Artificial Intelligence and the Law

Regulation by design (RBD) is a growing research field that explores, develops, and criticises the regulative function of design. In this article, we provide a qualitative thematic synthesis of the existing literature. The aim is to explore and analyse RBD’s core features, practices, limitations, and related governance implications. To fulfil this aim, we examine the extant literature on RBD in the context of digital technologies. We start by identifying and structuring the core features of RBD, namely the goals, regulators, regulatees, (...) methods, and technologies. Building on that structure, we distinguish among three types of RBD practices: compliance by design, value creation by design, and optimisation by design. We then explore the challenges and limitations of RBD practices, which stem from risks associated with compliance by design, contextual limitations, or methodological uncertainty. Finally, we examine the governance implications of RBD and outline possible future directions of the research field and its practices. (shrink)

Artificial intelligence (AI) has transformed the way people engage with politics around the world: how citizens consume news, how they view the institutions and norms, how civic groups mobilize public interests, how data-driven campaigns are shaping elections, and so on (Ho & Vuong, 2024). Placing people at the center of the increasingly AI-mediated political landscape has become an urgent matter that transcends all forms of institutions. In this essay, we argue that, in this era, it is necessary to look beyond (...) certain limited notions of democracy and broaden our views of what it means to put people at the heart of political governance. Thus, we introduce some key features of a very, if not the most important concept, in East Asian political culture, ‘people as roots (of the state)’ or (dân bản in Vietnamese and 民本 in Chinese) . We propose that a more culturally sensitive analysis, which takes into account the diverse interpretations of people-centeredness within different political cultures, can provide valuable insights for researchers and leaders worldwide. Indeed, as the sociologist Shmuel Eisenstadt succinctly puts, modernity does not and should not correspond to Westernization. (shrink)

This chapter explores the influence of Artificial Intelligence (AI) on digital democracy, focusing on four main areas: citizenship, participation, representation, and the public sphere. It traces the evolution from electronic to virtual and network democracy, underscoring how each stage has broadened democratic engagement through technology. Focusing on digital citizenship, the chapter examines how AI can improve online engagement while posing privacy risks and fostering identity stereotyping. Regarding political participation, it highlights AI's dual role in mobilising civic actions and spreading misinformation. (...) Regarding representation, AI's involvement in electoral processes can enhance voter registration, e-voting, and the efficiency of result tabulation but raises concerns regarding privacy and public trust. Also, AI's predictive capabilities shift the dynamics of political competition, posing ethical questions about manipulation and the legitimacy of democracy. Finally, the chapter examines how integrating AI and digital technologies can facilitate democratic political advocacy and personalised communication. However, this also comes with higher risks of misinformation and targeted propaganda. (shrink)

In "Digital Doppelgängers and Lifespan Extension: What Matters?", Iglesias et al. argue that “some of the aims or ostensible goods of person-span expansion could plausibly be fulfilled in part by creating a digital doppelgänger”. Since person-extension aims are deeply heterogeneous, however, no single type of doppelgänger system is likely to suffice to meet all such needs. We propose a partial typology of doppelgängers—the family heirloom, the research archive, the public legacy, the project surrogate—and suggest appropriate training methods, design features and (...) governing norms for each. Finally, we reflect on the implications of concurrent yet heterogeneous doubles for questions of personal identity. (shrink)

Uno de los principios éticos mencionados más frecuentemente en los lineamientos para el desarrollo de la inteligencia artificial (IA) es la transparencia algorítmica. Sin embargo, no existe una definición estándar de qué es un algoritmo transparente ni tampoco es evidente por qué la opacidad algorítmica representa un reto para el desarrollo ético de la IA. También se afirma a menudo que la transparencia algorítmica fomenta la confianza en la IA, pero esta aseveración es más una suposición a priori que una (...) tesis basada en evidencia empírica. Tampoco se discute mucho hasta qué punto es técnicamente posible volver transparente la caja negra de la IA a través de los métodos de explicabilidad. En este capítulo haré un análisis de la interrelación entre los conceptos de transparencia, explicabilidad y confianza. Inicialmente, analizaré los diferentes tipos de opacidad algorítmica para entender mejor cuál es el problema al que nos enfrentamos. En las secciones subsiguientes trazaré la relación entre explicabilidad y transparencia, y presentaré los límites de los métodos actuales de explicabilidad. En la sección final, examinaré la evidencia empírica acerca de la relación entre transparencia y confianza en las decisiones automatizadas basadas en sistemas de IA. (shrink)

