Strict Liability Regime Research Articles

Product liability in modern conditions: European reform experience

At the end of September 2022, the European Commission presented two notable documents designed to fundamentally change the current system of product liability in Europe. In part, these projects were a response to the challenges posed by digitalization and modern technology. The first document is designed to regulate liability for harm caused by artificial intelligence systems, while the second is aimed at adapting the EU Council Directive of July 25, 1985 No. 85/374/EEC to contemporary conditions. The present article sets out to review the key developments in the field of product liability in Europe. To this end, a review of the existing system of product liability in Europe is carried out. The existing product liability system is comprised of two parts: norms enshrined in national laws, as well as harmonized liability under the EU Council Directive of July 25, 1985 No. 85/374/EEC 1985. However, there is no consensus in European doctrine and practice regarding the regime of harmonized liability. While on the one hand, this regime is based on the idea of strict liability, on the other hand, there is also a reasoned opinion that the Directive factually establishes a regime of liability based on fault. On the example of German law, it is revealed that, despite the strict liability regime approved by special law, courts often focus in practice on a manufacturer’s breach of the duty of care, which once again testifies to liability based on fault. Possible factors behind the decision on the part of the European regulator to reform the existing liability system include: the increasing complexity of the goods themselves; the expansion of intermediary chains and emergence of new potential subjects of liability, including owners of aggregators; difficulties in proving the existence of a product defect and a causal link between such a defect and the resulting harm; the concept of harm in the digital age and the special role of data; providers’ liability for goods equipped with artificial intelligence technology.

The Proposal for a Directive on Defective Products: A Game Changer for Innovative Medicinal Products.

At the end of 2022, the European Commission published a proposal for a directive to revise the strict liability regime introduced in 1985. Although the main goal of this new proposal is to adapt the regulations to information technologies such as artificial intelligence, it has multiple impacts on other economic sectors, including the pharmaceutical market. Therefore, this proposal could change the deal in terms of liability in this specific market. Indeed, the proposal modifies the burden of proof, which can be quite challenging to establish in the case of adverse effects of medicinal products. It introduces a possible presumption of liability for a manufacturer who fails to communicate, to a court, the information they required, which might jeopardise the protection of trade secrets and commercial confidentiality. In addition, the proposal also extends the limitation period, and more importantly, it mandates the application of the 'development risk defence.'

Disciplining Orders Under the National Financial Reporting Authority Framework: Stepping into a Strict Liability Regime

Disciplining Orders Under the National Financial Reporting Authority Framework: Stepping into a Strict Liability Regime

Artificial intelligence and civil liability—do we need a new regime?

Abstract Artificial intelligence (AI) is almost ubiquitous, featuring innumerable facets of daily life. For all its advantages, however, it carries risks of harm. In this article, we discuss how the law of tort should deal with these risks. We take account of the need for any proposed scheme of liability to protect the existing values of tort law without acting as a barrier to innovation. To this end, we propose a strict liability regime in respect of personal injury and death, and a bespoke fault-based regime for dignitary or reputational injuries. For other losses, we take the view that there is no justification for introducing any new regime, on the basis that AI applications do not introduce substantial added degrees of risk that would justify departing from the existing scheme of liability arising under the current law of tort.

