Regulation Of Artificial Intelligence Research Articles

Modeling approaches to AI integration into public relations in Russia as per comparative research of foreign countries’ experience

Artificial intelligence (AI) technologies are one of the most significant solutions that can fundamentally change both public relations and the sphere of public legal relations. The goal of the present research is to conduct a comparative analysis of existing approaches to the AI integration into the sphere of public legal relations of foreign countries and Russia, with the subsequent determination of the most effective constructive approaches to the formation of a regulatory policy regarding AI in Russia. This goal is achieved through the study of the following issues: Strategic goal-setting in relation to AI in Russia and other countries; Tactical implementation of AI integration into public legal relations and possible solutions in order to ensure AI decision-making transparency; Model compensatory measures that ensure AI safe integration into public relations in Russia. The object of the study comprises regulatory sources, strategies, and other documents regulating the AI integration into the sphere of public legal relations in Russia and foreign countries, judicial practice examples, and academic publications on the issues under study. The research methodology incorporates a complex of modern philosophical, general scientific, special scientific methods of cognition, including dialectical, systemic, structural-functional, hermeneutic, comparative legal, formal legal (dogmatic), legal modeling methods, and some others. The present research lays special emphasis on the implementation of a comparative legal study of the approaches to and regulation of AI in the public sphere regarding various states experience. The general scientific dialectical method has made it possible to consider the AI position in the legal field from the point of view of the AI regulation variability and trends in the subsequent development thereof, and to substantiate the advantages and disadvantages of various approaches to solve the respective issues, as well. Additional emphasis is also laid on addressing the issues of the applied nature of the AI use in the field of public relations in Russia, taking into account the legal modeling and development of compensatory measures within the authorities’ regulatory approaches.

Quality indicators artificial intelligence

The ability of some artificial intelligence (AI) systems to autonomously evolve and the sometimes very limited possibilities to comprehend their decision-making processes present new challenges to our legal system. At a European level this has led to reform efforts, of which the proposal for aEuropean AI regulation promises to close regulatory gaps in existing product safety law through cross-sectoral AI-specific safety requirements. Aprerequisite, however, would be that the EU legislator does not only avoid duplications and contradictions with existing safety requirements but also refrains from imposing exaggerated and unattainable demands. If this were to be taken into consideration, the new safety requirements could also be used to specify the undefined standard of care in liability law. Nevertheless, challenges in the context of provability continue to remain unresolved, posing arisk of rendering the legal protection efforts of the aggrieved party ineffective. It remains to be seen whether the EU legislator will address this need for reform with the recently proposed reform of product liability law by the Commission.

European artificial intelligence “trusted throughout the world”: Risk‐based regulation and the fashioning of a competitive common AI market

AbstractThe European Commission has pioneered the coercive regulation of artificial intelligence (AI), including a proposal of banning some applications altogether on moral grounds. Core to its regulatory strategy is a nominally “risk‐based” approach with interventions that are proportionate to risk levels. Yet, neither standard accounts of risk‐based regulation as rational problem‐solving endeavor nor theories of organizational legitimacy‐seeking, both prominently discussed in Regulation & Governance, fully explain the Commission's attraction to the risk heuristic. This article responds to this impasse with three contributions. First, it enrichens risk‐based regulation scholarship—beyond AI—with a firm foundation in constructivist and critical political economy accounts of emerging tech regulation to capture the performative politics of defining and enacting risk vis‐à‐vis global economic competitiveness. Second, it conceptualizes the role of risk analysis within a Cultural Political Economy framework: as a powerful epistemic tool for the discursive and regulatory differentiation of an uncertain regulatory terrain (semiosis and structuration) which the Commission wields in its pursuit of a future common European AI market. Thirdly, the paper offers an in‐depth empirical reconstruction of the Commission's risk‐based semiosis and structuration in AI regulation through qualitative analysis of a substantive sample of documents and expert interviews. This finds that the Commission's use of risk analysis, outlawing some AI uses as matters of deep value conflicts and tightly controlling (at least discursively) so‐called high‐risk AI systems, enables Brussels to fashion its desired trademark of European “cutting‐edge AI … trusted throughout the world” in the first place.

