Relevant bibliographies by topics / Criminal liability of artificial intelligence

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
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Academic literature on the topic 'Criminal liability of artificial intelligence'

Author: Grafiati
Published: 4 June 2021
Last updated: 7 February 2022

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Journal articles on the topic "Criminal liability of artificial intelligence"

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Seongjo Ahn. "Artificial Intelligence and Criminal Liability." Korean Journal of Legal Philosophy 20, no. 2 (August 2017): 77–122. http://dx.doi.org/10.22286/kjlp.2017.20.2.003.

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Kirpichnikov, Danila, Albert Pavlyuk, Yulia Grebneva, and Hilary Okagbue. "Criminal Liability of the Artificial Intelligence." E3S Web of Conferences 159 (2020): 04025. http://dx.doi.org/10.1051/e3sconf/202015904025.

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Today, artificial intelligence (hereinafter – AI) becomes an integral part of almost all branches of science. The ability of AI to self-learning and self-development are properties that allow this new formation to compete with the human intelligence and perform actions that put it on a par with humans. In this regard, the author aims to determine whether it is possible to apply criminal liability to AI, since the latter is likely to be recognized as a subject of legal relations in the future. Based on a number of examinations and practical examples, the author makes the following conclusion: AI is fundamentally capable of being criminally liable; in addition, it is capable of correcting its own behavior under the influence of coercive measures.
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Радутний, Олександр Едуардович. "Criminal liability of the artificial intelligence." Problems of Legality, no. 138 (September 27, 2017): 132–41. http://dx.doi.org/10.21564/2414-990x.138.105661.

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황만성. "A Study about Criminal Liability of Artificial Intelligence." 법과정책 24, no. 1 (March 2018): 361–84. http://dx.doi.org/10.36727/jjlpr.24.1.201803.012.

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Khisamova, Zarina, and Ildar Begishev. "Criminal Liability and Artificial Intelligence: Theoretical and Applied Aspects." Russian Journal of Criminology 13, no. 4 (August 23, 2019): 564–74. http://dx.doi.org/10.17150/2500-4255.2019.13(4).564-574.

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The humanity is now at the threshold of a new era when a widening use of artificial intelligence (AI) will start a new industrial revolution. Its use inevitably leads to the problem of ethical choice, it gives rise to new legal issues that require urgent actions. The authors analyze the criminal law assessment of the actions of AI. Primarily, the still open issue of liability for the actions of AI that is capable of self-learning and makes a decision to act / not to act, which is qualified as a crime. As a result, there is a necessity to form a system of criminal law measures of counteracting crimes committed with the use of AI. It is shown that the application of AI could lead to four scenarios requiring criminal law regulation. It is stressed that there is a need for a clear, strict and effective definition of the ethical boundaries in the design, development, production, use and modification of AI. The authors argue that it should be recognized as a source of high risk. They specifically state that although the Criminal Code of the Russian Fe­deration contains norms that determine liability for cybercrimes, it does not eliminate the possibility of prosecution for infringements committed with the use of AI under the general norms of punishment for various crimes. The authors also consider it possible to establish a system to standardize and certify the activities of designing AI and putting it into operation. Meanwhile, an autonomous AI that is capable of self-learning is considerably different from other phenomena and objects, and the situation with the liability of AI which independently decides to undertake an action qualified as a crime is much more complicated. The authors analyze the resolution of the European Parliament on the possibility of granting AI legal status and discuss its key principles and meaning. They pay special attention to the issue of recognizing AI as a legal personality. It is suggested that a legal fiction should be used as a technique, when a special legal personality of AI can be perceived as an unusual legal situation that is different from reality. It is believed that such a solution can eliminate a number of existing legal limitations which prevent active involvement of AI into the legal space.
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Rahman, Rofi Aulia, and Rizki Habibulah. "THE CRIMINAL LIABILITY OF ARTIFICIAL INTELLIGENCE: IS IT PLAUSIBLE TO HITHERTO INDONESIAN CRIMINAL SYSTEM?" Legality : Jurnal Ilmiah Hukum 27, no. 2 (November 6, 2019): 147. http://dx.doi.org/10.22219/jihl.v27i2.10153.