Suggestions for a Revision of the European Smart Robot Liability Regime

In recent years, the need for regulation of robots and Artificial Intelligence, together with the urgency of reshaping the civil liability framework, has become apparent in Europe. Although the matter of civil liability has been the subject of many studies and resolutions, multiple attempts to harmonize EU tort law have been unsuccessful so far, and only the liability of producers for defective products has been harmonized so far. In 2021, by publishing the AI Act proposal, the European Commission reached the goal to regulate AI at the European level, classifying smart robots as ”high-risk systems”. This new piece of legislation, albeit tackling important issues, does not focus on liability rules. However, regulating the responsibility of developers and manufacturers of robots and AI systems, in order to avoid a fragmented legal framework across the EU and an uneven application of liability rules in each Member State, is still an important issue that raises many concerns in the industry sector. In particular, deep learning techniques need to be carefully regulated, as they challenge the traditional liability paradigm: it is often not possible to know the reason behind the output given by those models, and neither the programmer nor the manufacturer is able to predict the AI behavior. For this reason, some authors have argued that we need to take liability away from producers and programmers when robots are capable of acting autonomously from their original design, while others have proposed a strict liability regime. This article explores liability issues about AI and robots with regards to users, producers, and programmers, especially when the use of machine learning techniques is involved, and suggests some regulatory solutions for European lawmakers.

Suggestions for a Revision of the European Smart Robot Liability Regime

In recent years, the need for regulation of robots and Artificial Intelligence, together with the urgency of reshaping the civil liability framework, has become apparent in Europe. Although the matter of civil liability has been the subject of many studies and resolutions, multiple attempts to harmonize EU tort law have been unsuccessful so far, and only the liability of producers for defective products has been harmonized so far. In 2021, by publishing the AI Act proposal, the European Commission reached the goal to regulate AI at the European level, classifying smart robots as ”high-risk systems”. This new piece of legislation, albeit tackling important issues, does not focus on liability rules. However, regulating the responsibility of developers and manufacturers of robots and AI systems, in order to avoid a fragmented legal framework across the EU and an uneven application of liability rules in each Member State, is still an important issue that raises many concerns in the industry sector. In particular, deep learning techniques need to be carefully regulated, as they challenge the traditional liability paradigm: it is often not possible to know the reason behind the output given by those models, and neither the programmer nor the manufacturer is able to predict the AI behavior. For this reason, some authors have argued that we need to take liability away from producers and programmers when robots are capable of acting autonomously from their original design, while others have proposed a strict liability regime. This article explores liability issues about AI and robots with regards to users, producers, and programmers, especially when the use of machine learning techniques is involved, and suggests some regulatory solutions for European lawmakers.

CONTRIBUTORY FAULT AND ITS ASSESSMENT IN THE LIABILTY OF THE INSURANCE COMPANY ARISING FROM THE OPERATION OF THE MOTOR VEHICLE

İşletilme halindeki motorlu aracın sebep olduğu zarara ilişkin olarak KTK m. 85/1 hükmünde bir kusursuz sorumluluk rejimi olan tehlike sorumluluğu kabul edilmiştir. Sigorta şirketi, KTK m. 85/1 kapsamında meydana gelen zarardan belli meblağa kadar sorumludur. Sigorta şirketi, araç sürücüsünün/işletenin kusurlu olmadığından/az kusurlu olduğundan bahisle tazminatta indirim talep edemez. Sigorta şirketlerinin, sürücünün kusurlu olmadığını ileri sürmesi anlamsız olduğu gibi, belirli bir oran vererek (%30-40-50) kusurlu olduğunu beyan etmesi, ek (munzam) kusurun ifşasından başka bir şey değildir. Ek kusur da tazminattan indirim sebebi değil, aksine kusurun ağırlığına göre indirimi ortadan kaldıran bir haldir. Zarar görenin kusuru ise, kusurun ağırlığına ve kanunda aranan diğer şartların varlığı halinde sigorta şirketinin motorlu aracın işletilmesinden doğan sorumluluğunda tazminattan indirim sebebi teşkil edebilir. Zarar görenin kusuruna dayanarak tazminattan indirim yapılmasını talep eden sigorta şirketi, zarar görenin kusurunu ispat yükü altındadır. Yargıtay kararlarında da kabul edildiği üzere, zarar görenin kusuru, gerek nedensellik bağının kesilmesine sebep olduğu durumlar bakımından sorumluluğu (ve bu bağlamda hakkı) ortadan kaldırması hasebiyle gerekse tazminattan indirim sebebi olarak hakkı sınırlandırması yönüyle hukuk hâkimi (hakemi) tarafından re’sen (kendiliğinden) dikkate alınmalıdır.

