Search

The long-awaited introduction of the AI Act, notwithstanding its originality, does not introduce any regulation outside the existing framework. It supplements the safeguards provided in numerous sectors of the EU legislation, inter alia, consumer protection. An examination of the basic EU law along with national legislation of the most influential legal orders, i.e. the French and German one, and model rules of the Draft Common Frame of Reference (DCFR) confirms that the new AI Act sheds light on pre-existing vague legal concepts. In this respect, this novel piece of legislation promotes a better understanding of traditional notions of law applicable to the modern digital reality without introducing totally new rules. Accordingly, certainty of law is reinforced where consumer protection had languished, not because of legislative shortage, but for facts and situations described as necessary conditions of certain rights were contested on the basis of contrary possible interpretations of decisive terms. Ultimately, the very importance of the AI act regarding consumer protection lies not in the introduction of new rights and obligations, but in a multiple practical assistance to the implementation of existing rules adjusting thus the traditional legal concepts with technological development beyond their original scope.

Artificial intelligence's threats to human rights can offset its significant benefits for human welfare. This makes it essential to analyse the current status and existing practices in developing the regulatory framework for artificial intelligence (AI). This paper aims to conduct a comparative legal analysis of the role of AI in ensuring human rights in Europe (in the example of the European Union) and the Middle East (in the example of Israel). The article uses comparative legal, formal legal and descriptive methods. The analysis shows that AI may harm the enjoyment of several human rights. Existing legislative initiatives (in particular, The EU Artificial Intelligence Act (AI Act), the Council of Europe's AI Convention) do not fully protect human rights from the impact of artificial intelligence due to existing gaps in the regulation of the private sector and national security, as well as the effect on the transparency of decisions in criminal law. The main problem is the inadequate regulation of the development and use of AI in national security and the private sector. This creates loopholes through which AI can cause significant harm to human rights and lead to violations. Further research can determine how the shortcomings identified in this paper may affect human rights and what safeguards can be put in place. [ABSTRACT FROM AUTHOR]

Public sector digitalisation is transforming public governance at an accelerating rate. Digitalisation is outpacing the evolution of the legal framework. Despite several strands of international efforts to adjust good administration guarantees to new modes of digital public governance, progress has so far been slow and tepid. The increasing automation of decision-making processes puts significant pressure on traditional good administration guarantees, jeopardises individual due process rights, and risks eroding public trust. Automated decision-making has, so far, attracted the bulk of scholarly attention, especially in the European context. However, most analyses seek to reconcile existing duties towards individuals under the right to good administration with the challenges arising from digitalisation. Taking a critical and technology-centred doctrinal approach to developments under the law of the European Union and the Council of Europe, this paper goes beyond current debates to challenge the sufficiency of existing good administration duties. By stressing the mass effects that can derive from automated decision-making by the public sector, the paper advances the need to adapt good administration guarantees to a collective dimension through an extension and a broadening of the public sector's good administration duties: that is, through an extended ex ante control of organisational risk-taking, and a broader ex post duty of automated redress. These legal modifications should be urgently implemented. [ABSTRACT FROM AUTHOR]

Artificial intelligence has become an issue in public policy. Multiple documents issued by public sector actors link artificial intelligence to a wide range of issues, problems or goals and propose corresponding measures and interventions. While there has been substantial research on national and supranational artificial intelligence strategies and regulations, this article is interested in unpacking the processes and priorities of artificial intelligence policy in the making. Conceptually, this article takes a controversy studies lens onto artificial intelligence policy, and complements this with concepts and insights from policy studies. Empirically, we investigate the emergence of German artificial intelligence policy based on content analyses of policy documents and expert interviews. The findings reveal a late, but then powerful institutionalisation of artificial intelligence policy in German federal politics. Artificial intelligence policy in Germany focuses on funding research and supporting industry actors in networked configurations, much more than addressing societal concerns on inequality, discrimination or political economy. With regard to controversies, we observe that German policy is evading controversies by normalising artificial intelligence both with regard to taking artificial intelligence integration in all sectors of society for granted, as well as by accommodating artificial intelligence issues into the routines and institutions of German policy. [ABSTRACT FROM AUTHOR]