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The pace of technology evolution is very fast. The technology has brought us to the limitless world and becoming our ally in every daily life. The technology has created a visionary autonomous agent that could surpass human capability with little or without human intervention, called by Artificial Intelligence (AI). In the implementation of AI in every area that could be in industrial, health, agriculture, artist, etc. Consequently, AI can damage individual or congregation life that is protected by criminal law. In the current Indonesian criminal system, it just acknowledges natural person and legal person (recht persoon) as the subject of law that can be imposed by criminal sanction. Hitherto and near foreseeable future AI has a notable role in every aspect, which affects also criminal aspects due to the damage resulted. AI has no sufficient legal status to be explained in the Indonesian criminal system. In this paper, the author will assess whether the current criminal system of Indonesia can sue the criminal liability of artificial intelligence, and also will make it clear to whom the possibility of criminal liability of artificial intelligence shall be charged.
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Shestak, Victor, and Aleksander Volevodz. "Modern Requirements of the Legal Support of Artificial Intelligence: a View from Russia." Russian Journal of Criminology 13, no. 2 (April 26, 2019): 197–206. http://dx.doi.org/10.17150/2500-4255.2019.13(2).197-206.

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At the present stage of the society’s development the artificial intelligence is quickly widening its possibilities. These changes raise the issue of applying norms, including international law norms, to solve problems connected with the essence and technical protocol of using artificial intelligence. The article is devoted to the problems of legal regulation of the creation and use of artificial intelligence and the development of the conceptual framework and the definition of artificial intelligence according to the widely recognized scientific theories; the analysis of doctrinal approaches to the understanding of the place of artificial intelligence in legal relations; the evidence that giving artificial intelligence the status of a person is not legally grounded; the critical analysis of the ideas put forward by some American researchers that artificial intelligence should comply with the whole set of laws currently used for its human producer and operator. The authors study the legislation on the legal regulation of relations between the human and artificial intelligence in such countries as the Republic of Korea, the USA, Japan, the People’s Republic of China, the Republic of Estonia, the Federal Republic of Germany and the Russian Federation, as well as the European Union. They present various approaches to the classification of artificial intelligence’s features. The authors also examine the problem of defining the legal personality of an «electronic person»; analyze the necessity of making the owner liable for the compensation of moral and material damage inflicted by the «electronic person». The article also discusses key problems of enforcing the legal norms regulating intellectual property and copyright, criminal liability and participation in criminal proceedings within the framework of using artificial intelligence. The authors analyze key risks and uncertainties connected with artificial intelligence and crucial for improving relevant legislation. They work out suggestions for the future discussion of the following issues: the applications of artificial intelligence at the contemporary stage; development prospects in this sector; legally relevant problems researched of this sphere and the problems connected with the use of the existing and the development of new autonomous intelligence systems; the development of new strategies and legal norms to bridge the gaps in the legal regulation of using artificial intelligence, including using it as a participant in criminal proceedings; creation of the concept of liability in the sphere of using artificial intelligence, including the criminal one.
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Louis, Mark, Angelina Anne Fernandez, Nazura Abdul Manap, Shamini Kandasamy, and Sin Yee Lee. "ARTIFICIAL INTELLIGENCE: IS IT A THREAT OR AN OPPORTUNITY BASED ON ITS LEGAL PERSONALITY AND CRIMINAL LIABILITY?" Journal of Information System and Technology Management 6, no. 20 (March 1, 2021): 01–09. http://dx.doi.org/10.35631//jistm.620001.

