Regulation of Robotics & AI

The political dimensions of robotic surgery encompass challenges such as public perception, team dynamics, and the organizational hurdles of implementing advanced technologies. Successful programs navigate three phases: the "Hype Phase," marked by steep learning curves; the "Trough of Disillusionment," involving confidence challenges; and "Establishing a New Normal," where true program value is realized. Key strategies include fostering high-performing teams, honest communication, and selecting supportive hospital environments to ensure sustainable progress and quality outcomes.

Rapid technological advancements in Artificial Intelligence (AI), as well as the growing deployment of intelligent technologies in new application domains, have generated serious anxiety and a fear of missing out among different stake-holders, fostering a racing narrative. Whether real or not, the belief in such a race for domain supremacy through AI, can make it real simply from its consequences, as put forward by the Thomas theorem. These consequences may be negative, as racing for technological supremacy creates a complex ecology of choices that could push stake-holders to underestimate or even ignore ethical and safety procedures. As a consequence, different actors are urging to consider both the normative and social impact of these technological advancements, contemplating the use of the precautionary principle in AI innovation and research. Yet, given the breadth and depth of AI and its advances, it is difficult to assess which technology needs regulation and when. As there is...

The activities of large online platforms based in third countries in the internal market pose potential risks to EU users. The EU aims to ensure a safe online environment not only for consumers, but also for all users active in this ecosystem. Increased security, legal certainty, consumer protection, transparency, and several other partial aims have led to the adoption of the Digital Services Package, which includes the so-called DSA Regulation. The present article aims to identify the key impacts of the new regulation on very large online platforms that are part of the daily routine of EU citizens and to highlight the benefits it brings to regular users. There are many changes brought about by the new legislation; therefore, we decided to focus only on those that we consider the most tangible, both from the perspective of the everyday user and for the platforms per se.

**Abstract** 

Este estudo aborda as considerações éticas envolvidas na seleção de conteúdo para treinamento de chatbots políticos, destacando os desafios na construção de modelos conversacionais que influenciam a opinião pública. Examina-se o impacto da antropomorfização das máquinas na tomada de decisão e a necessidade de diretrizes éticas para evitar a disseminação de desinformação e comportamentos indesejáveis. O trabalho propõe princípios como neutralidade, precisão, transparência e respeito à diversidade, fundamentais para garantir interações éticas. Além disso, apresenta ferramentas como NLTK e SpaCy para análise e filtragem de conteúdo, mitigando viés e linguagem imprópria. Conclui-se que, embora os processos de análise humana sejam essenciais, há potencial para a evolução de modelos autônomos capazes de verificar a veracidade e adequação do conteúdo.

This paper introduces the Discrete Judgment Intermediate (DJI) as a novel framework for AI safety, regulatory oversight, and ethical alignment. By functioning as an executive function of the artificial mind, DJI serves as a modular, discrete layer that works alongside primary AI systems, addressing critical challenges such as ethical drift, bias, and regulatory non-compliance. Unlike traditional embedded mechanisms, DJI offers a transparent, inspectable, and adaptable approach without compromising proprietary innovations. Key components include ethical compliance sublayers, regulatory monitoring, and context enrichment mechanisms. The framework incorporates a blockchain-based registration workflow that ensures real-time transparency through user-facing AI safety status indicator to foster trust. DJI represents a comprehensive ecosystem that provides a holistic solution for regulatory, compliance, and safety needs, enabling any rogue or malicious AI to be instantly and visibly identified as an outlaw within a transparent, integrated paradigm.

This is the extended abstract, translated to english, of the Hebrew publication 'Human, Machine, State: Toward the Regulation of Artificial Intelligence'. A primer to AI regulation for Hebrew speaking readers, which outlines also recommendations and tools for policy makers

ספר זה, הראשון מסוגו בעברית, בוחן מהי בינה מלאכותית, מהם יתרונותיה ואילו חששות היא מעוררת בארץ ובעולם. מחבריו קוראים למקבלי ההחלטות, התעשייה, האקדמיה וארגוני החברה האזרחית בישראל להיערך לקראתה באמצעות אסטרטגיה לאומית ומדיניות רגולטורית. כדי להבטיח שאנשים הם שישלטו במכונות ולא להפך, נדרש פיתוח של עקרונות מנחים ליצירת מדיניות בינה מלאכותית מכוונת זכויות וארגז כלים לאסדרת בינה מלאכותית.