Regulatory frameworks for artificial intelligence (AI) are needed to mitigate risks while ensuring the ethical, secure, and effective implementation of AI technology in healthcare and population health. In this article, we present a synthesis of 141 binding policies applicable to AI in healthcare and population health in the EU and 10 European countries. The EU AI Act sets the overall regulatory framework for AI, while other legislations set social, health, and human rights standards, address the safety of technologies and the implementation of innovation, and ensure the protection and safe use of data. Regulation specifically pertaining to AI is still nascent and scarce, though a combination of data, technology, innovation, and health and human rights policy has already formed a baseline regulatory framework for AI in health. Future work should explore specific regulatory challenges, especially with respect to AI medical devices, data protection, and data enablement. [ABSTRACT FROM AUTHOR]

Copyright of Teoria y Realidad Constitucional is the property of Editorial UNED and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In Europe, there is increasing recognition of the ethical challenges associated with designing and developing Artificial Intelligence (AI) and Machine Learning (ML) systems, especially concerning their potential impact on fundamental rights. As a result, ethics frameworks and guidelines have been issued by stakeholders in both the private and public sectors. At the same time, fostering innovation in the field is also crucial. The implementation of the European Union (EU) sustainability goals is one area where AI/ML is expected to make a significant contribution, but there are important considerations to address. The expanding reliance on data storage and the subsequent increase in electricity consumption due to advancements in AI/ML have significant implications for greenhouse gas emissions. This paper examines the regulatory landscape for environmental sustainability using an institutional analysis contrasting the ethical frameworks and current normative standards applicable within the EU. The purpose is to identify a realistic and practical interpretation that prioritizes the development and implementation of AI/ML in a way that facilitates a smooth transition towards the sustainable usage of digital and automated technologies. [ABSTRACT FROM AUTHOR]

Over the last few years, artificial intelligence (AI) technologies have become embedded in various domains of social life, prompting legislative efforts at both national and international levels. In the European Union (EU), this drive for legislation has been reflected in various legal instruments, notably the proposed AI Act, which is expected to become a global standard through the "Brussels Effect." This Article argues that while the AI Act will likely produce a Brussels Effect of its own, such an outcome will be accompanied by a side effect that undermines the EU's ambition to spread legislative text and values in AI governance. Since the AI Act follows EU product safety legislation, its provisions supply limited protection to some of the values the EU policy intends to protect, such as the protection of fundamental rights. These shortcomings are compounded by the EU's active efforts to shape alternative instruments, such as the Council of Europe's proposed convention on AI along the lines of the AI Act. As a result, the diffusion of the AI Act as a global standard will have consequences for the EU policy agenda on AI and the conceptualization of the Brussels Effect. [ABSTRACT FROM AUTHOR]

This commentary critically evaluates Showler’s pragmatic approach to moral status, which integrates moral individualism and moral relationalism to address the moral complexities surrounding non-human entities, especially social robots. Showler proposes a unified methodology that delineates distinct roles for each theory—moral coordination problems for moral individualism and moral transformation for moral relationalism. However, my commentary identifies key methodological ambiguities and potential conflation of moral status determination with broader ethical reasoning. It argues for clearer application guidelines and further theoretical refinement to enhance the framework’s robustness and practical applicability, suggesting this model as an interesting starting point for further debates on moral status. [ABSTRACT FROM AUTHOR]

The focus of this study is on the Hiroshima AI Process. It ranks among the most important AI global governance initiatives in recent years. Over the course of the 2023 year G7 states discussed current issues of AI regulations and adopted a number of documents. Among them are those that lay the foundations of a comprehensive policy framework on AI and are recommended for implementation by the relevant actors in this field. The author investigated the Hiroshima AI Process as a separate phenomenon from the standpoint of the influence of international cooperation on the development of AI. He examined a few documents reflecting current trends in AI governance. Those include the Takasaki Ministerial Declaration with the results of the meeting of Digital and Tech Ministers, The Hiroshima Process International Guiding Principles for Organizations Developing Advanced AI Systems, as well as the Report "Towards a G7 Common Understanding on Generative AI". The author's interest in this global governance initiative is largely explained by the fact that the positions of highly developed states with their own vision of AI policy and AI regulations were agreed upon and reflected after the discussions. The documents prepared will have a significant impact on the domain of AI far beyond the borders of G7 states, given their important role in law and policy making processes at the global level. Subsequently in the study of the Hiroshima AI Process the author revealed that international cooperation with the participation of the G7 had established a superstructure for the generally recognized AI principles of trustworthy, accountability, transparency and fairness. On the basis of the analysis of the Ministerial Declaration, a kind of AI G7 road map for international discussions on advanced AI systems has been created. The findings are valuable for both a better understanding of AI global governance and determining the near future prospects for regulations. [ABSTRACT FROM AUTHOR]