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Information technology is taking the world by storm. The technological world is changing rapidly and drastically. Human activities are taken over by robots and computers. The usage of computers and robots has increased productivity in various sectors. The emergence of artificial intelligence has stirred up many debates on both its importance and limitations. Artificial intelligence is directed to the usage of Information Technology in conducting tasks that normally require human intelligence. The expectation of artificial intelligence is high, nevertheless, artificial intelligence has its shortcomings namely the impact of artificial intelligence on the concept of a legal personality. The problem with artificial Intelligence is the debate on whether does it have a legal personality? And another problem is under what situation does the law treat artificial intelligence as an entity with its own rights and obligations. The objective of this article is to examine the various definitions of legal personality and whether artificial intelligence can become a legal person. The article will also examine the criminal liability of artificial intelligence when a crime has been committed. The methodology adopted is qualitative namely Doctrinal Legal Research by analyzing the relevant legal views from various journals on artificial intelligence. The study found out that artificial intelligence has its limitations in defining its legal personality and also in examining the criminal liability when a crime has been committed by robots.
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Kamalova, G. G. "SOME QUESTIONS OF CRIMINAL LEGAL RESPONSIBILITY IN THE FIELD OF APPLICATION OF ARTIFICIAL INTELLIGENCE SYSTEMS AND ROBOTICS." Bulletin of Udmurt University. Series Economics and Law 30, no. 3 (June 26, 2020): 382–88. http://dx.doi.org/10.35634/2412-9593-2020-30-3-382-388.

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The article discusses the problems of improving criminal law in the context of the development of one of the types of breakthrough digital technologies - artificial intelligence. The author notes that the explosive development in this area has led to the growth of high-tech crime, a special place among which is occupied by crimes using tools of artificial intelligence technology. Since the subjects of criminal activity traditionally use advanced technologies, at present such crimes are already represented by fraud, computer information crimes, terrorism, violations in the field of road safety, violation of the right to privacy and a number of others. Although there are no special offenses related to artificial intelligence in the criminal law today, this does not mean that existing norms cannot be applied to traditional subjects. Given the current level of development of artificial intelligence technology, it is now necessary to strengthen criminal liability for the compositions provided for by the current Criminal Code of the Russian Federation by introducing an appropriate qualifying attribute. With the recognition of the legal personality of artificial intelligence systems and robots, one of the key issues of applying criminal law rules to them will be the question of the subjective side of the committed act. The lack of “strong” artificial intelligence and the current level of development of solutions and devices based on artificial technology allow us to limit ourselves to classifying the facts of their use as components of the objective side of the crime.
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Chernyh, Evgeniya. "Artificial intelligence in the Russian healthcare sector: current situation and criminal and legal risks." Vestnik of the St. Petersburg University of the Ministry of Internal Affairs of Russia 2020, no. 4 (December 11, 2020): 127–31. http://dx.doi.org/10.35750/2071-8284-2020-4-127-131.

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The article discusses the prospects for the development of artificial intelligence systems in healthcare in Russia in the context of the introduction of the digital economy. A brief historical analysis of the use of artificial intelligence in the social sphere is carried out, the main directions of the modern Russianstate concept of the development of artificial intelligence are investigated. The main directions of using intelligent systems are revealed. The author emphasizes the need for legal regulation of digital medicine and, in this regard, analyzes the main criminal legal risks of causing harm to law-protected interests by one of the areas of digital medicine. It is noted that the criminal law problem of the use of artificial intelligence remains to date not developed in Russian criminal law, in this regard, the author emphasizes the urgent need for a more rapid development of criminal law rules governing legal relations in this area of activity. At the same time, the conditionality of the existence of a norm on criminal liability directly depends on the nature and degree of social danger of the act. The author of a brief analysis of foreign experience in the legal regulation of the use of artificial intelligence in the medical field. In the final part of the article, the author proposes qualification options in determining the subject composition causing harm.
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Dissertations / Theses on the topic "Criminal liability of artificial intelligence"

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Wang, Gang, Hsinchun Chen, and Homa Atabakhsh. "Automaticially Detecting Deceptive Criminal Identities." ACM, 2004. http://hdl.handle.net/10150/106000.