This paper provides a philosophically informed and robust account of the global justice implications of Artificial Intelligence (AI). We first discuss some of the key theories of global justice, before justifying our focus on the Capabilities Approach as a useful framework for understanding the context-specific impacts of AI on lowto middle-income countries. We then highlight some of the harms and burdens facing low- to middle-income countries within the context of both AI use and the AI supply chain, by analyzing the (...) extraction of materials, which includes mineral extraction and the environmental harms associated with it, and the extraction of labor, which includes unethical labor practices, low wages, and the trauma experienced by some AI workers. We then outline some of the potential harms and benefits that AI poses, how these are distributed, and what global justice implications this has for low- to middle-income countries. Finally, we articulate the global justice significance of AI by utilizing the Capabilities Approach. We argue that AI must be considered from a global justice perspective given that, globally, AI puts significant downward pressure on several elements of well-being thereby making it harder for people to achieve threshold levels of the central human capabilities needed for a life of dignity. (shrink)

Recently, the United Kingdom Supreme Court decided that only natural persons can be considered inventors. A year before, the United States Court of Appeals for the Federal Circuit issued a similar decision. In fact, so have many the courts all over the world. This Article analyses these decisions, argues that the courts got it right, and finds that artificial inventorship is at odds with patent law doctrine, theory, and philosophy. The Article challenges the intellectual property (IP) post-humanists, exposing the analytical (...) and normative perils of their argumentation, and recommends against getting rid of the nominally central place of humans in the law. This response to IP post-humanism rests in equal measure on patent doctrine, legal causation, and the mythology which creates and justifies the law. (shrink)

Generative AI technologies have the potential to be socially and politically transformative. In this paper, we focus on exploring the potential impacts that Generative AI could have on the functioning of our democracies and the nature of citizenship. We do so by drawing on accounts of deliberative democracy and the deliberative virtues associated with it, as well as the reciprocal impacts that social media and Generative AI will have on each other and the broader information landscape. Drawing on this background (...) theory, we outline some of the key positive and negative impacts that Generative AI is likely to have on democratic citizenship. The political significance of these impacts suggests the need for further regulation. (shrink)

This paper reviews the different meanings of vulnerability in the AI Act (AIA). We show that the AIA follows a rather established tradition of looking at vulnerability as a trait or a state of certain individuals and groups. It also includes a promising account of vulnerability as a relation but does not clarify if and how AI changes this relation. We spot the missing piece of the AIA: the lack of recognition that vulnerability is an inherent feature of all human-AI (...) interactions, varying in degree based on design choices and modes of interaction. Finally, we show how such a meaning of vulnerability may be incorporated into the AIA by interpreting the concept of “specific social situation” in Article 5 (b). (shrink)

As the geopolitical superpowers race to regulate the digital realm, their divergent rights-centered, market-driven, and social-control-based approaches require a global compact on digital regulation. If diverse regulatory jurisdictions remain, forms of domination entailed by cultural imposition and hermeneutical injustice related to AI legislation and AI systems will follow. We argue for consensual regulation on shared substantive issues, accompanied by proper standardization and coordination. Failure to attain consensus will fragment global digital regulation, enable regulatory capture by authoritarian powers or bad corporate (...) actors, and deepen the historical geopolitical power asymmetries between the global South and the global North. To prevent an unjust regulatory landscape where the global South’s cultural and hermeneutic resources are absent, two principles for the Global Digital Compact to counter these prospective harms are proposed and discussed: (1) “recognitive consensus on key substantive benefits and harms” and (2) “procedural consensus on global coordination and essential standards.”. (shrink)