Pull yourself up by your bootstraps: Identifying procedural preferences against helping others in the presence of moral hazard

Governments and organizations often implement policies designed to help people affected by undesirable events. Such policies can make the society better off, but they may also create moral hazard. We use a laboratory experiment to examine two questions. First, can discretionary decisions to provide assistance overcome the problem of moral hazard and lead to higher efficiency? Second, if so, will people prefer this discretionary procedure to the strict liability policy in which no assistance is provided? We find that assistance is more efficient than a strict liability procedure. However, people still prefer the strict liability regime over assistance. We conduct additional treatments that show that this effect is not driven by the presence of human discretion, nor by aversion to risk, ambiguity, loss or inequality. This suggests that when moral hazard is a concern people have procedural preferences in favor of strict liability.

Implementation of professional activity as an alternative to guilt in civil law: theory and practice

The subject of this research is the legal norms, doctrinal provisions and case law on the conditions of civil liability. The relevance of this topic is determined by the tendency to expand the list of cases of strict liability detected in comparison the current and Soviet legislation. However, the principle observed by the legislator in transferring cases from the "regime of fault liability" to the "regime of strict liability" is still a puzzle. For the purpose of systematicity of legislation and reasonable claim of strict liability, such principle should be captured in legislation. The goal of this research lies in determination of the condition of civil liability without fault. Using the method of legal induction, the author formulates the conclusion on the condition of strict liability based on the analysis of separate court decisions and legal norms dedicated to various cases of strict liability. A number of cases of civil liability without fault specified in the law are substantiated by a different (instead of fault) condition of liability, namely the implementation of professional activity that entailed civil violation. If the case of liability without fault specified in the law does not contain any other condition of liability alternative to fault, the corresponding rule should be excluded from the law due to groundlessness (for example, the rule on strict liability for obligations of the trustee in relation to individuals who are not the subjects of professional activity in this sphere; the rule on compensation for moral damages irrespective of guilt for distribution of discrediting information by a person who is not a professional distributor of mass media products). The author offers to legislate the principle of civil strict liability.

Unreasonable: A Strict Liability Solution to the FTC’s Data Security Problem

For over two decades, the FTC creatively employed its capacious statute to police against shoddy data practices. Although the FTC’s actions were arguably needed at the time to fill a gap in enforcement, there are reasons to believe that its current approach has outlived its usefulness and is in serious need of updating. In particular, our analysis shows that the FTC’s current approach to data security is unlikely to instill anything close to optimal incentives for data holders. These shortcomings cannot be fixed through changes to the FTC enforcement approach, as they are largely generated by a mismatch between the tools that Congress gave it over a century ago and what it needs to foster firms’ incentives to mimic socially optimal levels of care for the data they hold. Not only does the current framework likely suffer from informational deficiencies attendant to its focus on “reasonable” security that render liability standards uncertain, it also lacks the ability to obtain the type of relief that will force firms to internalize the costs of their data security decisions. We examine the problem of data security enforcement through the lens of the economics of optimal precautions and identify several reasons why a strict liability regime administered by the FTC, under which firms pay for the expected harm from breaches they cause, is likely to be superior to the current framework that revolves around the concept of reasonableness. The benefits of strict liability flow from the likelihood that firms do not fully internalize the costs and benefits of their data security decisions and the relatively large informational burdens associated with measuring actual and optimal care under a negligence regime. We also show why in this informational environment, strict liability is better than negligence for developing a vibrant cyber insurance market, allowing for data security regulation to be de facto outsourced to insurers who will contract with firms for optimal levels of care. Because these private contracts will harness private information on costs and benefits from precautions, they are likely to incentivize more efficient behavior.