We are at the dawn of the Fourth Industrial Revolution, characterised by the interaction of so-called disruptive technologies (biotechnology, synthetic biology, nanotechnology, neurotechnology and artificial intelligence). We believe that the challenges posed by technoscience cannot be met by the three generations of human rights that already exist. The need to create a fourth generation of human rights is, therefore, explored in this article. For that purpose, the state of the art will be analysed from a scientific and ethical perspective. We will consider the position of academic doctrines on the issues that a fourth generation of human rights should tackle. And, finally, in this fourth generation, we will propose the principles of identity and precaution as reference values, equivalent to the role played by freedom, equality and solidarity in the first three generations of human rights. [ABSTRACT FROM AUTHOR]

This paper delves into the complexities of global AI regulation and governance, emphasizing the socio-economic repercussions of rapid AI development. It scrutinizes the challenges in creating effective governance structures amidst the AI race, considering diverse global perspectives and policies. The discourse moves beyond specific corporate examples, addressing broader implications and sector-wide impacts of AI on employment, truth discernment, and democratic stability. The analysis focuses on contrasting regulatory approaches across key regions—the United States, European Union, Asia, Africa, and the Americas and thus highlighting the variations and commonalities in strategies and implementations. This comparative study reveals the intricacies and hurdles in formulating a cohesive global policy for AI regulation. Central to the paper is the examination of the dynamic between rapid AI innovation and the slower pace of regulatory and ethical standard-setting. It critically evaluates the advantages and drawbacks of shifting regulatory responsibilities between government bodies and the private sector. In response to these challenges, the discussion proposes an innovative and integrated regulatory model. The model advocates for a collaborative network that blends governmental authority with industry expertise, aiming to establish adaptive, responsive regulations (called "dynamic laws") that can evolve with technological advancements. The novel approach aims to bridge the gap between rapid AI advancements in the industry and the essential democratic processes of law-making. [ABSTRACT FROM AUTHOR]

Automated decision-making gains traction, prompting discussions on regulation with calls for human oversight. Understanding how human involvement affects the acceptance of algorithmic recommendations and the accuracy of resulting decisions is vital. In an online experiment (N = 292), for a prediction task, participants choose a recommendation stemming either from an algorithm or another participant. In a between-subject design, we varied if the prediction was delegated completely or if the recommendation could be adjusted. 66% of times, participants preferred to delegate the decision to an algorithm over an equally accurate human. The preference for an algorithm increased by 7 percentage points if participants could monitor and adjust the recommendations. Participants followed algorithmic recommendations more closely. Importantly, they were less likely to intervene with the least accurate recommendations. Hence, in our experiment the human-in-the-loop design increases the uptake but decreases the accuracy of the decisions. [ABSTRACT FROM AUTHOR]

This Comment argues that the U.S. restrictions on the export of semiconductors and other AI technology to China do not violate the General Agreement on Tariffs and Trade 1994 (GATT 1994). Instead, such measures are legitimate expressions under GATT 1994's Article XXI national security exception, which allows a country to break other articles within the agreement if necessary to protect the country's essential national security interests. Given the national security risks associated with the rise of AI technology and the likelihood that such technology will be supplied to a military enterprise, the current trade restrictions qualify for the exception. However, this Comment ultimately argues that while valid under GATT 1994, these trade restrictions are not a permanent solution. Such trade restrictions hurt international trade agreements and multilateral trading systems and do not remedy national security concerns. Ultimately a multilateral agreement regarding the safe trade and use of AI technology is needed to relieve the national security risks and prevent future disruption to trade. [ABSTRACT FROM AUTHOR]