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Artificial Intelligence Lab, Department of MIS, Univeristy of Arizona
Fear about identity verification reached new heights since the terrorist attacks on Sept. 11, 2001, with national security issues related to detecting identity deception attracting more interest than ever before. Identity deception is an intentional falsification of identity in order to deter investigations. Conventional investigation methods run into difficulty when dealing with criminals who use deceptive or fraudulent identities, as the FBI discovered when trying to determine the true identities of 19 hijackers involved in the attacks. Besides its use in post-event investigation, the ability to validate identity can also be used as a tool to prevent future tragedies. Here, we focus on uncovering patterns of criminal identity deception based on actual criminal records and suggest an algorithmic approach to revealing deceptive identities.
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Xu, Jennifer J., and Hsinchun Chen. "Fighting organized crimes: using shortest-path algorithms to identify associations in criminal networks." Elsevier, 2004. http://hdl.handle.net/10150/106207.

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Artificial Intelligence Lab, Department of MIS, University of Arizona
Effective and efficient link analysis techniques are needed to help law enforcement and intelligence agencies fight organized crimes such as narcotics violation, terrorism, and kidnapping. In this paper, we propose a link analysis technique that uses shortest-path algorithms, priority-first-search (PFS) and two-tree PFS, to identify the strongest association paths between entities in a criminal network. To evaluate effectiveness, we compared the PFS algorithms with crime investigatorsâ typical association-search approach, as represented by a modified breadth-first-search (BFS). Our domain expert considered the association paths identified by PFS algorithms to be useful about 70% of the time, whereas the modified BFS algorithmâ s precision rates were only 30% for a kidnapping network and 16.7% for a narcotics network. Efficiency of the two-tree PFS was better for a small, dense kidnapping network, and the PFS was better for the large, sparse narcotics network.
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Claussén, Karlsson Matilda. "Artificial Intelligence and the External Element of the Crime : An Analysis of the Liability Problem." Thesis, Örebro universitet, Institutionen för juridik, psykologi och socialt arbete, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-58269.

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Sharma, Agni. "Assigning Liability in an Autonomous World." Scholarship @ Claremont, 2017. http://scholarship.claremont.edu/cmc_theses/1531.

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Liability laws currently in use rely on a fault-based system that focuses on a causal connection between driver actions and the resulting road accident. The role of the driver is set to reduce with the emergence of autonomous vehicles, so how will liability adapt to meet the needs of an autonomous world? The paper discusses possible frameworks of liability that could be implemented in the future, and accentuates the importance of the causal aspects of the current framework in the new system.
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Merege, Fernando. "Identificação de padrões de criminosos seriais usando inteligência artificial associada a neurônios espelhos." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/3/3142/tde-21052015-164058/.