Nous proposons de présenter une réflexion sur l’Intelligence Artificielle (IA) au prisme du genre, de la classe et de la race, dans une approche intersectionnelle qui questionne l’apparente neutralité de cette Technique. L’objectif étant de mettre en visibilité les différents impacts de ces technologies sur les rapports sociaux, notamment en démontrant que l’IA est une Technique intrinsèquement sociale, idéologique et politique. Penser l’IA en co-construction avec la société permet d’éviter de tomber dans un « maths washing » invisibilisant les rapports de pouvoir sous couvert d’objectivité mathématique et d’interroger les dispositifs mis en place par les différentes organisations pour veiller à ce que cette Technique n’automatise pas les injustices et inégalités.

A inteligência artificial (IA) tem sido utilizada em larga escala em variados domínios, com cada vez mais implicações sociais, éticas e de privacidade. À medida que suas potencialidades e aplicações são expandidas, surgem dúvidas sobre a confiabilidade dos sistemas equipados com IA, particularmente aqueles que empregam técnicas de machine learning que podem torná-los verdadeiras ‘caixas-pretas’. A XAI (Explainable Artificial Intelligence), ou inteligência artificial explicável, objetiva oferecer informações que ajudam a explicar o processo preditivo de determinado modelo algorítmico. Este artigo se volta especificamente para o estudo da XAI, investigando seu potencial para explicar decisões de modelos algorítmicos e combater o enviesamento dos sistemas de IA. Na primeira etapa do trabalho, é discutida a questão da falibilidade e enviesamento da IA, e como a opacidade agrava esses problemas. Na segunda parte, apresenta-se a inteligência artificial explicável e suas potenciais contrib...

Introduction: The application of artificial intelligence (AI) has been steadily increasing in diverse spheres of life, such as technologies, economics, education, art and culture, even in politics and others. What is more, the everyday life has been deeply impacted by the development of the AI. As AI is possibly to become integrated into the operations of state governments worldwide, ethical concerns emerge, regarding the extent of AI's autonomy in decision-making and action execution. This research article, therefore, delves into the ethical dimensions of AI deployment within the context of state government and public relations, focusing on two distinct usage scenarios. In the first scenario, AI serves as a tool for information analysis and recommendation without executing decisions or actions autonomously. The second scenario involves AI systems with the authority to independently execute decisions and actions that require the imperative human oversight. Human involvement is essential to ensure that decisions made by AI align with societal values, uphold legal and ethical standards, and safeguard against unforeseen consequences. This dual-tier approach, combining AI's capabilities with human confirmation, strikes a balance between technological advancement and ethical responsibility.
Aim: This study aims to provide certain guidelines for policymakers and technologists in navigating the ethical complexities of AI implementation in the public sector.
Methods: The study employs a comparative analysis approach to assess the ethical considerations surrounding AI's autonomy in state government and public relations. It examines the differing needs of AI systems in two distinct scenarios, offering insights into the balance between AI autonomy and human oversight.
Findings: The research findings emphasize the importance of a dual-tier approach in state government AI deployment.
Originality and value: This research contributes to the emerging field of AI ethics by specifically addressing the ethical challenges posed by AI in state government and public relations. The value of the research is set to outline the framework of future solutions and it puts forth the question of the influence of the AI regarding state governments and policymakers, thus focusing on the ethical implications of AI integration.

Increased automation with algorithms, particularly through the use of artificial intelligence (AI), offers opportunities for the public and private sectors to complete increasingly complex tasks with a level of productivity and effectiveness far beyond that of humans, generating substantial social and economic benefits in the process. However, many believe an increased use of algorithms will lead to a host of harms, including exacerbating existing biases and inequalities, and have therefore called for new public policies, such as establishing an independent commission to regulate algorithms or requiring companies to explain publicly how their algorithms make decisions. Unfortunately, all of these proposals would lead to less AI use, thereby hindering social and economic progress.

AI is one of the biggest technical advancements in recent times. but it can pose a great danger to humanity by unleashing misinformation and deepfakes. Regulating it therefore is of utmost importance. The recently concluded conference on 1-2 November 2023 in UK raised some hope in this regard.

Rapid technological advancements in Artificial Intelligence (AI), as well as the growing deployment of intelligent technologies in new application domains, have generated serious anxiety and a fear of missing out among different stake-holders, fostering a racing narrative. Whether real or not, the belief in such a race for domain supremacy through AI, can make it real simply from its consequences, as put forward by the Thomas theorem. These consequences may be negative, as racing for technological supremacy creates a complex ecology of choices that could push stake-holders to underestimate or even ignore ethical and safety procedures. As a consequence, different actors are urging to consider both the normative and social impact of these technological advancements, contemplating the use of the precautionary principle in AI innovation and research. Yet, given the breadth and depth of AI and its advances, it is difficult to assess which technology needs regulation and when. As there is...

