Attribution Of Liability Research Articles

China’s Legal Practices Concerning Challenges of Artificial General Intelligence

The artificial general intelligence (AGI) industry, represented by ChatGPT, has impacted social order during its development, and also brought various risks and challenges, such as ethical concerns in science and technology, attribution of liability, intellectual property monopolies, data security, and algorithm manipulation. The development of AI is currently facing a crisis of trust. Therefore, the governance of the AGI industry must be prioritized, and the opportunity for the implementation of the Interim Administrative Measures for Generative Artificial Intelligence Services should be taken. It is necessary to enhance the norms for the supervision and management of scientific and technological ethics within the framework of the rule of law. Additionally, it is also essential to continuously improve the regulatory system for liability, balance the dual values of fair competition and innovation encouragement, and strengthen data-security protection systems in the field of AI. All of these will enable coordinated governance across multiple domains, stakeholders, systems, and tools.

AI in Radiology: Navigating Medical Responsibility.

The application of Artificial Intelligence (AI) facilitates medical activities by automating routine tasks for healthcare professionals. AI augments but does not replace human decision-making, thus complicating the process of addressing legal responsibility. This study investigates the legal challenges associated with the medical use of AI in radiology, analyzing relevant case law and literature, with a specific focus on professional liability attribution. In the case of an error, the primary responsibility remains with the physician, with possible shared liability with developers according to the framework of medical device liability. If there is disagreement with the AI's findings, the physician must not only pursue but also justify their choices according to prevailing professional standards. Regulations must balance the autonomy of AI systems with the need for responsible clinical practice. Effective use of AI-generated evaluations requires knowledge of data dynamics and metrics like sensitivity and specificity, even without a clear understanding of the underlying algorithms: the opacity (referred to as the "black box phenomenon") of certain systems raises concerns about the interpretation and actual usability of results for both physicians and patients. AI is redefining healthcare, underscoring the imperative for robust liability frameworks, meticulous updates of systems, and transparent patient communication regarding AI involvement.

Legal implications of using generative AI in the media

ABSTRACT Generative AI is increasingly being used, among others also in the professional media industry. This article provides an overview of the main ethical and legal challenges regarding content generated by, or with the help of generative AI. Among the ethical challenges, special attention is devoted to the development of journalistic standards. The legal discussion highlights the questions of civil and criminal responsibility regarding content, with a primary focus on the attribution of liability. It scrutinises the roles of deployers, assessing their contributions to the final product. It suggests that all human participants’ contributions should be accordingly acknowledged, potentially necessitating the creation of novel categories such as hybrid authorship and shared responsibility.

Attribution of Liability for Copyright Infringement by Artificial Intelligence Generated Content

As generative artificial intelligence continues to advance, providing an ever-expanding range of functions and applications for humanity, it has given rise to novel forms of torts, with the potential for more to emerge in the near future. Resolving issues of liability hinges on the identification of the responsible party. However, neither Chinese legislation nor academic views have specified rules or a clear and consistent opinion on the liability attribution issue. This paper aims to address this question. Commencing with the premise that artificial intelligence inherently lacks legal personality, this paper systematically examines all relevant subjects who could potentially bear liability for copyright infringement. The legal foundations for each entitys liability are thoroughly analysed. Meanwhile, this article elucidates the principles of attribution of liability, drawing from established theories of traditional tort law and jurisprudential principles while taking into account the special characteristics of copyright infringement and artificial intelligence. In conclusion, in the absence of a clear consensus on determining the liable party, the principle of correspondence between risks, benefits and responsibilities should guide the attribution of liability for copyright infringement involving generative artificial intelligence. This approach will ensure an equitable distribution of losses, responsible burden-sharing, and comprehensive protection of rights.

The Twofold Role of Legal Liability Misattribution on Intention to Buy Automated Vehicles: A Survey in China

Liability attribution for crashes involving automated vehicles (AVs), if applied improperly, is a factor which can potentially hinder acceptance. The present study investigated the impact of liability attribution on intention to buy an AV. A vignette-based survey was implemented with a hypothetical crash similar to the 2018 Uber crash (which was jointly caused by driver distraction and the malfunctioning of the automated system) leading to a pedestrian’s fatality. Respondents (N = 1524) chose their preferred liability attribution, ranging from human driver exclusively liable to AV manufacturer exclusively liable. Respondents were then randomly allocated to different conditions of actual liability attribution by the local authority. These conditions were then combined into, negative misattribution (the authority assigned more liability to the human driver, compared to the respondent), positive misattribution (the authority assigned less liability to the human driver), and no misattribution. Negative misattribution negatively affected intention to buy; however, positive misattribution did not have a significant impact. The results of a multiple-mediator model indicated that negative misattribution affects intention to buy through the mediating effects of trust, negative affect, and crash acceptability. Theoretical and practical implications of our results are discussed.