A Sandbox Approach to Regulating High-Risk Artificial Intelligence Applications

AbstractThis paper argues for a sandbox approach to regulating artificial intelligence (AI) to complement a strict liability regime. The authors argue that sandbox regulation is an appropriate complement to a strict liability approach, given the need to maintain a balance between a regulatory approach that aims to protect people and society on the one hand and to foster innovation due to the constant and rapid developments in the AI field on the other. The authors analyse the benefits of sandbox regulation when used as a supplement to a strict liability regime, which by itself creates a chilling effect on AI innovation, especially for small and medium-sized enterprises. The authors propose a regulatory safe space in the AI sector through sandbox regulation, an idea already embraced by European Union regulators and where AI products and services can be tested within safeguards.

An Environmental Risk Assessment of Filling Stations Using the Principles of Security Management. A Case Study in the Slovak Republic

The issue of environmental risk assessment currently deserves great attention. In order to protect the environment, maintain healthy living conditions, and prevent environmental damage, the member states of the European Union have adopted a Directive of the European Parliament and of the Council on environmental liability with regard to the prevention and remedying of environmental damage. The directive classifies two types of operators with different liability regimes for environmental damage, namely, the regime with no-fault (strict) liability and liability for fault. With the adoption of the directive, among experts, operators and the general public have posed questions about how to assess the risk of environmental damage. At present, there is still no uniform procedure for assessing environmental risks, which would create a comprehensive methodological framework for assessment for this type of risk. Due to the non-existent risk assessment methodology for operators with strict liability regimes and the lack of a systematic search for risk sources, a risk assessment procedure is proposed that provides guidance in a sequence of several steps on how to implement the obligations arising from the adopted Environmental Liability Directive. The proposed procedure was verified on a specific operator with a strict liability regime. The environmental risk analysis performed through the proposed procedure provided information on possible operational problems and verified its applicability. Last but not least, the use of the proposed procedure makes it possible to identify serious sources of risk and to establish necessary preventive measures to prevent the occurrence of environmental damage.

Strict Products Liability 2.0: The Triumph of Judicial Reasoning Over Mainstream Tort Theory

Abstract Strict products liability has evolved in a manner that is widely misunderstood. The liability rule was first formulated to govern defective products that did not minimally perform one of their ordinary functions as expected by consumers—a malfunction that violates the implied warranty of quality. After adopting this rule, courts began applying it to products that did not malfunction and found that a test for defect based on consumer expectations often is indeterminate or can otherwise unduly limit liability in an important class of cases. To address these problems, most courts adopted the risk-utility test, a form of cost-benefit analysis that functions like the negligence standard of reasonable care. Relying on these cases, the Restatement (Third) of Torts: Products Liability embraced the risk-utility test, jettisoned the consumer expectations test, and characterized strict products liability as a misleading label that perpetuates confusion about liability being strict when it instead is based on negligence. In response, a clear majority of courts have rejected this negligence-based framework and affirmed the continued vitality of strict products liability. Puzzled by this unexpected development, mainstream scholars claim that courts are confused by the rhetoric of strict products liability. The prevailing scholarly opinion about this matter is confused; its fixation on negligence ignores the implied warranty rationale for strict products liability. Having been largely formulated as a rule of contract law, the implied warranty is under-theorized as a tort doctrine. Once adequately developed, the tort version of the implied warranty shows why courts have transformed the rule of strict products liability from the last century into a more comprehensive regime—“strict products liability 2.0”—that relies on consumer expectations to incorporate the risk-utility test into the framework of strict products liability. As compared to ordinary negligence liability, the implied warranty defines the safety problem in the normatively appropriate manner, thereby sharpening the inquiry about what’s at stake. In dismissing this important development, mainstream tort theory relies on legal categories that fundamentally differ from the ones courts have used to develop strict products liability with analogical reasoning. Scholars have either resorted to overly general theories of tort liability or have otherwise focused on narrow doctrinal questions. By not engaging in the mid-level categorical theorizing required by analogical reasoning, the mainstream position could not see how this characteristic form of judicial reasoning has created the substantively sound regime of strict products liability 2.0.