The policy papers here collected are the purport of the work carried out by EURA and its teams during the entire project duration (August 2018- today), and rest upon the analysis carried out over a number of events and debates, including previous editions of the yearly EURA Conference, and seminars, all of which may still be watched on our website (https://www.eura.santannapisa.it/) and social media, in particular the EURA YouTube channel1.
Indeed, one of the focal points of our Jean Monnet Centre of Excellence (CoE) is to
establish a constant dialogue with policy-makers, identifying
topics of relevance for societal debate, and selecting trends and issues
relevant for businesses and investors.
Our members participate in various entities for the support of policy
building in the area of robotics and embedment of ethical standards in
AI system.
In order to convey to legislative and governmental entities the outcome
of its research and activities, EURA released a number of opinions and
policy-papers, providing early identification of relevant issues,
assessment, recommendations, participating in many debates leading to
the adoption of regulation, advancing proposals for actions to be taken.
EURA as an entity, as well as its fellows in their individual capacity, have
participated in the policy debates on Artificial Intelligence, in particular
about the AI Act, with a focus on prohibited practices and user
deception, civil liability, risk-management and insurance, product safety,
industrial and social robotics applications and platforms regulation.

Analysis Legal privacy rising challenges in the development of cloud robotic with particular look at health cloud robots. "The VIROS project considers the challenges and solutions in regulating roboticslegally and technicallyparticularly with respect to addressing the safety, security and privacy concerns such systems raise. 1 "Regarding the legal aspect of privacy concerns of robots and artificial intelligence (AI) which highlighted by The Norwegian Data Protection Authority (DPA) 2 .. Most applications of artificial intelligence (AI) require huge volumes of data in order to learn and make intelligent decisions. Data protection poses novel legal and regulatory questions. A deep investigate among brand new researches which have been worked over the issue, shows that concerns are dramatically increased in respect of data protection, legal and other regulatory issues by the fast-evolving development of robots and artificial intelligence (AI) systems as the AI is no longer speak of future and it is here. Rapid progress in AI and robotics are challenging the traditional boundaries of the law. 3. Algorithms are widely employed to make decisions that have an increasing impact on individuals and society, potentially leading to manipulation, biases, censorship, social discrimination, violations of privacy and property rights, and more. This has sparked a global debate on how to regulate AI and robotics.

Recent years have witnessed an increasing amount of research and interest in the complex matter of digital platforms, which has been examined from diverse and multiple academic perspectives. The phenomenon of platformisation, defined as the penetration of infrastructures, economic processes and governmental frameworks of digital platforms in different economic sectors and spheres of existence, as well as the reorganisation of cultural practices and imaginations around these platforms (Poell et al., 2019), still represents a complex and deeply investigated subject, with visible repercussions on many aspects of public and private life.
A concrete example is the widespread diffusion of globally operating platform businesses—from Facebook to Google, to Amazon, etc.—that are becoming increasingly central to public and private life, transforming key economic sectors and spheres of life.
Following the evolution and the increasing significance of platforms and digital
intermediaries, institutions have been focusing their attention and their policymaking more and more on the issue of data and digital transition, which requires digital governance to adapt to each country’s regulatory culture and capacity, as well as understanding that these structures will continue to change over time (OECD, 2019:147). In this context, at least 73 countries worldwide have adopted a digital strategy or plan (ITU, 2020:3), while another recent trend is for countries to adopt strategies tailored to specific technologies or issues, such as automation, robotics, 5G, artificial intelligence (AI) and the Internet of Things (IoT). At the EU level, the latest Proposal of Regulation (EC)2020/825 on a Single Market for Digital Services (Digital Services Act, DSA) represents the culmination of a long-standing regulatory
process that, over the years, has touched on numerous issues related to digital
regulation. Particular attention has been paid to the implications for democratic stability caused by the extensive power of digital platforms and intermediaries: in the document published in 2020 by the European Commission’s Joint Research Centre, “Technology and Democracy: understanding the influence of online technologies on political behaviour and decision-making”, causal connections are established between how platforms work and how fundamental rights online are impacted. The research highlights how automated newsfeeds and recommendation systems are designed to maximise the attention and engagement of users by satisfying their alleged preferences, which may mean giving relevance to polarising and misleading content.
All these subjects—data-driven performances, data-agile economies and services, content’s ranking and recommendation systems—are linked by a common component: algorithms. Understanding algorithms, their role and functions in our digital world, the possible repercussions of their being more and more at the centre of the co-production of meaning in our society, is a key challenge of our times. The algorithmic power is transversal to many areas of life, and a single lens cannot magnify all of its complexity: a multidisciplinary approach can fruitfully help understand this all-encompassing phenomenon.
On the one hand, we need to understand the meaning of the “power of algorithms”: how does it concretely work, how it is related to platform performance and what are the possible implications, especially in terms of real interference with human knowledge and perception of reality. On the other hand, we will be examining the “counteractions” set out in the European regulation: how it has been developing over time and how algorithms have become increasingly central to the debate, subsequently highlighting the importance of algorithmic transparency and accountability. We will be looking at how lawmaking—in particular the European legal framework for AI—is trying to intercept that same algorithmic power and establish new benchmarks for transparency. In conclusion, we will assess how the most recent regulation proposal addresses the matter and what are the criticalities that might occur.