An Analysis of Judicial Decision on Sports Injury Accidents in Schools and a Study on Risk Avoiding Measures

By using the research methods of judicial case analysis and mathematical statistics analysis, this study analyzes 20 typical cases of school sports injury accidents published by “China Judgements Online”. The findings show that injuries occurred most often to primary and middle school students, and the courts restored the facts of the cases clearly and accurately; in the process of liability attribution, the fault principle, the equity principle and the risk assumption principle were mainly adopted. For the same type of injury accidents, the court decisions were not the same, and in the vast majority of cases, the schools bore civil liabilities. In order to reduce student injury accidents in PE teaching and other sports activities in schools and reduce the liabilities of schools, this study proposes the measures of “one qualified, one insured and nine in place,” that is, “ensuring that equipment is qualified, buying special insurances, teacher training in place, inspections in place, anticipation in place, design in place, cautions in place, protection in place, handling in place, reporting in place and care in place.”

Algorithmic discrimination at work

The potential for algorithms to discriminate is now well-documented, and algorithmic management tools are no exception. Scholars have been quick to point to gaps in the equality law framework, but existing European law is remarkably robust. Where gaps do exist, they largely predate algorithmic decision-making. Careful judicial reasoning can resolve what appear to be novel legal issues; and policymakers should seek to reinforce European equality law, rather than reform it. This article disentangles some of the knottiest questions on the application of the prohibition on direct and indirect discrimination to algorithmic management, from how the law should deal with arguments that algorithms are ‘more accurate’ or ‘less biased’ than human decision-makers, to the attribution of liability in the employment context. By identifying possible routes for judicial resolution, the article demonstrates the adaptable nature of existing legal obligations. The duty to make reasonable accommodations in the disability context is also examined, and options for combining top-level and individualised adjustments are explored. The article concludes by turning to enforceability. Algorithmic discrimination gives rise to a concerning paradox: on the one hand, automating previously human decision-making processes can render discriminatory criteria more traceable and outcomes more quantifiable. On the other hand, algorithmic decision-making processes are rarely transparent, and scholars consistently point to algorithmic opacity as the key barrier to litigation and enforcement action. Judicial and legislative routes to greater transparency are explored.

The Awkward Middle for Automated Vehicles: Liability Attribution Rules When Humans and Computers Share Driving Responsibilities

The Awkward Middle for Automated Vehicles: Liability Attribution Rules When Humans and Computers Share Driving Responsibilities

The difficult role of Artificial Intelligence in Medical Liability: to err is not only human.

The entrance of Artificial Intelligence (AI) as a new actor in the doctor-patient relationship has encouraged important legal and ethi-cal considerations among the experts. On the one hand, there is the request to establish a new and dedicated legal background involving AI and AI-related technologies, while others believe there is no need to add new laws in the attempt to define AI's role in healthcare. The aim of this paper is to analyse the possible role of AI in civil liability in healthcare practice, underlining its limits of autonomy in a field where the attribution of liability cannot be uncertain.

Liability Attribution in the Context of AI Use

AI (artificial intelligence) systems represent a double-bladed sword. AI brings both benefits and harms to our society. When adverse consequences are produced by AI use in practice, responsibility gaps emerge, due to the opacity and complex nature of these sociotechnical systems. In this study, we propose that assigning liabilities collectively among AI actors can bridge the responsibility gap, hence promoting justice and ethical uses of AI in society. We do so by drawing on the field of philosophy and attempting to answer the question of how (to whom and to what extent) responsibility can be allocated to reduce accountability gaps in the AI context. We generate a set of propositions that lay out the ground for future research this important interdisciplinary domain.

Autonomous Space Objects and International Space Law: Navigating the Liability Gap

The introduction of advanced new technologies is transforming the space industry. Artificial intelligence is offering unprecedented possibilities for space-related activities because it enables space objects to gain autonomy. The increasing autonomy level of space objects does not come without legal implications. The lack of human control challenges existing liability frameworks. This paper reviews the provisions of the Outer Space Treaty and the Liability Convention as the main legal documents introducing the legal grounds for attributing liability in case of damages caused by autonomous space objects. Looking at the limitations of these legal frameworks in what concerns the attribution of liability, this paper identifies the conditions that could cause a liability gap. The amendment of the Liability Convention, the concept of “international responsibility” introduced by Article VI of the Outer Space Treaty and several international law principles are analysed as potential solutions for preventing the liability gap and mitigating the risks posed by autonomous space objects.