The present narrative review seeks to unravel where we are now, and where we need to go to delineate the active ingredients in psychotherapy delivered by conversational agents (e.g., chatbots). While psychotherapy delivered by conversational agents has shown promising effectiveness for depression, anxiety, and psychological distress across several randomized controlled trials, little emphasis has been placed on the therapeutic processes in these interventions. The theoretical framework of this narrative review is grounded in prominent perspectives on the active ingredients in psychotherapy. (...) Based on search terms derived from various theoretical perspectives, we conducted a systematic literature search of four scientific databases and identified 17 studies. Across the selected studies, three themes emerged: relationship variables, emotional venting, and cognitive factors. While methodological issues compromise the epistemic value of this evidence base, core questions also remain to be answered. Such questions include, but are not limited to, whether humans can form affectionate bonds to inanimate beings and whether these kind of mental health treatments should be understood as psychotherapy or something else. Researchers should therefore be cautious when applying theories of psychotherapy in the realm of conversational agents. We conclude the paper by introducing recommendations for future research, which we hope will help instigate methodologically sound studies in this field. (shrink)

Algorithmic risk assessment tools, such as COMPAS, are increasingly used in criminal justice systems to predict the risk of defendants to reoffend in the future. This paper argues that these tools may not only predict recidivism, but may themselves causally induce recidivism through self-fulfilling predictions. We argue that such “performative” effects can yield severe harms both to individuals and to society at large, which raise epistemic-ethical responsibilities on the part of developers and users of risk assessment tools. To meet these (...) responsibilities, we present a novel desideratum on algorithmic tools, called explainability-in-context, which requires clarifying how these tools causally interact with the social, technological, and institutional environments they are embedded in. Risk assessment practices are thus subject to high epistemic standards, which haven't been sufficiently appreciated to date. Explainability-in-context, we contend, is a crucial goal to pursue in addressing the ethical challenges surrounding risk assessment tools. (shrink)

ChatGPT – a large language model – recently passed the U.S. bar exam. The startling rise and power of generative artificial intelligence (AI) systems such as ChatGPT lead us to consider whether and how more specialized systems could be used to overcome existing barriers to the legal system. Such systems could be employed in either of the two major stages of the pursuit of justice: preliminary information gathering and formal engagement with the state’s legal institutions and professionals. We focus on (...) the former and argue that developing and deploying publicly funded AI legal advisors can reduce economic and shame-based cultural barriers to the information-gathering stage of pursuing justice. (shrink)

The complexity and emergent autonomy of Generative AI systems introduce challenges in predictability and legal compliance. This paper analyses some of the legal and regulatory implications of such challenges in the European Union context, focusing on four areas: liability, privacy, intellectual property, and cybersecurity. It examines the adequacy of the existing and proposed EU legislation, including the Artificial Intelligence Act (AIA), in addressing the challenges posed by Generative AI in general and LLMs in particular. The paper identifies potential gaps and (...) shortcomings in the EU legislative framework and proposes recommendations to ensure the safe and compliant deployment of generative models. (shrink)

The article argues that AI can enhance the measurement and implementation of democratic processes within political parties, known as Intra-Party Democracy (IPD). It identifies the limitations of traditional methods for measuring IPD, which often rely on formal parameters, self-reported data, and tools like surveys. Such limitations lead to partial data collection, rare updates, and significant resource demands. To address these issues, the article suggests that specific data management and Machine Learning techniques, such as natural language processing and sentiment analysis, can (...) improve the measurement and practice of IPD. (shrink)

Regulation is nothing without enforcement. This particularly holds for the dynamic field of emerging technologies. Hence, this article has two ambitions. First, it explains how the EU´s new Artificial Intelligence Act (AIA) will be implemented and enforced by various institutional bodies, thus clarifying the governance framework of the AIA. Second, it proposes a normative model of governance, providing recommendations to ensure uniform and coordinated execution of the AIA and the fulfilment of the legislation. Taken together, the article explores how the (...) AIA may be implemented by national and EU institutional bodies, encompassing longstanding bodies, such as the European Commission, and those newly established under the AIA, such as the AI Office. It investigates their roles across supranational and national levels, emphasizing how EU regulations influence institutional structures and operations. These regulations may not only directly dictate the structural design of institutions but also indirectly request administrative capacities needed to enforce the AIA. (shrink)