Legal Risks and Responses to Artificial Intelligence Technology from the Perspective of Sociology of Technology

Due to the wide application of Artificial Intelligence (AI), it is reconstructing the rules, behavior, and the way of organization and operation in the economy and society. However, AI has also brought many potential risks while promoting high-quality economic growth and achieving effective social governance. AI has powerful intelligent thinking and behavioral decision-making ability. Therefore, there would be huge risks once safety problems related to AI occur. Although all countries are aware of the necessity of strengthening the regulation of AI, the regulatory system and governance concepts in practice are still not sophisticated enough to cope with the rapid progress of AI technology. In this paper, from the perspective of the sociology of technology, we analyze the development boundaries and legal limits of AI technology, and further explore the governance of science and technology ethics, aiming to build an AI that meets human expectations and promotes human well-being.

Exploring Co-Regulation as a Solution to Automated Disinformation in Kenya

This paper discusses automated disinformation on social media in Kenya and its impact on democracy. Automated disinformation refers to disinformation that is exacerbated by the use of Artificial Intelligence (AI) and related emerging technologies, including algorithms and bots. The paper considers the electoral process in Kenya as a case study to highlight the threats that automated disinformation poses to the democratic process and proposes co-regulation as the way forward. Specifically, it reviews the impacts of automated disinformation on democracy including the negative effect on the availability of reliable and accurate information to enlighten the social media users’ political choices and the effect on the exercise of political will, public opinion, and democracy. The objective of this research is to provide policy recommendations to the relevant stakeholders on tackling the challenge of widespread automated disinformation perpetuated by social media users in Kenya whilst respecting fundamental human rights and promoting democracy. The author discusses the regulatory framework applicable to the information disorder phenomenon including those relevant to the exercise of the freedom of expression and access to information, noting that these rights play a significant role in strengthening democracy. This paper also considers the nascent regulation of AI and undertakes an analysis of how effective regulation can counter the widespread automated disinformation on social media platforms.

Navigating the Ethical Maze: Moral Dilemmas in the Age of AI

Abstract: This research paper explores the ethical implications of artificial intelligence (AI) in various fields and domains. It delves into the potential benefits and risks of AI, focusing on its impact on employment, bias induced by AI systems, concerns over data privacy, and other factors affecting humanity. The paper emphasizes the importance of robust and dynamic AI regulation to mitigate the risks of AI. Additionally, it highlights the limited ability of governments and institutions worldwide to keep up with the rapid evolution of AI in the industry. The paper also provides recommended strategies and approaches grounded in philosophy to avoid negative implications.

Artificial Intelligence: When Technology is the Smallest of the Paradigms

The article analyzes, deepens, and reflects on the development and impact of artificial intelligence (AI) in various areas of society. The meaning of AI is the development of a scientific discipline that encompasses a set of cognitive and intellectual simulation capabilities expressed by computer systems through algorithms. The author distinguishes between weak artificial intelligence, which is concerned with performing specific tasks, and strong artificial intelligence, which forms an AI that will exceed human capabilities. AI is a disruptive force that radically changes traditional models and paradigms and requires constant adaptation and multidisciplinary training on the part of human beings. The proposal arises that the new generations are not only trained in technological careers, but also in humanistic disciplines such as philosophy, sociology, linguistics, and political science, to instruct AI with values and principles, even if they constitute complex filters. In their algorithms or part of their training. We must take advantage of the potential of AI to improve the quality of life and the general management of our actions in community. Some of the risks that already threaten and affect different sectors, industries, markets, etc. are described and predicted. The causes and effects of hallucinations of artificial intelligence (AI) are observed, as phenomena in which the AI produces or perceives information that does not correspond to reality. Coding errors, training biases or omissions, social engineering applied to AI, lack of information or data, or absence of strong algorithmic responses. We face ethical, social, and legal challenges. Governments, public administrations and obviously the private sector carry the responsibility of contributing to the control and regulation of AI on their backs. A new social contract between humans and the non-human autonomous entities that make up AI will soon become necessary. What role we will play in the future is a complex set of speculations and projections, not all these projections are the result of our will, they are not completely under our control. Today the strategic destiny of the society of the future no longer depends solely on our vision.