Car accidents in the age of robots

In this paper, we compare liability rules in a world where human-driven and fully-autonomous cars coexist. We develop a model where a manufacturer can invest to improve the safety of autonomous cars. Human drivers may decide to purchase a fully-autonomous car to save precaution costs to avoid road accidents and shift liability to the car manufacturer. As compared to the negligence rule, a strict liability regime on both human drivers and car manufacturers is proved to be a superior policy. In particular, strict liability leads to more efficient R&D investments to enhance the benefits of the technology and favors the adoption of fully-autonomous cars. We also recommend that users of fully-autonomous cars make a technology-dependent payment to a third-party if there is an accident to discipline their activity levels.

AI Strict Liability Vis-À-Vis AI Monopolization

Some argue that applying a strict liability regime on AI-inflicted damages may allow well-financed big AI companies to monopolize the industry. They hypothesize that a strict liability regime would expose AI companies to significant legal liability. Since small AI companies lack the necessary resources to pay for damages inflicted by their AI technology, a strict liability regime could erect barriers to entry for these small companies. Ultimately, the argument continues, such a regime would give a small group of companies a virtual monopoly on the AI industry. Thus, some conclude that strict liability inherently stifles innovation and should not be applied to emerging technologies, such as AI.
 This Article maintains that legislators should adopt a strict liability regime, and it rejects the above argument for two reasons. First, there is no substantial connection between a strict liability regime and the AI monopolization that is already underway. Second, insurance policies could mitigate the effects a strict liability regime may have on the capabilities of small AI companies to enter and compete in this important market. Therefore, the ongoing process of monopolization of the AI market should not by itself render strict liability a non-viable regime when AI-inflicted damages occur.

Liability for Artificial Intelligence: A Proposal of the European Parliament

Digital autonomous systems are characterized by their ability to make their “own” decisions, i.e. decisions that are not fully determined by the software that animates them. As such, they pose a challenge to existing liability systems and to the general law of delict or torts. At the European level, the European Parliament took the initiative and drafted a Regulation on Liability for the Operation of Artificial-Intelligence-Systems it recommended for adoption by the Commission. The European Parliament distinguishes between high-risk-AI-systems, that shall be governed by a regime of strict liability, and “other” AI-systems, that create only normal risks and are left to fault-based liability, as defined in the legal systems of the Member States. With a view to the addresses of the new liability scheme, the draft regulation distinguishes between frontend- and backend-operators. The following chapter discusses the fundamental choices which the framers of the draft made. It concludes that the focus of the proposal on user liability is misguided, as the manufacturers are the central actors who determine the safety features of AI-systems. Moreover, introducing the concept of a backend-operator creates needless friction with the Products Liability Directive. While the commitment to strict liability for high-risk-AI-systems draws a wedge into existing regimes of strict liability under national law, the imposition of fault-based liability on users of ordinary AI-systems forces some Member States to roll back more generous rules of tort law.

Pull yourself up by your bootstraps: Identifying procedural preferences against helping others in the presence of moral hazard

Governments and organizations often implement policies designed to help people in case of an undesirable event. Such policies can make the society better off, but they may also create moral hazard. We use a laboratory experiment to examine two questions. First, can discretionary decisions to provide assistance overcome the problem of moral hazard and lead to higher efficiency? Second, if so, will people prefer this discretionary procedure to the strict liability policy in which no assistance is provided? We find that the assistance is more ecient than the strict liability procedure. However, people still prefer the strict liability regime rather than assistance provision. We conduct additional treatments that show that this eect is not driven by the presence of the human discretion, nor by risk, loss or inequality aversion. This suggests that when moral hazard is a concern people have procedural preferences in favor of the strict liability regime.