Artificial Intelligence Ethics Supervision in China: Demand Analysis and Countermeasures

The rapid development of artificial intelligence (AI) industry is accompanied by various social ethical risks, and the consequences of these risks have gradually emerged. Allowing humans to securely enjoy the major benefits of AI technology has become an important task of AI supervision. In this article, we first analyze the focus issues of AI ethics, including the distribution of machine and human rights, social trust crisis of AI, security of data and algorithms, as well as confirmation of rights and attribution of liability. Subsequently, we summarize the development paths and policy status of AI industry in China and abroad, and analyze the demand for AI ethical supervision in China from multiple dimensions. Furthermore, we suggest that the supervision scope of AI should be extended in a staged manner based on the technical progress of AI. To create better global development opportunities for China’s AI industry, a multi-dimensional supervision framework that combines ethics, law, and policy should be established, a sufficient social discussion space should be provided for all stakeholders to participate in public discussion on AI security, scientific and technological ethics supervision organizations of multiple levels should be improved in an orderly manner, and China should actively participate in the formulation of AI international rules.

L’obsolescenza dell’art. 603-bis c.p. e le nuove forme di sfruttamento lavorativo

Article 603-bis of the Criminal Code describes the case of exploitation of labour through the so-called indices of exploitation. The use of this innovative contextual typification technique has application limits, since the indices almost exclusively refer to regulatory parameters typical of subordinate labour. A rigid application of these indices therefore risks excluding from criminal protection forms of degradation of work now widespread in various production contexts, when formally the work is not attributable to the case of subordination. In order to overcome this possible gap in protection, there are two alternatives: either disregard the indices with respect to these new forms of exploitation, or assimilate platform work to subordinate work. However, while it is impracticable, from several points of view, to renounce the indices of exploitation, given the low selective capacity of the typical fact referred to in Article 603-bis of the Criminal Code, the possibility of equating platform work with subordination seems less problematic. However, even if the highlighted obstacles were to be considered surmountable by way of interpretation, further difficulties arise with respect to the multifaceted structure of the global enterprise, where it is increasingly difficult to identify a decision-making centre. This obviously poses problems for the attribution of liability, in view of the fact that there is no regulation of criminal liability in groups of companies and no independent criminal case for those who knowingly benefit from degraded work.

Roman Slavery Law: A Competent Answer of how to Deal With Strong Artificial Intelligence? Review of Robot Rights with View of Czech and German Constitutional Law and Law History

One basic aim of law is the correct attribution of liability. Natural or legal persons have to bear responsibility after infringing other parties’ legal interests. Normally the damaging party has to compensate the damages caused by his/her deeds. In many cases the attribution of responsibility appears easy and unambiguous. Though, this only applies in cases where there is an actual person behind the infringement. Attributing liability appears to be highly complex in cases of artificial intelligence (AI). When significant technological innovations appear, especially if these innovations manage to bring major changes in the division of labour, or even changes in society, the regulations concerning liability are often questioned. Today, law distinguishes between the holder/user, programmer, and producer. This may be sufficient for today’s technology and today’s development in AI. Though, these cases still manage to pose a challenge for our modern legislation. Since technology and also AI advance rapidly, this problem is not going to be any less complicated in close, but also in far future. Here it makes sense to take old legislations as “inspiration” for present and future law-making, in this case antic roman slave-law, as the antic romans faced similar problems and opted for partly similar solutions as modern legislations.

Exploring the prospects of host-state counterclaims in corruption disputes

Abstract While the regime of investment treaty arbitration has evolved manifold over the decades, has the position of the host-states as a Respondent improved? The authors argue that it has not. Bilateral Investment Treaties (hereinafter BIT(s)) are still asymmetrical in nature where the states are obliged to protect the rights of the foreign investors but are not provided with any remedy against the corrupt activities of the investors. While tribunals have denied jurisdiction over the investors’ claims tainted with corruption, they have provided states with no consequent remedy against such investors. Consequently, the states have to first bear the loss of a failed investment in its territory and then pay for the exorbitant costs of international arbitration as well. Where scholars are arguing for attribution of liability of corrupt activities of the public officials to the states, the authors here raise an important question of what if the liability cannot be attributed to the states due to lack of apparent authority? Should the states be then allowed to move forward from the jurisdictional stage to raise counterclaims to seek damages for the loss caused by the investors? In this article, the authors explore these questions and present arguments in favour of the inclusion of corruption-based counterclaims.

