This textbook presents an overview of the critically important ethical and legal issues that arise in the computing field and provides a professional perspective from software engineering. The author gained exposure to these aspects of computing while working as a software engineer at Motorola in Ireland, where he coordinated the patent programme and worked with several software suppliers. Topics and features: Presents a broad overview of ethics and the law Includes key learning topics, summaries, and review (...) questions in each chapter, together with a useful glossary Discusses the professional responsibility of computer professionals Explores ethics in various civilisations and religious traditions Discusses ethical software engineering and ethical outsourcing Considers what is fair and ethical in data science Describes ethical challenges that arise in social media and the AI field Reviews intellectual property including patents, copyright and trademarks This practical and easy-to-follow textbook/reference is ideal for computer science students seeking to understand legal and ethical aspects of computing. The text also serves as a concise self-study primer for software engineers and software managers. (shrink)

This book provides an overview of computer techniques and tools — especially from artificial intelligence (AI) — for handling legal evidence, police intelligence, crime analysis or detection, and forensic testing, with a sustained discussion of methods for the modelling of reasoning and forming an opinion about the evidence, methods for the modelling of argumentation, and computational approaches to dealing with legal, or any, narratives. By the 2000s, the modelling of reasoning on legal evidence has emerged as a (...) significant area within the well-established field of AI & Law. An overview such as this one has never been attempted before. It offers a panoramic view of topics, techniques and tools. It is more than a survey, as topic after topic, the reader can get a closer view of approaches and techniques. One aim is to introduce practitioners of AI to the modelling legal evidence. Another aim is to introduce legal professionals, as well as the more technically oriented among law enforcement professionals, or researchers in police science, to information technology resources from which their own respective field stands to benefit. Computer scientists must not blunder into design choices resulting in tools objectionable for legal professionals, so it is important to be aware of ongoing controversies. A survey is provided of argumentation tools or methods for reasoning about the evidence. Another class of tools considered here is intended to assist in organisational aspects of managing of the evidence. Moreover, tools appropriate for crime detection, intelligence, and investigation include tools based on link analysis and data mining. Concepts and techniques are introduced, along with case studies. So are areas in the forensic sciences. Special chapters are devoted to VIRTOPSY (a procedure for legal medicine) and FLINTS (a tool for the police). This is both an introductory book (possibly a textbook), and a reference for specialists from various quarters. (shrink)

In this paper, the results of a pilot interview study with 19 subjects participating in an EEG-based non-invasive brain–computer interface (BCI) research study on stroke rehabilitation and assistive technology and of a survey among 17 BCI professionals are presented and discussed in the light of ethical, legal, and social issues in research with human subjects. Most of the users were content with study participation and felt well informed. Negative aspects reported include the long and cumbersome preparation procedure, discomfort (...) with the cap and the wet electrodes, problems concerning BCI control, and strains during the training sessions. In addition, some users reflected on issues concerning system security. When asked for morally problematic issues in this field of non-invasive BCI research, the BCI professionals stressed the need for correct information transfer, the obligation to avoid unrealistic expectations in study participants, the selection of study participants, benefits and strains of participation, BCI illiteracy, the possibility of detrimental brain modifications induced by BCI use, and problems that may arise at the end of the trials. Furthermore, privacy issues were raised. Based on the results obtained, psychosocial and ethical aspects of EEG-based non-invasive BCI research are discussed and possible implications for future research addressed. (shrink)

The focus of this book is on the epistemological and hermeneutic implications of data science and artificial intelligence for democracy and the Rule of Law. How do the normative effects of automated decision systems or the interventions of robotic fellow 'beings' compare to the legal effect of written and unwritten law? To investigate these questions the book brings together two disciplinary perspectives rarely combined within the framework of one volume. One starts from the perspective of 'code and law' and (...) the other develops from the domain of 'law and literature'. Integrating original analyses of relevant novels or films, the authors discuss how computational technologies challenge traditional forms of legal thought and affect the regulation of human behavior. Thus, pertinent questions are raised about the theoretical assumptions underlying both scientific and legal practice. (shrink)