The re-use of publicly available (personal) data for originally unanticipated purposes has become common practice. Without such secondary uses, the development of many AI systems like large language models (LLMs) and ChatGPT would not even have been possible. This chapter addresses the ethical implications of such secondary processing, with a particular focus on data protection and privacy issues. Legal and ethical evaluations of secondary processing of publicly available personal data diverge considerably both among scholars and the general public. While some (...) of these uses are met with opposition and criticism, others are quite unanimously viewed as unproblematic. Often, proponents and opponents of such practices invoke the same ethical and legal standards for their opposite conclusions. This state of affairs shows that other considerations besides the public availability of data must play a role. It calls for a theoretical clarification of the additional criteria that should guide decisions about the (legally informed) ethical acceptability of re-processing practices. In order to make a contribution towards this goal, the present chapter maps the ongoing debate and systematises the existing contributions around three lines of argument: a consent-centred position, an approach that focuses on the distinction between data and information, and finally a line of argument that focuses on the contextual norms that govern the flows of information. The chapter further relates these arguments to three underlying conceptions of privacy and data protection: rights-based, structural and contextual, and discusses the advantages and disadvantages of each position in the light of concrete examples. It concludes by arguing for a mixed approach that combines core elements of the structural and contextual approaches. The chapter aims to contribute to existing research in the fields of data, AI and research ethics, and to reconnect the debate with ethical and legal scholarship on privacy and data protection. In doing so, it aims to make a theoretical contribution towards refining existing conceptions of privacy and data protection in order to make them more fit to ‘drive our digital world’ as far as the use of publicly available data is concerned. (shrink)

Mark Coeckelbergh starts his book with a very powerful picture based on a real incident: On the 9th of January 2020, Robert Williams was wrongfully arrested by Detroit police officers in front of his two young daughters, wife and neighbors. For 18 hours the police would not disclose the grounds for his arrest (American Civil Liberties Union 2020; Hill 2020). The decision to arrest him was primarily based on a facial detection algorithm which matched Mr. Williams’ driving license photo with (...) the picture of a man who was suspected of watch theft two years earlier. Not only did the computer ‘get it wrong’ as one of the detectives said, when Mr. Williams made them aware that the picture of the suspect obviously wasn’t resembling him, the probably unreliable algorithm very likely contributed to racial discrimination (Hill 2020). It is well documented that many available facial detection algorithms at this time had significant problems (e.g. a comparably high false positive rate) with respect to black persons, like Mr. Williams (NIST 2019). Multiple causes may exist, such as unbalanced training datasets and insufficient optimization. Coeckelbergh compares the disturbing case of Mr. Williams with a political interpretation of Franz Kafka’s The Trial, where the protagonist, Josef K., is accused of an unspecified crime by an opaque, oppressive and absurd bureaucracy: “In the 21st-century United States, Josef K. is black and is falsely accused by an algorithm, without explanation” (p. 2). (shrink)

This book explores the use of artificial intelligence by intelligence services around the world and its critical role in intelligence analysis, defense, and national security. Intelligence services play a crucial role in national security, and the adoption of artificial intelligence technologies has had a significant impact on their operations. It also examines the various applications of artificial intelligence in intelligence services, the implications, challenges and ethical considerations associated with its use. The book emphasizes the need for continued research and development (...) in the field of artificial intelligence to ensure that intelligence services. and overall national defense and security can effectively adapt to emerging threats. -/- CONTENTS: -/- Abstract Introduction The evolution of AI Uses and applications Implications and advantages Strategies and implementation - A successful example: SABLE SPEAR Challenges and limitations Conclusion Bibliography -/- DOI: 10.58679/MM72104. (shrink)

Any moral algorithm for autonomous vehicles must provide a practical solution to moral problems of the trolley type, in which all possible courses of action will result in damage, injury, or death. This article discusses a hitherto neglected variety of this type of problem, based on a recent psychological study whose results are reported here. It argues that the most adequate solution to this problem will be achieved by a moral algorithm that is based on Confucian ethics. In addition to (...) this philosophical and psychological discussion, the article outlines the mathematics, engineering, and legal implementation of a possible Confucian algorithm. The proposed Confucian algorithm is based on the idea of making it possible to set an autonomous vehicle to allow an increased level of protection for selected people. It is shown that the proposed algorithm can be implemented alongside other moral algorithms, using either the framework of personal ethics settings or that of mandatory ethics settings. (shrink)