A inteligência artificial (IA) tem sido utilizada em larga escala em variados domínios, com cada vez mais implicações sociais, éticas e de privacidade. À medida que suas potencialidades e aplicações são expandidas, surgem dúvidas sobre a confiabilidade dos sistemas equipados com IA, particularmente aqueles que empregam técnicas de machine learning que podem torná-los verdadeiras ‘caixas-pretas’. A XAI (Explainable Artificial Intelligence), ou inteligência artificial explicável, objetiva oferecer informações que ajudam a explicar o processo preditivo de determinado modelo algorítmico. Este artigo se volta especificamente para o estudo da XAI, investigando seu potencial para explicar decisões de modelos algorítmicos e combater o enviesamento dos sistemas de IA. Na primeira etapa do trabalho, é discutida a questão da falibilidade e enviesamento da IA, e como a opacidade agrava esses problemas. Na segunda parte, apresenta-se a inteligência artificial explicável e suas potenciais contribuições para tornar os sistemas mais transparentes, auxiliando no combate aos erros e vieses algorítmicos. Conclui-se que a XAI pode colaborar para a identificação de vieses em modelos algorítmicos, razão pela qual sugere-se que a capacidade de “se explicar” – ou seja, a explicabilidade – seja um requisito para a adoção de sistemas de IA em searas mais sensíveis, como por exemplo, o auxílio à tomada de decisão judicial.

In the last years, explainable algorithms and AI raise significant interest (and concerns) in the legal debate. However, adequate recognition of this elusive right to explanation remains ambiguous and uncertain, mainly because of the current legal framework's limits. This paper addresses the problem from the perspective of constitutional law, examining if and how the so-called law in action can consolidate rights and duties to explainable and comprehensible algorithms. Focusing on EU law, the paper considers the achievements gained in personal data protection, focusing on the innovations introduced by art. 22, reg. EU 679/2016 (GDPR). In light of the shortcomings that emerged in this field, the reflection thus recalls the constitutional rationale of data protection. It, therefore, examines how national case-law – using the same method – fosters a more solid recognition of an effective right to understand and a duty to explain algorithms.

As we enter the Age of Artificial Intelligence and an increasingly securitized cyberspace, the direction of history, materially or ideationally, may be diverging away from those articulated by Francis Fukuyama, Parag Khanna, and Yan Xuetong. This will impact how we conceive of great powers and leadership, as new forms of power and the creation of power manifest not according to human logic and capacities but instead according to artificial intelligence (AI) algorithms. AI and cybersecurity have become protean security disruptors and may manifest into new power paradigms for states and nonstate actors.

This article explores the legal and ethical implications of big data's pursuit of human 'digital thought clones'. It identifies various types of digital clones that have been developed and demonstrates how the pursuit of more accurate personalised consumer data for micro-targeting leads to the evolution of digital thought clones. The article explains the business case for digital thought clones and how this is the commercial Holy Grail for profit-seeking big data and advertisers, who have commoditised predictions of digital behaviour data. Given big data's industrial-scale data mining and relentless commercialisation of all types of human data, this article identifies some types of protections but argues that more jurisdictions urgently need to enact legislation similar to the General Data Protection Regulation in Europe to protect people against unscrupulous and harmful uses of their data and the unauthorised development and use of digital thought clones.