At the start of the twentieth century, the first quantum revolution upset our vision of the world. New physics offered surprising realities, such as wave-particle duality, and led to major inventions: the transistor, the laser, and computer's integrated circuits. Less known is the second quantum revolution, arguably initiated in 1935 during a debate between giants Albert Einstein and Niels Bohr. This revolution is still unfolding. Its revolutionaries--including the author of this short accessible book, Nobel Prize-winning physicist Alain Aspect--explore the notion (...) of entangled particles, able to interact at seemingly impossible distances. Aspect has investigated entangled particles since the beginning of the 1980s and has helped to show how entanglement may both upend existing technologies, like cryptography, and usher in entirely new ones, like quantum computing. Explaining this physics of the future, this work tells a story of how philosophical debates can shape new realities. (shrink)

Background The nursing profession requires ethical and legal regulations to guide nurses’ performance. Ethical climate plays a part in shaping nurses’ ethical practice. Therefore, ethico-legal aspects and ethical climate contribute to improving nurses’ ethical practice and competencies with reducing medical errors in hospital settings. Objective This study examined the effect of ethico-legal aspects and ethical climate on managing safe patient care and medical errors among nurses. Materials and methods A cross-sectional correlational study was carried out (...) on 548 nurses. Data were collected through self-administered questionnaires about nurses’ knowledge in both ethical and legal aspects, ethical practice, competencies, ethical climate and experience with medical error. Results The main sources of nurses’ knowledge of ethical and legal aspects were undergraduate lectures, job experience and colleagues. Nurses’ knowledge in both ethical and legal aspects, nurses’ ethical practice and competencies were insufficient. Nurses fairly perceived their ethical climate. Also, nurses experienced medical errors about 22.6% in their units. Nurses’ knowledge of ethical and legal aspects, as well as the ethical climate were positive predictors of inadequate nurses’ ethical practice and competencies. Additionally, nurses’ knowledge in both ethical and legal aspects, ethical climate and practice had a negative influence on the occurrence of medical errors. Conclusion Enhancing nurses’ knowledge in both ethical and legal aspects as well as ethical climate could significantly influence improving nurses’ ethical practice, competencies and reducing medical errors in the study units. Therefore, planning for enhancing the nurses’ ethico-legal learning and ethical climate seems to be mandatory. (shrink)

Privacy, Due process and the Computational Turn: The Philosophy of Law Meets the Philosophy of Technology engages with the rapidly developing computational aspects of our world including data mining, behavioural advertising, iGovernment, profiling for intelligence, customer relationship management, smart search engines, personalized news feeds, and so on in order to consider their implications for the assumptions on which our legal framework has been built. The contributions to this volume focus on the issue of privacy, which is often equated (...) with data privacy and data security, location privacy, anonymity, pseudonymity, unobservability, and unlinkability. Here, however, the extent to which predictive and other types of data analytics operate in ways that may or may not violate privacy is rigorously taken up, both technologically and legally, in order to open up new possibilities for considering, and contesting, how we are increasingly being correlated and categorizedin relationship with due process – the right to contest how the profiling systems are categorizing and deciding about us. (shrink)

We show that the fundamental legal structure of a well-written financial contract follows a state-transition logic that can be formalized mathematically as a finite-state machine (specifically, a deterministic finite automaton or DFA). The automaton defines the states that a financial relationship can be in, such as “default,” “delinquency,” “performing,” etc., and it defines an “alphabet” of events that can trigger state transitions, such as “payment arrives,” “due date passes,” etc. The core of a contract describes the rules by which (...) different sequences of events trigger particular sequences of state transitions in the relationship between the counterparties. By conceptualizing and representing the legal structure of a contract in this way, we expose it to a range of powerful tools and results from the theory of computation. These allow, for example, automated reasoning to determine whether a contract is internally coherent and whether it is complete relative to a particular event alphabet. We illustrate the process by representing a simple loan agreement as an automaton. (shrink)