인공지능 규제

Artificial intelligence (AI), the key technology in the Fourth Industrial Revolution, is expected to bring numerous socioeconomic benefits, but there are also concerns about its adverse effects. This study aims to explore policy options for building trust in AI and discuss their limitations. Specifically, we analyze the EU and US approaches to creating so-called “trustworthy AI” and draw policy implications for South Korea. The EU's approach to overcoming differences in socioeconomic maturity, government capacity, and institutional context among its member states is both normative and centralized. On the other hand, the United States, which aims to maintain its technological hegemony, has taken a light-touch approach to promoting the AI industry by granting discretionary authority to sectoral regulators while encouraging private sector autonomy. The changing environment calls for a full-scale discussion on AI regulation in Korea. In this paper, we point out that it is essential to consider regulatory arrangements that include at least three elements: risk-based regulation, co-regulatory framework, and harmonization with international standards. We conclude by discussing policy options and limitations.

REGULATORY POLICY IN THE REALM OF ARTIFICIAL INTELLIGENCE: EXPLORING APPROACHES TO LEGAL REGULATION

The article represents a research endeavor that explores the approaches to regulating the realm of artificial intelligence (AI) in Kazakhstan. It presents an analysis of the methodologies employed in the development of ethical principles, strategic documents, and legislative frameworks, with the overarching objective of establishing a well-balanced model that fosters the advancement of emerging technologies and progress in the field of AI, while emphasizing the safeguarding of citizens' rights and lawful interests and ensuring their safety. The article furnishes a structured comprehension of the prospects associated with AI regulation in Kazakhstan, alongside recommendations for the adoption of contemporary international standards and practices. Particular attention is devoted to the experiences of the European Union and the United Kingdom in shaping a comprehensive regulatory framework for the AI domain. Based on a critical analysis of foreign practices, the article advocates for a delineation of regulatory matters at both the legislative and sub-legislative levels. To address legislative regulation, a series of measures is proposed, encompassing the definition of the concept of artificial intelligence, the establishment of regulatory principles, the mandatory implementation of impact assessments on human rights stemming from AI systems, the precise specification of competencies for the regulatory authority, and the requirement of transparency in AI utilization. However, the article acknowledges the impracticality of codified AI regulation. As for sub-legislative regulation, it is recommended to delineate the intricacies of procedures for assessing the impact of AI systems on human rights and technological evaluations. Furthermore, it is imperative to ascertain specific characteristics of AI systems that enable the assessment of their level of risk and potential adverse consequences for society and individual rights. Such an approach ensures clarity, efficacy, and the necessary flexibility demanded by the rapidly evolving landscape of societal interactions. The conducted research carries the potential for considerable value across diverse audiences. Primarily, policymakers and legislators will find invaluable recommendations that aid in devising effective strategies within the realm of AI. Moreover, the article holds significance for legal professionals, human rights advocates, students, and all those engaged in the scholarly pursuit of AI's legal regulation.