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Os criminosos seriais que atuam no cometimento do crime de furto possuem modos de operação (Modus operandi) distintos e, que podem ser identificados através da análise dos exames periciais utilizando-se redes neurais. No sistema proposto, identificado um determinado modo de operação, um analista forense utilizando as informações adicionais coletadas e as hipóteses geradas pelos peritos de campo tem a competência de definir conjuntos de ações periciais complementares, que serão adicionados aos registros do modo identificado. Durante um novo exame pericial, em tempo real, a sub-rotina auxiliar analisa os blocos de dados enviados pelos peritos criminais de campo e, em caso de similaridade com um modo de operação anteriormente identificado, envia a eles um conjunto de ações complementares que, a critério do responsável em campo, pode ou não ser usado para alterar o procedimento de campo escolhido. Neste trabalho definimos Neurônios Espelho como sendo a associação das redes neurais para a identificação de padrões com a planilha de trabalho, utilizada pelo analista forense para a definição de ações complementares, com a sub-rotina auxiliar que verifica os blocos de informação recebidos e, que pode identificar partes de um modo de operação, remetendo para os peritos de campo um conjunto de ações complementares. Esta definição deve-se a descoberta pela neurobiologia de um tipo especifico de neurônio que tem a capacidade de disparar ao receber um input sensorial ativando uma área de memória que, em consequência, pode ativar outras áreas de memória ou enviar um comando motor. Neste trabalho foram desenvolvidos os programas de rede neural utilizados para a identificação dos modos de operação parcial e o final, além, das planilhas de trabalho para a elaboração das ações complementares e a sub-rotina auxiliar para identificação em tempo real dos modos de operação parciais. O treinamento da rede foi efetuado com 98 ocorrências e na verificação de validade foram utilizados 10 ocorrências.
The serial criminals who operate in the commission of the crime of theft have different modes of operation (modus operandi) and which may be identified through the analysis of forensic examinations using neural networks. In the proposed system, identified a particular mode of operation, a forensic analyst using the information collected and the hypotheses generated by field experts have the competence to define sets of complementary expert shares, which will be added to the records so identified. During a new forensic examination, in real time, the auxiliary subroutine examines data blocks sent by forensic experts in the field and, in the case of similarity to previously identified a mode of operation, sends them a complementary set of actions that the discretion of the responsible in the field, or can not be used to change the procedure chosen field. In this paper we define Mirror Neurons as the association of neural networks to identify patterns with the worksheet, used by forensic analyst for the definition of complementary actions, with the auxiliary subroutine that checks the blocks of information received and that can identify parts of a mode of operation, referring to field experts a set of complementary actions. This definition should be discovered by the neurobiology of a specific type of neuron that has the ability to shoot while receiving a sensory \"input\" activating an area of memory that, in consequence, can activate other areas of memory or send a motor command. This work programs of neural network used for identifying the modes of operation and the final part were developed, in addition, the worksheets for the elaboration of complementary actions and the auxiliary subroutine for real-time identification of the modes of partial operation. Network training was performed with 98 occurrences and validity check 10 events were used.
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Haviland, Hannah. ""The Machine Made Me Do It!" : An Exploration of Ascribing Agency and Responsibility to Decision Support Systems." Thesis, Linköping University, Centre for Applied Ethics, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2922.

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Are agency and responsibility solely ascribable to humans? The advent of artificial intelligence (AI), including the development of so-called “affective computing,” appears to be chipping away at the traditional building blocks of moral agency and responsibility. Spurred by the realization that fully autonomous, self-aware, even rational and emotionally-intelligent computer systems may emerge in the future, professionals in engineering and computer science have historically been the most vocal to warn of the ways in which such systems may alter our understanding of computer ethics. Despite the increasing attention of many philosophers and ethicists to the development of AI, there continues to exist a fair amount of conceptual muddiness on the conditions for assigning agency and responsibility to such systems, from both an ethical and a legal perspective. Moral and legal philosophies may overlap to a high degree, but are neither interchangeable nor identical. This paper attempts to clarify the actual and hypothetical ethical and legal situations governing a very particular type of advanced, or “intelligent,” computer system: medical decision support systems (MDSS) that feature AI in their system design. While it is well-recognized that MDSS can be categorized by type and function, further categorization of their mediating effects on users and patients is needed in order to even begin ascribing some level of moral or legal responsibility. I conclude that various doctrines of Anglo legal systems appear to allow for the possibility of assigning specific types of agency – and thus specific types of legal responsibility – to some types of MDSS. Strong arguments for assigning moral agency and responsibility are still lacking, however.

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Racek, Libor. "Trestní odpovědnost umělé inteligence." Master's thesis, 2020. http://www.nusl.cz/ntk/nusl-411530.