This article argues that an artificial superintelligence (ASI) emerging in a world where war is still normalised constitutes a catastrophic existential risk, either because the ASI might be employed by a nation–state to war for global domination, i.e., ASI-enabled warfare, or because the ASI wars on behalf of itself to establish global domination, i.e., ASI-directed warfare. Presently, few states declare war or even war on each other, in part due to the 1945 UN Charter, which states Member States should "refrain in their international relations from the threat or use of force", while allowing for UN Security Council-endorsed military measures and self-defense. As UN Member States no longer declare war on each other, instead, only 'international armed conflicts' occur. However, costly interstate conflicts, both hot and cold and tantamount to wars, still take place. Further, a New Cold War between AI superpowers looms. An ASI-directed/enabled future conflict could trigger total war, including nuclear conflict, and is therefore high risk. Via conforming instrumentalism, an international relations theory, we advocate risk reduction by optimising peace through a Universal Global Peace Treaty (UGPT), contributing towards the ending of existing wars and prevention of future wars, as well as a Cyberweapons and Artificial Intelligence Convention. This strategy could influence state actors, including those developing ASIs, or an agential ASI, particularly if it values conforming instrumentalism and peace. [ABSTRACT FROM AUTHOR]

The rapid development and use of digital technology, including artificial intelligence (AI), have a significant impact on society in general, but specifically also on the public sector. In this data driven digital era the use of AI in government has become a crucial tool to help shape the future of public governance. Automated decision-making or algorithmic decision-making enables more informed and evidence-based decision-making in government. The variety of applications of AI is growing rapidly and spans all functional areas of government. AI based technologies create opportunities to transform the way in which local governments deliver municipal services. Also, in other spheres of government it enhances efficiency, and proactive and responsive decision-making to the benefit of citizens. It has huge potential and offers many benefits, but also includes many risks. This requires a responsible approach that will include mechanisms for safeguarding fundamental rights, inclusivity and a process of constant participation with citizens, and ensuring that the performance of AI systems is proportionate, supervised and reasoned. Responsible AI based on a set of key principles such as accountability, explainability and respect for privacy and other human rights should be the foundation for the use of AI in public governance. Various policy and legislative initiatives around the world aim to create clear, workable frameworks for the development and use of responsible AI. An example is the AI Act in the European Union which was approved by the European Parliament in June 2023, and which follows a risk-based approach that acknowledges the protection of human rights in the development and use of AI. Various local and regional policy and legal developments to support responsible AI at sub-national level are also in process. How can AI be used to improve public governance? What safeguards should be put in place to ensure ethical and responsible AI and the protection of human rights? How can AI be used to co-create public services? In presenting the paper, these critical questions will be considered. This paper explores the development of responsible and ethical AI policies and initiatives in public governance, with a specific focus on AI in cities. It discusses key initiatives such as the establishment of an algorithmic register in Amsterdam and Barcelona, as well as specific AI applications that enhances service delivery. It will conclude with some recommendations for building blocks in ensuring responsible AI in public governance in local government. [ABSTRACT FROM AUTHOR]

The use of Artificial Intelligence (AI) medical devices is rapidly growing. Although AI may benefit the quality and safety of healthcare for older adults, it simultaneously introduces new ethical and legal issues. Many AI medical devices exhibit age-related biases. The first part of this paper explains how 'digital ageism' is produced throughout the entire lifecycle of medical AI and may lead to health inequity for older people: systemic, avoidable differences in the health status of different population groups. This paper takes digital ageism as a use case to show the potential inequitable effects of AI, conceptualized as the 'AI cycle of health inequity'. The second part of this paper explores how the European Union (EU) regulatory framework addresses the issue of digital ageism. It argues that the negative effects of age-related bias in AI medical devices are insufficiently recognized within the regulatory framework of the EU Medical Devices Regulation and the new AI Act. It concludes that while the EU framework does address some of the key issues related to technical biases in AI medical devices by stipulating rules for performance and data quality, it does not account for contextual biases, therefore neglecting part of the AI cycle of health inequity. [ABSTRACT FROM AUTHOR]

A rational agent (artificial or otherwise) residing in a complex changing environment must gather information perceptually, update that information as the world changes, and combine that information with causal information to reason about the changing world. Using the system of defeasible reasoning that is incorporated into the OSCAR architecture for rational agents, a set of reason-schemas is proposed for enabling an agent to perform some of the requisite reasoning. Along the way, solutions are proposed for the Frame Problem, the Qualification Problem, and the Ramification Problem. The principles and reasoning described have all been implemented in OSCAR. [ABSTRACT FROM AUTHOR]