COMPENSATION FOR DAMAGE CAUSED BY THE USE OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES AS A SPECIAL TORT

The article is raised the issue of compensation for damage caused by the use of artificial intelligence technologies. It is emphasized that the active use of advances in computer technology not only creates additional opportunities for humanity, but also creates new risks, including the danger of harm. Therefore, the purpose of the publication is to develop a theoretical model of compensation for damage caused by the use of artificial intelligence technologies as a special tort. Based on the analysis of international and native sources, different approaches to compensation for damage caused by the use of artificial intelligence technologies are considered. In particular, two regimes of civil liability for damage caused by artificial intelligence are investigated: strict liability regime and fault-based liability. The general regime of strict liability provides for the liability of the operator of artificial intelligence systems for damage caused by artificial intelligence, regardless of where the operation takes place and it happens physically or virtually. Instead, fault-based liability makes it possible for an operator to avoid liability for damage caused by the use of artificial intelligence if the artificial intelligence system has been activated without his knowledge, or if the operator has exercised due care in maintaining the artificial intelligence system. The division of responsibility between the operators and the victim is also mentioned. As a result, it is concluded that when the development of artificial intelligence systems reaches the level of absolute autonomy in decision-making and implementation, the issue of liability for damage caused by artificial intelligence should be reconsidered from the standpoint of establishing the legal status of "electronic person" and determining its legal personality.

AI Strict Liability Vis-à-Vis AI Monopolization

Some argue that applying a strict liability regime on AI-inflicted damages may lead to the monopolization of the AI industry. Strict liability is considered to be a regime that inherently stifles innovation given the costs it may inflict on companies. Therefore, the argument continues, it should not be applied on emerging technologies, such as AI. A strict liability regime can erect barriers to entry in the AI market in a way that will prevent small AI companies from competing. This is because these small companies lack the necessary resources to pay for damages inflected by their AI technology, leaving the industry to be monopolized by well-financed big AI companies. This Article rejects this argument and the implied correlation between an AI strict liability regime and the monopolization of the AI market. It does so for two reasons. First, there is no substantial connection between a strict liability regime and AI monopolization that is already underway. Second, insurance policies are available to mitigate the effects a strict liability regime may have on the capabilities of small AI companies to enter and compete in this important market. Therefore, the ongoing process of monopolization of the AI market should not render strict liability as a non-viable regime when AI-inflicted damages occur.

Artificial Intelligence, LLC: Corporate Personhood for AI

Our legal system has long tried to fit the square peg of artificial intelligence (AI) technologies into the round hole of the current tort regime, overlooking the inability of traditional liability schemes to address the nuances of how AI technology creates harms. The current tort regime deals out rough justice—using strict liability for some AI products and using the negligence rule for other AI services—both of which are insufficiently tailored to achieve public policy objectives. Under a strict liability regime where manufacturers are always held liable for the faults of their technology regardless of knowledge or precautionary measures, firms are incentivized to play it safe and stifle innovation. But even with this cautionary stance, the goals of strict liability cannot be met due to the unique nature of AI technology: its mistakes are merely “efficient errors”—they appropriately surpass the human baseline, they are game theory problems intended for a jury, they are necessary to train a robust system, or they are harmless but misclassified. Under a negligence liability regime where the onus falls entirely on consumers to prove the element of causation, victimized consumers must surmount the difficult hurdle of tracing the vectors of causation through the “black box” of algorithms. Unable to do so, many are left without sufficient recourse or compensation. This Article proposes a new framework to regulate AI technologies: bestowing corporate personhood to AI systems. First, the corporate personality trait of “limited liability” strikes an optimal balance in determining liability—it would both compensate victims (for instance, through obligations to carry insurance and a straightforward burden of causation) while holding manufacturers responsible only when the infraction is egregious (for instance, through veil-piercing). Second, corporate personhood is “divisible”—meaning not all corporate personality traits need to be granted—which circumvents many of the philosophical criticisms of giving AI the complete set of rights of full legal personhood. Third, innovation incentives weigh heavily in favor of shifting to a tort regime better tailored to the potential promises and unique harms of AI.