (the trustworthy approach) and to upgrade this legislation to achieve positive effects from digital transformation. The authors offer several suggestions for optimization of the provisions of the legislation, including designing a model legal act in the sphere of AI.

Download the article from SSRN at the link.

Marchant, Tournas, and Gutierrez on Governing Emerging Technologies Through Soft Law: Lessons For AI @GaryMarchant1

Gary E. Marchant, Lucille Tournas, and Carlos Ignacio Gutierrez, all of the Arizona State University College of Law, are publishing Governing Emerging Technologies Through Soft Law: Lessons for Artificial Intelligence in volume 61 of Jurimetrics (2020).

Artificial Intelligence (AI) is positioned to be a foundational technology in most industrial sectors, societal interactions, as well as in many other technological advantages. AI is rapidly evolving with the promise of bettering our businesses, keeping us safer, and transforming us into a better society. At the same time, we know there will be concerns, some anticipated, and many that will develop alongside the technology itself. Its ubiquitous nature and rapid pace of development make traditional governance structures difficult to impose. However, there are a number of “soft-law” or non-legally binding tools that offer the flexibility needed to foster innovation safely.

Download the article from SSRN at the link.

Karen Hao on How We Lost Control of Our Faces

From MIT Technology Review:

Karen Hao, This Is How We Lost Control of Our Faces: The largest ever study of facial-recognition data shows how much the rise of deep learning has fueled a loss of privacy. 

 

Smuha on Going Beyond a Human Rights-Based Approach to AI Governance @NathalieSmuha

Nathalie A. Smuha, Faculty of Law, KU Leuven, has published Beyond a Human Rights-based approach to AI Governance: Promise, Pitfalls, Plea

This paper discusses the establishment of a governance framework to secure the development and deployment of “good AI”, and describes the quest for a morally objective compass to steer it. Asserting that human rights can provide such compass, this paper first examines what a human rights-based approach to AI governance entails, and sets out the promise it propagates. Subsequently, it examines the pitfalls associated with human rights, particularly focusing on the criticism that these rights may be too Western, too individualistic, too narrow in scope and too abstract to form the basis of sound AI governance. After rebutting these reproaches, a plea is made to move beyond the calls for a human rights-based approach, and start taking the necessary steps to attain its realisation. It is argued that, without elucidating the applicability and enforceability of human rights in the context of AI; adopting legal rules that concretise those rights where appropriate; enhancing existing enforcement mechanisms; and securing an underlying societal infrastructure that enables human rights in the first place, any human rights-based governance framework for AI risks falling short of its purpose.

Download the article from SSRN at the link.