Up to the present, there have not been any specific norms regarding medically assisted human reproduction in Romanian legislation. Due to this situation the general legislation regarding medical assistance, the Penal and Civil law and the provisions of the Code of Deontology of the Romanian College of Physicians are applied to the field of medically assisted human reproduction. By analysing the ethical and legal conflicts regarding medically assisted human reproduction in Romania, some characteristics cannot be set apart because they (...) derive from religious, cultural and socio-economic aspects. In this article the authors identify the development stages of medically assisted human reproduction in Romania, beginning from these characteristics and insisting upon the failure of the legal system in this specific field. The authors consider that the law regarding medically assisted human reproduction cannot be effective because it did not take into account the ethical and cultural aspects that might appear. Furthermore, in this framework of the legal process, no public debate involving the representatives of civil society was undertaken although the Council of Europe Oviedo Convention approved by our country according to law no. 17/2001 stipulated exactly this working method. Content Type Journal Article Pages 4-13 Authors Beatrice Ioan, PHD, MD, MA IN BIOETHICS, University of Medicine and Pharmacy, Iasi, Romania Vasile Astarastoae, PHD, MD, JD, University of Medicine and Pharmacy, Iasi, Romania Journal Human Reproduction & Genetic Ethics Online ISSN 2043-0469 Print ISSN 1028-7825 Journal Volume Volume 14 Journal Issue Volume 14, Number 2 / 2008. (shrink)

A brain-computer interface technology that can decode the neural signals associated with attempted but unarticulated speech could offer a future efficient means of communication for people with severe motor impairments. Recent demonstrations have validated this approach. Here we assume that it will be possible in future to decode imagined (i.e., attempted but unarticulated) speech in people with severe motor impairments, and we consider the characteristics that could maximize the social utility of a BCI for communication. As a social interaction, communication (...) involves the needs and goals of both speaker and listener, particularly in contexts that have significant potential consequences. We explore three high-consequence legal situations in which neurally-decoded speech could have implications:Testimony, where decoded speech is used as evidence;Consent and Capacity, where it may be used as a means of agency and participation such as consent to medical treatment; andHarm, where such communications may be networked or may cause harm to others. We then illustrate how design choices might impact the social and legal acceptability of these technologies. (shrink)

In this work we study, design, and evaluate computational methods to support interpretation of statutory terms. We propose a novel task of discovering sentences for argumentation about the meaning of statutory terms. The task models the analysis of past treatment of statutory terms, an exercise lawyers routinely perform using a combination of manual and computational approaches. We treat the discovery of sentences as a special case of ad hoc document retrieval. The specifics include retrieval of short texts, specialized document types, (...) and, above all, the unique definition of document relevance provided in detailed annotation guidelines. To support our experiments we assembled a data set comprising 42 queries which we plan to release to the public in the near future in order to support further research. Most importantly, we investigate the feasibility of developing a system that responds to a query with a list of sentences that mention the term in a way that is useful for understanding and elaborating its meaning. This is accomplished by a systematic assessment of different features that model the sentences’ usefulness for interpretation. We combine features into a compound measure that accounts for multiple aspects. The definition of the task, the assembly of the data set, and the detailed task analysis provide a solid foundation for employing a learning-to-rank approach. (shrink)

"Databases containing the accumulated genomic data of the research community are growing exponentially. This book contains cutting-edge insights from scholars, bioethicists and legal practitioners who work at the ever-changing intersection of law and bioinformatics"--Page 4 of cover.

Identification of rhetorical roles like facts, arguments, and final judgments is central to understanding a legal case document and can lend power to other downstream tasks like legal case summarization and judgment prediction. However, there are several challenges to this task. Legal documents are often unstructured and contain a specialized vocabulary, making it hard for conventional transformer models to understand them. Additionally, these documents run into several pages, which makes it difficult for neural models to capture the (...) entire context at once. Lastly, there is a dearth of annotated legal documents to train deep learning models. Previous state-of-the-art approaches for this task have focused on using neural models like BiLSTM-CRF or have explored different embedding techniques to achieve decent results. While such techniques have shown that better embedding can result in improved model performance, not many models have focused on utilizing attention for learning better embeddings in sentences of a document. Additionally, it has been recently shown that advanced techniques like multi-task learning can help the models learn better representations, thereby improving performance. In this paper, we combine these two aspects by proposing a novel family of multi-task learning-based models for rhetorical role labeling, named MARRO, that uses transformer-inspired multi-headed attention. Using label shift as an auxiliary task, we show that models from the MARRO family achieve state-of-the-art results on two labeled datasets for rhetorical role labeling, from the Indian and UK Supreme Courts. (shrink)