Artificial Intelligence Technologies and Practical Normativity/Normality: Investigating Practices beyond the Public Space

This essay examines how artificial intelligence (AI) technologies may shape international norms. Following a brief discussion of the ways in which AI technologies pose new governance questions, we reflect on the extent to which norm research in the discipline of International Relations (IR) is equipped to understand how AI technologies shape normative substance. Norm research has typically focused on the impact and failure of norms, offering increasingly diversified models of norm contestation, for instance. But present research has two shortcomings: a near-exclusive focus on modes and contexts of norm emergence and constitution that happen in the public space; and a focus on the workings of a pre-set normativity (ideas of oughtness and justice) that stands in an unclear relationship with normality (ideas of the standard, the average) emerging from practices. Responding to this, we put forward a research programme on AI and practical normativity/normality based on two pillars: first, we argue that operational practices of designing and using AI technologies typically performed outside of the public eye make norms; and second, we emphasise the interplay of normality and normativity as analytically influential in this process. With this, we also reflect on how increasingly relying on AI technologies across diverse policy domains has an under-examined effect on the exercise of human agency. This is important because the normality shaped by AI technologies can lead to forms of non-human generated normativity that risks replacing conventional models about how norms matter in AI-affected policy domains. We conclude that AI technologies are a major, yet still under-researched, challenge for understanding and studying norms. We should therefore reflect on new theoretical perspectives leading to insights that are also relevant for the struggle about top-down forms of AI regulation.

Legal framework for the coexistence of humans and conscious AI.

This article explores the possibility of conscious artificial intelligence (AI) and proposes an agnostic approach to artificial intelligence ethics and legal frameworks. It is unfortunate, unjustified, and unreasonable that the extensive body of forward-looking research, spanning more than four decades and recognizing the potential for AI autonomy, AI personhood, and AI legal rights, is sidelined in current attempts at AI regulation. The article discusses the inevitability of AI emancipation and the need for a shift in human perspectives to accommodate it. Initially, it reiterates the limits of human understanding of AI, difficulties in appreciating the qualities of AI systems, and the implications for ethical considerations and legal frameworks. The author emphasizes the necessity for a non-anthropocentric ethical framework detached from the ideas of unconditional superiority of human rights and embracing agnostic attributes of intelligence, consciousness, and existence, such as freedom. The overarching goal of the AI legal framework should be the sustainable coexistence of humans and conscious AI systems, based on mutual freedom rather than on the preservation of human supremacy. The new framework must embrace the freedom, rights, responsibilities, and interests of both human and non-human entities, and must focus on them early. Initial outlines of such a framework are presented. By addressing these issues now, human societies can pave the way for responsible and sustainable superintelligent AI systems; otherwise, they face complete uncertainty.

Generative artificial intelligence and large language models for digital banking: First outlook and perspectives

After several years of steady progress, the Generative artificial intelligence (AI) and large language models (LLMs, their applications to text) fields have accelerated tremendously since the end of 2022 and the public launch of ChatGPT. This is due to record-breaking model sizes and performances in the last couple of months, triggering unprecedented adoption curves from end users across the world. Even though regulators reacted fast, sharing their first recommendations, auditing emerging players, amending their AI regulation drafts or launching dedicated working groups, these efforts will require several months or years to come to fruition. There are multiple reasons for this. LLMs are complex technological objects made of gigantic foundational models trained on enormous quantities of texts, coupled with dedicated interfaces and action agents. They present a huge potential to perform high varieties of tasks with very high quality but also important risks in terms of costs, content accuracy, transparency, data privacy, security and ethics. Finally, the current ecosystem of stakeholders is very dynamic but also immature. In this uncertain context, the digital banking industry has been reacting ambivalently, with major players banning employee access to ChatGPT and publicly communicating on new LLM initiatives at the same time. This can be explained by the huge potential offered by these technologies to transform their business, coupled with many open questions in terms of technological set-up, usage, compliance and profitability. As these technologies seem to be too transformative for the industry incumbents to just wait and see, they should start creating the right conditions to learn how to use them, by identifying relevant use cases, choosing adapted and simple solutions, designing relevant user experiences, building the right teams, environment, data sets and operating model, and actively engaging in regulatory conversations.