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1 Criminal liability of artificial intellingence Abstract The aim of this diploma thesis is to evaluate the possible criminal liability of artificial intelligence for its socially harmful unlawful conduct and if artificial intelligence cannot be criminal liable then evaluate criminal liability of persons for the unlawful acts of artificial intelligence, and also to assess whether it is necessary to change laws so that we can use in such situations the ultima ratio principle (criminal law). The first chapter deals with the concept of artificial intelligence. At the beginning of this chapter I deal with the definition of artificial intelligence from a technical point of view and I also deal with the most important points of its historical development. Then I analyze artificial intelligence from the perspective of the Czech legal order. First, I do so in connection with private law (specifically with civil law, respectively mainly with copyright) and then with public law (specifically with criminal law). The second chapter aims to introduce the concept of criminal liability as an institute of Czech law. I focus here on the individual components of criminal liability and its legal requirements, but not in an exhaustive way, but only to the extent that it is necessary to fulfill the topic of the thesis and to...
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Chao, Shih-wei, and 趙士瑋. "Study of Artificial Intelligence Product Tort Liability: Focusing on Autonomous Vehicles." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/fug776.

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碩士
國立交通大學
科技法律研究所
107
When autonomous vehicles (AVs) eventually begin to fill our roads, we are sure to be sorely reminded, aside from their numerous benefits, of the risk they bring forth in the form of accidents. This thesis attempts to explore the identification, management and allocation of AV-related risks from a tort liability perspective. It is first discovered that current tort liability schemes fail to address AVs properly, not only due to the “responsibility gap” caused by the autonomy and unpredictability of modern artificial intelligence systems, but also since both driver liability and product liability regulations exhibit fatal flaws in accounting for the attributes of such a revolutionary technology. This thesis instead proposes a liability scheme catered towards AVs. First and foremost, AVs are divided into two categories, fully- and non-fully-autonomous, according to whether the role of “driver” is present within. Non-fully-autonomous AVs should follow the traditional automobile accident liability paradigm where the driver is primarily responsible for the injury. Fully-autonomous AVs, on the other hand, give rise to a more sophisticated resolution of accidents. Initially, the victim should be entitled to partial but immediate compensation from an AV-injury public fund. Then, in court, the victim should be allowed to make claims against the AV owner, lending from vicarious liability theory, and against the manufacturer in terms of strict liability. This thesis aspires to involve all stakeholders regarding AV safety and liability, with aim to safeguard unfortunate AV accident victims, and ultimately build confidence among the public towards a future including AVs.
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CHANG, CHAN, and 張湛. "The Civil Liability of Artificial Intelligence System Users—Focusing on Autonomous Vehicles." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/9cwbqk.

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碩士
國立中正大學
財經法律系研究所
107
Autonomous vehicles, one of the most crucial parts of artificial intelligence, will soon be mass-produced and commercialized. Especially when the concepts of drivers and driving no longer exist in level 4 and 5 autonomous vehicles, it raises an important issue about the imputation in a car accident. In U.S. Law, the liability in the car accident is transformed from autonomous vehicles users to manufacturers. Meanwhile, the concept of manufacturer enterprise responsibility is also proposed as a solution, in which the manufacturers share the liability of personal damage caused by the autonomous vehicles. In our country, we can use product liability enacted under article 7 of Consumer Protection Act to tackle the problem of liability in an accident. Furthermore, service liability in Consumer Protection Act, which the manufacturers should compensate consumers or the third parties when the transportation service they provide fails to meet the contemporary technical and professional standards with reasonably expected safety, can be used to deal with the problem as well. The author tries to examine Contract Law in our country with autonomous vehicle. First, autonomous vehicles will concern issues related to defect warranty and the liability of non-performance after they are commercialized. Among others, the establishment of accessory obligation and collateral obligation is prominent. Besides, the transportation service with autonomous vehicles are related to the contract of hire of work and carriage of passengers. The author tries to blaze a trail by observing the autonomous vehicles as quasi-entities to deal with the humanlike characteristic of artificial intelligence, and hope to construct a more rigorous legal system.
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Urban, Martin. "Umělá inteligence a odpovědnost za její jednání." Master's thesis, 2018. http://www.nusl.cz/ntk/nusl-388942.