Following modernization paradigm and some local dynamics conducive to development, some Asian countries emerged as economic tigers in the world. Conversely, other Asian countries including Bangladesh failed to taste economic development despite having monetary and technological aids from some developed nations. Drawing on some social and historical trajectories of the divergent contours of Asian development/ underdevelopment, the paper examines the state of development in Bangladesh. The study has found that Japan is the first country in Asia to achieve modernization, and (...) it was followed by other Asian tigers such as Korea, Taiwan, Singapore, Malaysia and currently China and India. We found that all these Asian tigers exert a developmental model which is characterized by ‘endogenous’ modernity and economic nationalism largely driven by, among other things, long-term economic vision and strong political leadership. While the history of Bangladesh has witnessed various cultural nationalisms, the nation has failed to generate any unified economic nationalism since its independence in 1971. We suggest that Bangladesh needs a long-term development vision—a key thrust for economic nationalism—focusing more on some socioeconomic and legal aspects that have historically become major impediments for development. (shrink)

The genome of two completely unrelated individuals is quite similar apart from minor variations called single nucleotide polymorphisms which contribute to the uniqueness of each and every person. These single nucleotide polymorphisms are of great interest clinically as they are useful in figuring out the susceptibility of certain individuals to particular diseases and for recognizing varied responses to pharmacological interventions. This gives rise to the idea of ‘personalized medicine’ as an exciting new therapeutic science in this genomic era. Personalized medicine (...) suggests a unique treatment strategy based on an individual’s genetic make-up. Its key principles revolve around applied pharmaco-genomics, pharmaco-kinetics and pharmaco-proteomics. Herein, the ethical and legal aspects of personalized medicine in a new genomic era are briefly addressed. The ultimate goal is to comprehensively recognize all relevant forms of genetic variation in each individual and be able to interpret this information in a clinically meaningful manner within the ambit of ethical and legal considerations. The authors of this article firmly believe that personalized medicine has the potential to revolutionize the current landscape of medicine as it makes its way into clinical practice. (shrink)

Identifying, classifying, and analyzing arguments in legal discourse has been a prominent area of research since the inception of the argument mining field. However, there has been a major discrepancy between the way natural language processing (NLP) researchers model and annotate arguments in court decisions and the way legal experts understand and analyze legal argumentation. While computational approaches typically simplify arguments into generic premises and claims, arguments in legal research usually exhibit a rich typology that is (...) important for gaining insights into the particular case and applications of law in general. We address this problem and make several substantial contributions to move the field forward. First, we design a new annotation scheme for legal arguments in proceedings of the European Court of Human Rights (ECHR) that is deeply rooted in the theory and practice of legal argumentation research. Second, we compile and annotate a large corpus of 373 court decisions (2.3M tokens and 15k annotated argument spans). Finally, we train an argument mining model that outperforms state-of-the-art models in the legal NLP domain and provide a thorough expert-based evaluation. All datasets and source codes are available under open lincenses athttps://github.com/trusthlt/mining-legal-arguments. (shrink)

In the civil law tradition, legal arguments are used to justify the outcomes of judicial decision-making. These arguments are formed relying on a canon of interpretation techniques (e.g. textual or teleological interpretation). We study the identifiability of interpretation techniques as they are employed by the European Court of Human Rights (ECtHR) from a computational law perspective using a unique dataset. We show how Large Language Models (LLMs) can be utilized to classify legal interpretations, and we compare their performance. (...) We evaluate proprietary and opensource models using methods such as few-shot and zero-shot chain-of-thought prompting combined with self-consistency. Our results imply that feature-extraction using LLMs leads to robust outcomes while allowing for greater resource- and timeefficiency compared to human annotation. Furthermore, our results imply that LLMs can play a larger role in the extraction of more complex features that are of particular relevance from a legal perspective. (shrink)