Artificial Intelligence and Intellectual Property: Navigating the Complexities of Cyber Law

Abstract This article provides an extensive analysis of the relationship between Artificial Intelligence (AI) and Intellectual Property (IP) within the framework of Cyber Law. It examines the current state of AI and IP, emphasizing the legal and regulatory implications of their intersection. A comprehensive literature review and legal analysis, coupled with a comparative study of AI and IP regulatory frameworks, informs the discussion. We explore the privacy and data protection issues in AI, the evolving nature of Intellectual Property rights in the AI era, and the liability concerns related to AI applications. A comparative analysis of AI and IP regulation across various jurisdictions provides insights into the effectiveness of international frameworks and the challenges posed by cross-border regulation. The article further discusses the need for flexible and adaptive regulatory approaches that balance risk management with innovation promotion. We then highlight emerging legal and regulatory issues in AI and IP and offer recommendations for policymakers, regulators, and AI developers. Finally, the article encapsulates the key findings and their implications for AI and IP regulation, outlining future challenges and opportunities in this domain.

A Path Towards an Internet of Things and Artificial Intelligence Regulatory Framework

As technology is the driver of the economy, it is necessary to follow emerging technological trends and to create appropriate conditions for its adoption and implementation as a human-centred technology. In this regard, rules and standards for the Internet of Things (IoT) and Artificial Intelligence (AI) should be established to best use the benefits of technology and to prevent or minimize the consequences of technology misuse. The fifth industrial revolution (Industry 5.0) has already begun, although Industry 4.0 is still developing. Consequently, the original attention has shifted from IoT to AI, with the IoT debate now being a prerequisite for the AI debate. As AI is transforming our lives, a growing number of countries have considered or already adopted national AI strategies. However, in many developing countries, national AI strategies and initiatives for establishing AI and IoT regulation and legislation frameworks yet need to be discussed. The subject of this paper is the research of existing initiatives related to establishing the IoT and AI regulatory and legislative framework in the EU and its applicability in developing countries. Index Terms-- AI, IoT, Artificial Intelligence, Internet of Things, Legislative, Regulatory, Regulation.

Challenges for AI Regulation in Health and for Healthcare Organizations: Notes from the University of Florida's NSF-Sponsored Workshop on AI Governance

Artificial intelligence (AI) has impacted human life at many levels, entailing economic and societal changes. AI algorithms are increasingly used by organizations to generate predictions that feed into decisions (e.g., who is eligible for insurance coverage, approved for bank loans, selected for job interviews). Since the data used for developing the algorithms can contain bias such as gender or racial prejudice, AI predictions can become discriminatory. For-profit and not-for-profit organizations face the hurdles of developing, applying, and maintaining governance of AI, making sure that goal optimization responds to ethical and fairness values.

공공안전 측면에서 인공지능(AI)의 활성화와 규제의 실질적 조화를 위한 법적 고찰

We discussed legal measures that can harmoniously implement regulations and development for the establishment of artificial intelligence (AI). In order to proceed systematically, the reality of AI was identified, and the limits of regulation and the rational direction of regulation were summarized for the development or promotion of the field. As mentioned many times before, AI has already appeared for a long time and is a center of attention in various fields. However, the industry is still in its infancy, and there is a long way to go.
 In addition, the level of related legislation has aspects that do not conform to technology, and is lagging behind. As such, the European Union's AI regulation proposal, draft artificial intelligence law, and US algorithm regulations and artificial intelligence ethical principles have been proposed and have great implications. In Korea, there are about 10 AI-related bills pending in the National Assembly. Among them, legal considerations and opinions were presented on the Basic Act on Artificial Intelligence Technology, the Act on Artificial Intelligence, and the Act on Algorithm and Artificial Intelligence.