Protection of emergent works is impossible. Without an author, there is no expression of ideas which can be original, and thus no copyrightable work. Indeed, the whole system of copyright law, its conceptual building blocks of idea-expression dichotomy, originality, authorship, and the concept of a protectable work operate in the notation of human creativity. Emergent works fall outside of copyright’s positive ontology, being akin to ideas, facts, or subject-matter predicated by technical considerations, rather than authorial creativity. In other words, they (...) do not exist as things in law and thus cannot as such be owned. Rather, like any idea, they can be transformed through creative expression of an author–– possibly becoming works, but also not being authorless or emergent anymore. This is argued as a matter of the U.S. and EU legal doctrines, the international framework, and copyright theory. (shrink)

Digitalisation has lent the right to privacy increasing philosophical and legal relevance. However, privacy’s epistemic status and associated normative values are constantly subject to radical criticisms. This article investigates the validity, in theory and practice, of three radical critiques of privacy. A review of the philosophical and interdisciplinary discourse on privacy during the last half century is followed by analyses of recent legal developments within the EU. Privacy emerges as a highly differentiated and powerful tool to protect individuals and social (...) relations and to limit and redistribute power. However, the right to privacy remains far from realising its practical potential. (shrink)

While philosophers hold that it is patently absurd to blame robots or hold them morally responsible [1], a series of recent empirical studies suggest that people do ascribe blame to AI systems and robots in certain contexts [2]. This is disconcerting: Blame might be shifted from the owners, users or designers of AI systems to the systems themselves, leading to the diminished accountability of the responsible human agents [3]. In this paper, we explore one of the potential underlying reasons for (...) robot blame, namely the folk's willingness to ascribe inculpating mental states or "mens rea" to robots. In a vignette-based experiment (N=513), we presented participants with a situation in which an agent knowingly runs the risk of bringing about substantial harm. We manipulated agent type (human v. group agent v. AI-driven robot) and outcome (neutral v. bad), and measured both moral judgment (wrongness of the action and blameworthiness of the agent) and mental states attributed to the agent (recklessness and the desire to inflict harm). We found that (i) judgments of wrongness and blame were relatively similar across agent types, possibly because (ii) attributions of mental states were, as suspected, similar across agent types. This raised the question - also explored in the experiment - whether people attribute knowledge and desire to robots in a merely metaphorical way (e.g., the robot "knew" rather than really knew). However, (iii), according to our data people were unwilling to downgrade to mens rea in a merely metaphorical sense when given the chance. Finally, (iv), we report a surprising and novel finding, which we call the inverse outcome effect on robot blame: People were less willing to blame artificial agents for bad outcomes than for neutral outcomes. This suggests that they are implicitly aware of the dangers of overattributing blame to robots when harm comes to pass, such as inappropriately letting the responsible human agent off the moral hook. (shrink)

This publication forms a basis for the interdisciplinary development of a certification system for artificial intelligence. In view of the rapid development of artificial intelligence with disruptive and lasting consequences for the economy, society, and everyday life, it highlights the resulting challenges that can be tackled only through interdisciplinary dialogue between IT, law, philosophy, and ethics. As a result of this interdisciplinary exchange, it also defines six AI-specific audit areas for trustworthy use of artificial intelligence. They comprise fairness, transparency, autonomy (...) and control, data protection as well as security and reliability while addressing ethical and legal requirements. The latter are further substantiated with the aim of operationalizability. (shrink)

Die vorliegende Publikation dient als Grundlage für die interdisziplinäre Entwicklung einer Zertifizierung von Künstlicher Intelligenz. Angesichts der rasanten Entwicklung von Künstlicher Intelligenz mit disruptiven und nachhaltigen Folgen für Wirtschaft, Gesellschaft und Alltagsleben verdeutlicht sie, dass sich die hieraus ergebenden Herausforderungen nur im interdisziplinären Dialog von Informatik, Rechtswissenschaften, Philosophie und Ethik bewältigen lassen. Als Ergebnis dieses interdisziplinären Austauschs definiert sie zudem sechs KI-spezifische Handlungsfelder für den vertrauensvollen Einsatz von Künstlicher Intelligenz: Sie umfassen Fairness, Transparenz, Autonomie und Kontrolle, Datenschutz sowie Sicherheit und (...) Verlässlichkeit und adressieren dabei ethische und rechtliche Anforderungen. Letztere werden mit dem Ziel der Operationalisierbarkeit weiter konkretisiert. (shrink)

Book review of "Killing by remote Control," Bradley Jay Strawser (Ed), Oxford university Press.