In the last years, explainable algorithms and AI raise significant interest (and concerns) in the legal debate. However, adequate recognition of this elusive right to explanation remains ambiguous and uncertain, mainly because of the current legal framework's limits. This paper addresses the problem from the perspective of constitutional law, examining if and how the so-called law in action can consolidate rights and duties to explainable and comprehensible algorithms. Focusing on EU law, the paper considers the achievements gained in personal data protection, focusing on the innovations introduced by art. 22, reg. EU 679/2016 (GDPR). In light of the shortcomings that emerged in this field, the reflection thus recalls the constitutional rationale of data protection. It, therefore, examines how national case-law-using the same method-fosters a more solid recognition of an effective right to understand the duty to explain algorithms.

MENDES, Laura Schertel; FONSECA, Gabriel Campos Soares da. Entre a ética dos robôs e a ética dos humanos: a atualidade dos princípios da robótica de Isaac Asimov. In: TAVARES, André Ramos. Vestígios do Futuro: 100 anos de Isaac Asimov. São Paulo: Etheria Editora, 2020, p. 85-89.

This article explores the legal and ethical implications of big data's pursuit of human 'digital thought clones'. It identifies various types of digital clones that have been developed and demonstrates how the pursuit of more accurate personalised consumer data for micro-targeting leads to the evolution of digital thought clones. The article explains the business case for digital thought clones and how this is the commercial Holy Grail for profit-seeking big data and advertisers, who have commoditised predictions of digital behaviour data. Given big data's industrial-scale data mining and relentless commercialisation of all types of human data, this article identifies some types of protections but argues that more jurisdictions urgently need to enact legislation similar to the General Data Protection Regulation in Europe to protect people against unscrupulous and harmful uses of their data and the unauthorised development and use of digital thought clones.

Rapid technological advancements in Artificial Intelligence (AI), as well as the growing deployment of intelligent technologies in new application domains, have generated serious anxiety and a fear of missing out among different stake-holders, fostering a racing narrative. Whether real or not, the belief in such a race for domain supremacy through AI, can make it real simply from its consequences, as put forward by the Thomas theorem. These consequences may be negative, as racing for technological supremacy creates a complex ecology of choices that could push stake-holders to underestimate or even ignore ethical and safety procedures. As a consequence, different actors are urging to consider both the normative and social impact of these technological advancements, contemplating the use of the precautionary principle in AI innovation and research. Yet, given the breadth and depth of AI and its advances, it is difficult to assess which technology needs regulation and when. As there is no easy access to data describing this alleged AI race, theoretical models are necessary to understand its potential dynamics, allowing for the identification of when procedures need to be put in place to favour outcomes beneficial for all. We show that, next to the risks of setbacks and being reprimanded for unsafe behaviour, the timescale in which domain supremacy can be achieved plays a crucial role. When this can be achieved in a short term, those who completely ignore the safety precautions are bound to win the race but at a cost to society, apparently requiring regulatory actions. Our analysis reveals that imposing regulations for all risk and timing conditions may not have the anticipated effect as only for specific conditions a dilemma arises between what is individually preferred and globally beneficial. Similar observations can be made for the long-term development case. Yet different from the short-term situation, conditions can be identified that require the promotion of risk-taking as opposed to compliance with safety regulations in order to improve social welfare. These results remain robust both when two or several actors are involved in the race and when collective rather than individual setbacks are produced by risk-taking behaviour. When defining codes of conduct and regulatory policies for applications of AI, a clear understanding of the timescale of the race is thus required, as this may induce important non-trivial effects.

The purpose of this dissertation is to suggest a new approach to face the trolley problem in light of AI developments concerning automated vehicles, in order to provide a shared framework for computer scientists and jurists to enhance the implementation of decision algorithms and legal regulations of AI, respectively.
In order to do so, we move from an example of the difficulty in leading with dilemmatic scenarios from a legal standpoint to a descriptive analysis of the trolley problem as a particularly relevant instance of moral dilemmas, by considering it both from an ethical-philosophical and neuroscientific point of view, and highlighting the criticism that can be moved from the current approach to the issue.
Subsequently, we consider the impact of AI and self-driving cars in particular on the approach to this dilemma from a philosophical as well as a legal perspective and present the main regulations that have been put in place to govern such scenarios.
Lastly, setting aside all preconceptions, we consider once again the trolley problem from a purely logical perspective and avail ourselves of computational logic to propose a new approach which can be fruitfully implemented on self- driving vehicles, while also aligning with legal principles and judicial reasoning and having the potential to enhance the current regulatory landscape.