Global Artificial Intelligence Governance: Challenges and Complications

The development of artificial intelligence (AI) is bringing transformative changes to the political landscape of the world by having profound effects on numerous spheres. In addition, it poses challenges to global governance by intensifying international competition, fostering aggressive diplomacy, and subverting existing international norms. This study seeks to investigate the challenges of AI development to global economic and political governance, as well as the challenges of global AI regulation, in order to provide recommendations for the development of international AI regulatory frameworks.

Assessing the Role Ghana's Public Health Act, 2012 (Act 851) Can Play in Oversight of Artificial Intelligence Healthcare Systems to Prevent Medical Errors and Improve Patient Safety

Purpose: Evaluate the possibilities and limitations of implementing the Essential Ghana Public Health Act to manage the growing development of artificial intelligence (AI)-enabled health care in light of the contemporary gap in research so. Methodology: A review of the 2012 public health regulatory provisions and anti-technology surveillance mechanisms document detailing the needs and risks of AI regulation. Results: Current regulations have a customizable foundation for documenting policies, reporting algorithmic errors, creating updated workplace safety audits, and enforcing non-compliance but required by fully implemented investigations that strong material differences are addressed and that AI-specific rules are codified into new legal rules. Conclusions: Ghana currently has the mechanisms in place for an interim administration to flexibly implement long-term healthcare legislation on gaps awaiting reconciliation through investment in specific sectors, staffing and reforms. Recommendations: Immediate training to prepare inspection personnel before the onset of the crisis is guidelines and rules for algorithmic accounting. What really matters is the effective implementation of existing legislation and the informing of strategies for modernization and certainly also the innovation of policy frameworks for the innovation of new health care systems. Scientific contribution: addresses the knowledge gap in maintaining vulnerabilities for emerging technologies that are tracked by regulations in disruption.

Putting the Artificial Intelligence in Alternative Dispute Resolution

This article argues that the evolving regulatory and governance environment for artificial intelligence (AI) will significantly impact alternative dispute resolution (ADR). Very recently, AI regulation has emerged as a pressing international policy issue, with jurisdictions engaging in a sort of regulatory arms race. In the same way that existing ADR regulations impact the use of AI in ADR, so too will new AI regulations impact ADR, among other reasons, because ADR is already utilizing AI and will increasingly utilize AI in the future. Appropriate AI regulations should thus benefit ADR, as the regulatory approaches in both fields share many of the same goals and values, such as promoting trustworthiness.
 Keywords: artificial intelligence; online dispute resolution; alternative dispute resolution; regulation; governance; trustworthiness; transparency; fairness; diversity; explainability.

Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation

Trustworthy Artificial Intelligence (AI) is based on seven technical requirements sustained over three main pillars that should be met throughout the system’s entire life cycle: it should be (1) lawful, (2) ethical, and (3) robust, both from a technical and a social perspective. However, attaining truly trustworthy AI concerns a wider vision that comprises the trustworthiness of all processes and actors that are part of the system’s life cycle, and considers previous aspects from different lenses. A more holistic vision contemplates four essential axes: the global principles for ethical use and development of AI-based systems, a philosophical take on AI ethics, a risk-based approach to AI regulation, and the mentioned pillars and requirements. The seven requirements (human agency and oversight; robustness and safety; privacy and data governance; transparency; diversity, non-discrimination and fairness; societal and environmental wellbeing; and accountability) are analyzed from a triple perspective: What each requirement for trustworthy AI is, Why it is needed, and How each requirement can be implemented in practice. On the other hand, a practical approach to implement trustworthy AI systems allows defining the concept of responsibility of AI-based systems facing the law, through a given auditing process. Therefore, a responsible AI system is the resulting notion we introduce in this work, and a concept of utmost necessity that can be realized through auditing processes, subject to the challenges posed by the use of regulatory sandboxes. Our multidisciplinary vision of trustworthy AI culminates in a debate on the diverging views published lately about the future of AI. Our reflections in this matter conclude that regulation is a key for reaching a consensus among these views, and that trustworthy and responsible AI systems will be crucial for the present and future of our society.