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Thesis title: Artificial intelligence and liability for its actions The artificial intelligence has recently become a ubiquitous phenomenon with a potential to change the world as we know it. Therefore, this thesis is concerned with the topic of artificial intelligence, specifically with a connection to a civil-law liability for its actions. It is absolutely clear that there will be more and more events in the future where damage will occur due to actions of artificial intelligence. Thus, the primary goal of this thesis is the determination of the person liable for damage caused in such cases under Czech law. Further goals of this thesis are an analysis of the question how is the dawn of autonomous cars influencing the legal instrument of liability for the damage caused by the operation of a means of transport as well as an introduction and examination of a recent resolution of the European Parliament which is supposed to serve as a basis for a future legal framework addressing the artificial intelligence in the area of the European Union. First, the paper focuses on the definition of the term artificial intelligence from a technical and legal viewpoint. This analysis shows that the definition of this term is not a straightforward one from neither of these viewpoints which can have serious...
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Books on the topic "Criminal liability of artificial intelligence"

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Hallevy, Gabriel. Liability for Crimes Involving Artificial Intelligence Systems. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-10124-8.

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Quattrocolo, Serena. Artificial Intelligence, Computational Modelling and Criminal Proceedings. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-52470-8.

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service), SpringerLink (Online, ed. Criminal Justice Forecasts of Risk: A Machine Learning Approach. New York, NY: Springer New York, 2012.

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Castella, Eduardo Marcelo. Investigação criminal e informática: Inteligência artificial x boletim de ocorrência (BO), soluções em KMAI. Curitiba: Juruá Editora, 2005.

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Procedure, Judicial Conference of the United States Committee on Rules of Practice and. Preliminary draft of proposed amendments to the Federal rules of criminal procedure. Wilmette, Ill. (3201 Old Glenview Rd., Wilmette 60091): Callaghan, 1986.

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The presence: A novel. Dallas, Tex: Novel Instincts, 2010.

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Montano, Pedro J. La responsabilidad penal de médicos y científicos ante las nuevas tecnologías de la procreación: Con especial referencia a las recomendaciones europeas y al Pacto de San José de Costa Rica. Montevideo: A.M. Fernández, 1991.

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Nissan, Ephraim. Computer Applications for Handling Legal Evidence, Police Investigation and Case Argumentation. Dordrecht: Springer Netherlands, 2012.

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Pagallo, Ugo. The Laws of Robots: Crimes, Contracts, and Torts. Dordrecht: Springer Netherlands, 2013.

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Subrahmanian, V. S. Handbook of Computational Approaches to Counterterrorism. New York, NY: Springer New York, 2013.

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Book chapters on the topic "Criminal liability of artificial intelligence"

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Hallevy, Gabriel. "Basic Requirements of Modern Criminal Liability." In Liability for Crimes Involving Artificial Intelligence Systems, 29–45. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10124-8_2.

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Muftic’, Nasir. "Liability for artificial intelligence." In Digital Technologies and the Law of Obligations, 95–118. London: Routledge, 2021. http://dx.doi.org/10.4324/9781003080596-7.

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Kingston, J. K. C. "Artificial Intelligence and Legal Liability." In Research and Development in Intelligent Systems XXXIII, 269–79. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47175-4_20.

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Hallevy, Gabriel. "Punishibility of Artificial Intelligence Technology." In Liability for Crimes Involving Artificial Intelligence Systems, 185–227. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10124-8_6.

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Hallevy, Gabriel. "External Element Involving Artificial Intelligence Systems." In Liability for Crimes Involving Artificial Intelligence Systems, 47–66. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10124-8_3.