Le misure anti-Covid19 nei luoghi di lavoro: dalla (sicura) emergenza sanitaria alla (temuta) emergenza sanzionatoria

The essay deals with the problems triggered by art. 42, para. 2 of the Decree “Cura Italia” that assimilates the cases of confirmed Coronavirus infection at work to cases of injury. Among the issues addressed, there is the dreaded “sanctioning emergency” that would result from the initiation of criminal proceedings to ascertain the employer's responsibility in the event of a contraction of the Covid-19 illness by a worker. The A., first of all, makes some proposals on how to manage the overburdening of the prosecution offices by speeding up preliminary investigations. He then provides some answers to the problem of possible exemption from liability for the employer if all the measures provided in the Decrees have been complied with. After pointing out the potential decisive nature of the lack of scientific knowledge about the pathogenesis related to the virus, in parallel with the judicial experience in the field of asbestos diseases, it is argued that even if the legislator ensures the absolute determination of the precautionary rules, there would be no certainty for the employer complying with them to be exempt from liability. The effort to be made is rather a rethinking of the criterion of guilt which, drawing on the experience of medical liability, offers more appropriate criteria for the attribution of liability.

The Criminal Liability of the Compliance Officer: An Approach Through Several Hard Cases

There is broad consensus in the academic legal opinion that traditional theories on perpetration and participation are insufficient to determine criminal liability in complex organisational structures, in particular in the business sector. Corporate activity rarely takes place through the implementation of naturalistic actions; it is more often a matter of adopting agreements reached by management bodies. Consequently, when determining perpetration, the decisive element is displaced from actual commission to the taking of strategic decisions, or even failure to avoid the criminal conduct committed by a third party. In this context, it is hardly surprising that particular relevance falls upon the attribution of liability for commission by omission. This would also be motivated by reasons of a practical nature: without evidence of actual commission of the offence, it would doubtlessly be easier to attest that the crime committed by someone lower down in the hierarchy had taken place in the sphere of competence of a hierarchical superior (administrator or senior manager) who, though able to prevent it, failed to do so. Based on this twofold premise, this paper sets out to reflect upon one of the new corporate subjects arising out of the reforms introduced by Organic Laws 5/2010 and 1/2015 in the field of criminal liability of legal persons and crime prevention models (corporate criminal compliance): the compliance officer.

Law and software agents: Are they “Agents” by the way?

Using intelligent software agents in the world of e-commerce may give rise to many difficulties especially with regard to the validity of agent-based contracts and the attribution of liability for the actions of such agents. This paper thus critically examines the main approaches that have been advanced to deal with software agents, and proposes the gradual approach as a way of overcoming the difficulties of such agents by adopting different standards of responsibility depending whether the action is done autonomously by an unattended software, or whether it is done automatically by an attended software. Throughout this paper, it is argued that the introduction of “one size” regulation without sufficient consideration of the nature of software agents or the environments in which they communicate might lead to a divorce between the legal theory and technological practice. It is also concluded that it is incorrect to deal with software agents as if they were either legal persons or nothing without in any way accounting for the fact that there are various kinds of such agents endowed with different levels of autonomy, mobility, intelligence, and sophistication. However, this paper is not intended to provide the final answer to all problematic questions posed by the emergence of intelligent software agents, but is designed to provide some kind of temporary relief until such agents reach a more reliable and autonomous level whereby law begins to regard them, rather than their users, as the source of the relevant action.

The Application of Current Antitrust Law to Explicit Collusion by Autonomously Acting Pricing Algorithms

This paper aims to answer the question whether the current (EU) antitrust law is well-equipped to deal with explicit collusion by pricing algorithms that act independently from the companies using them. The paper unfolds in three main parts: first, it outlines the exact circumstances of the later discussed scenario and the differentiation to other ways in which algorithms can be related to infringements of antitrust law. Then it investigates whether the use of algorithms specified in the first part falls under the scope of antitrust law in general, that is whether the term 'agreement' according to Art. 101 (1) TFEU is applicable to independently acting algorithms or whether any other tool of current antitrust law (here: concerted practices) enables for the application of Art. 101 (1) TFEU to algorithmic price-setting. Finally, it assesses if the company using the algorithm can be held responsible for any breach of antitrust law that the algorithm is engaged in. It does so by applying the concept of attribution of liability for acts of employees to the employing firm. My hypothesis is that there is no fundamental difference between the conduct of deep learning algorithms and human employees and that as a result the same principles of attribution of liability to firms can be applied.

The Question of Autonomy, Liability Attribution and Black Boxes Decision Making

The Question of Autonomy, Liability Attribution and Black Boxes Decision Making