With the regulation of Artificial Intelligence (AI), the European Commission is addressing one of the central issues of our time. However, a number of core legal questions are still unresolved. Against this background, the article in a first step lays regulatory foundations by examining the possible scope of a future AI regulation, and by discussing legal strategies for implementing a risk-based approach. In this respect, I suggest an adaptation of the Lamfalussy procedure, known from capital markets law, which would combine horizontal and vertical elements of regulation at several levels. This should include, at Level 1, principles for AI development and application, as well as sector-specific regulation, safe harbors and guidelines at Levels 2-4. In this way, legal flexibility for covering novel technological developments can be effectively combined with a sufficient amount of legal certainty for companies and AI developers.
In a second step, the article implements this framework by addressing key specific issues of AI regulation at the EU level, such as: documentation and access requirements; a regulatory framework for training data; a revision of product liability and safety law; strengthened enforcement; and a right to a data-free option.

Artificial intelligence (AI) increasingly pervades all areas of life. To seize the opportunities this technology offers society, while limiting its risks and ensuring citizen protection, different stakeholders have presented guidelines for AI ethics. Nearly all of them consider similar values to be crucial and a minimum requirement for “ethically sound” AI applications – including privacy, reliability and transparency. However, how organisations that develop and deploy AI systems should implement these precepts remains unclear. This lack of specific and verifiable principles endangers the effectiveness and enforceability of ethics guidelines. To bridge this gap, this paper proposes a framework specifically designed to bring ethical principles into actionable practice when designing, implementing and evaluating AI systems.

List of Authors:
Dr Sebastian Hallensleben
Carla Hustedt
Lajla Fetic
Torsten Fleischer
Paul Grünke
Dr Thilo Hagendorff
Marc Hauer
Andreas Hauschke
PD Dr Jessica Heesen
Michael Herrmann
Prof. Dr Rafaela Hillerbrand
Prof. Emeritus Christoph Hubig
Dr Andreas Kaminski
Tobias Krafft
Dr Wulf Loh
Philipp Otto
Michael Puntschuh

Competent authorities of many countries around the world are deploying automation tools in decision-making processes in the judiciary. The scope of application of automated judicial systems, often based on artificial intelligence (AI), is broad, ranging from the improvement and acceleration of organisational or office-based court tasks to the automation of substantive judicial decisions. The ongoing or future judicial automation in the European Union (EU) requires an in-depth legal analysis from the perspectives of data protection and privacy law, which raise crucial legal issues in the judicial automation landscape. The paper, therefore, aims to identify the constraints created by the EU data protection and privacy law to the use of automated decision-making within judicial proceedings. It first describes two models of judicial automation, which need to be distinguished on the basis of the degree of automation and the level of human involvement in the decision-making process (fully and partially automated decision-making and two sub-models of the latter). The paper then discusses the legal bases for both models of automated personal data processing in the judiciary, with a particular emphasis on the French national regulation, based on Article 22 of the GDPR, which provides the sharpest restriction to judicial automation within the European Union. Even when there are lawful grounds for judicial automation, legal requirements will provide constraints and limits to the operation of any automated decision-making systems. Acknowledging this fact, the paper concludes with the analysis of three perspectives which introduce limits to automation — data protection regulation, privacy law, and technological constraints —, as well as the safeguards that these viewpoints provide to the rights and interests of those affected by judicial automation.

Within the coming decade, the deployment of artificial intelligence ('AI') appears likely to have a disruptive impact on global affairs. What will such 'globally disruptive' AI imply for the form, function and viability of international law? I briefly sketch the long history of technological innovation driving, shaping and destroying international law. Drawing on scholarship on the relation between new technologies and international law, I argue that new technology changes legal situations both directly, by creating new entities or enabling new behaviour, and indirectly, by shifting incentives or values. I argue that development of increasingly more disruptive AI may produce three types of global legal impacts. The first is 'legal development' (patching); the second is 'legal displacement' (substitution); the third is 'legal destruction' (erosion). I discuss the potential impact of AI in all three modalities, and the implications for international relations. I argue that many of the challenges raised by AI could in principle be accommodated in the international law system through legal development, and that while AI may aid in compliance enforcement, the prospects for legal displacement-a shift towards an 'automated international law'-look slim. However, I also conclude that technical and political features of the technology will in practice render AI destructive to key areas of international law: the legal gaps it creates will be hard to patch, and the strategic capabilities it offers chip away at the rationales for powerful states to engage fully in, or comply with, international law regimes. This suggests some risk of obsolescence of distinct international law regimes. CONTENTS