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Baker, Dennis J., and Paul H. Robinson. "Emerging technologies and the criminal law." In Artificial Intelligence and the Law, 1–30. Milton Park, Abingdon, Oxon ; New York, NY : Routledge, 2021.: Routledge, 2020. http://dx.doi.org/10.4324/9780429344015-1.

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Schild, Uri J. "Criminal Sentencing and Intelligent Decision Support." In Judicial Applications of Artificial Intelligence, 47–98. Dordrecht: Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-015-9010-5_3.

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Hallevy, Gabriel. "Artificial Intelligence Technology and Modern Technological Delinquency." In Liability for Crimes Involving Artificial Intelligence Systems, 1–28. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10124-8_1.

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Hallevy, Gabriel. "Positive Fault Element Involving Artificial Intelligence Systems." In Liability for Crimes Involving Artificial Intelligence Systems, 67–146. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10124-8_4.

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Hallevy, Gabriel. "Negative Fault Elements and Artificial Intelligence Systems." In Liability for Crimes Involving Artificial Intelligence Systems, 147–84. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10124-8_5.

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Conference papers on the topic "Criminal liability of artificial intelligence"

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Borges, Georg. "AI systems and product liability." In ICAIL '21: Eighteenth International Conference for Artificial Intelligence and Law. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3462757.3466099.

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Maurushat, Alana, Lyria Bennett-Moses, and David Vaile. "Using 'big' metadata for criminal intelligence." In ICAIL '15: 15th International Conference on Artificial Intelligence and Law. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2746090.2746110.

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Thelisson, Eva. "Towards Trust, Transparency and Liability in AI / AS systems." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/767.

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Abstract:
The research problem being investigated in this article is how to develop governance mechanisms and collective decision-making processes at a global level for Artificial Intelligence systems (AI) and Autonomous systems (AS), which would enhance confidence in AI and AS.
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Wang, Xing, Yixin Sun, Xiaoliang Tang, Ji Chen, and Jiuxiang Jin. "Interchange of criminal rules between CLRL and LKIF." In ICMAI '18: 2018 International Conference on Mathematics and Artificial Intelligence. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3208788.3208802.

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Sushina, Tatyana, and Andrew Sobenin. "Artificial Intelligence in the Criminal Justice System: Leading Trends and Possibilities." In 6th International Conference on Social, economic, and academic leadership (ICSEAL-6-2019). Paris, France: Atlantis Press, 2020. http://dx.doi.org/10.2991/assehr.k.200526.062.

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Yuan, Danding. "Case Study of Criminal Law Based on Multi-task Learning." In 2020 International Conference on Artificial Intelligence and Computer Engineering (ICAICE). IEEE, 2020. http://dx.doi.org/10.1109/icaice51518.2020.00025.

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Li, Shang, Boyang Liu, Lin Ye, Hongli Zhang, and Binxing Fang. "Element-Aware Legal Judgment Prediction for Criminal Cases with Confusing Charges." In 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI). IEEE, 2019. http://dx.doi.org/10.1109/ictai.2019.00097.

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Krungklang, Weerayut, and Sukree Sinthupinyo. "An Analysis of Natural Language Text Relating to Thai Criminal Law." In 2020 12th International Conference on Electronics, Computers and Artificial Intelligence (ECAI). IEEE, 2020. http://dx.doi.org/10.1109/ecai50035.2020.9223143.

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Han, Jinbo, Dakui Li, Nanhai Yang, Zhu Liu, and Qiong Nan. "Analysis of Criminal Case Judgment Documents Based on Deep Learning." In 2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018). Paris, France: Atlantis Press, 2018. http://dx.doi.org/10.2991/acaai-18.2018.61.

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Kaya, Mustafa, Betul Ay Karakus, and Serkan Karakus. "Binary Classification of Criminal Tools from the Images of the Case Using CNN." In 2018 International Conference on Artificial Intelligence and Data Processing (IDAP). IEEE, 2018. http://dx.doi.org/10.1109/idap.2018.8620886.

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