From a psychological standpoint, communicating a severe diagnosis entails more than just naming a disease, it is a complex process with a number of stages: finding out what the patient already knows about the illness (some of which might be wrong, and thus psychologically detrimental), informing the patient while answering any questions (about the illness itself, the treatment, prognosis, recovery period, etc.) and last but not least, providing a minimum of psychological support depending on the patient’s reaction. Romanian law regarding (...) doctor-patient relationship and communication is modeled on the Anglo-Saxon model centered on patient autonomy and direct communication with the latter if the patient desires to know the truth about his condition. If this is not the case, the patient can name a proxy for doctor-patient communication. There are three legal documents that clarify these aspects: Law of Patient Rights, Medical Association’s Ethics Code and the Health Reform Law. The first two are conflicting on several aspects that we will discuss in this paper. The few studies on doctor-patient communication published in Romania reveal that there is no unitary methodology in this field. The doctors attest that often times the patient’s family, when faced with severe illness turn to the traditional model of communication, i.e. they desire to know the severe diagnosis first and pressure the physician to hide the truth form the patient, contrary to the letter of the law. The aim of this paper is to discuss the issue of communicating severe diagnosis in nowadays Romania in a very complex context: 1. The model of doctor-patient relationship and communication has changed after communist era (from paternalistic to partenerial); 2. Conflicting and missing issues in laws; 3. Laws based on patient’s autonomy principle in a traditional society based on another model of taking care (the patient is part of a family nucleus and the family wants to interfere into the medical communication process). Communication has only recently entered the curriculum of some medical schools in Romania. The doctors questioned as part of a study reveal that they‘ve learned to communicate a severe diagnosis by trial and error. This being said we recommend the inception of practical doctor-patient communication courses that could lead to improving doctor-patient relationships, communication of the diagnosis being their foundations. (shrink)

This book constitutes the thoroughly refereed post-proceedings of the Third International Conference on Logical Aspects of Computational Linguistics, LACL'98, held in Grenoble, France, in December 1998. The 15 revised full papers presented together with one invited paper were carefully reviewed and selected during two rounds of refereeing from 33 submissions and 19 conference presentations. Among the topics covered are various types of grammars, categorical inference, automated reasoning, constraint handling, logical forms, dialogue semantics, unification, and proofs.

Access to legal information is fundamental to access to justice. Yet accessibility refers not only to making legal documents available to the public, but also rendering legal information comprehensible to them. A vexing problem in bringing legal information to the public is how to turn formal legal documents such as legislation and judgments, which are often highly technical, to easily navigable and comprehensible knowledge to those without legal education. In this study, we formulate a (...) three-step approach for bringing legal knowledge to laypersons, tackling the issues of navigability and comprehensibility. First, we translate selected sections of the law into snippets (called CLIC-pages), each being a small piece of article that focuses on explaining certain technical legal concept in layperson’s terms. Second, we construct a _Legal Question Bank_, which is a collection of legal questions whose answers can be found in the CLIC-pages. Third, we design an interactive _CLIC Recommender_. Given a user’s verbal description of a legal situation that requires a legal solution, CRec interprets the user’s input and shortlists questions from the question bank that are most likely relevant to the given legal situation and recommends their corresponding CLIC pages where relevant legal knowledge can be found. In this paper we focus on the technical aspects of creating an LQB. We show how large-scale pre-trained language models, such as GPT-3, can be used to generate legal questions. We compare machine-generated questions against human-composed questions and find that MGQs are more scalable, cost-effective, and more diversified, while HCQs are more precise. We also show a prototype of CRec and illustrate through an example how our 3-step approach effectively brings relevant legal knowledge to the public. (shrink)

Natural language processing techniques contribute more and more in analyzing legal documents recently, which supports the implementation of laws and rules using computers. Previous approaches in representing a legal sentence often based on logical patterns that illustrate the relations between concepts in the sentence, often consist of multiple words. Those representations cause the lack of semantic information at the word level. In our work, we aim to tackle such shortcomings by representing legal texts in the form of (...) abstract meaning representation, a graph-based semantic representation that gains lots of polarity in NLP community recently. We present our study in AMR Parsing and AMR-to-text Generation specifically for legal domain. We also introduce JCivilCode, a human-annotated legal AMR dataset which was created and verified by a group of linguistic and legal experts. We conduct an empirical evaluation of various approaches in parsing and generating AMR on our own dataset and show the current challenges. Based on our observation, we propose our domain adaptation method applying in the training phase and decoding phase of a neural AMR-to-text generation model. Our method improves the quality of text generated from AMR graph compared to the baseline model. 2018; and “Legal Text Generation fromMeaning Representation”, published in the 32nd International Conference on Legal Knowledge and Information Systems 2019.). (shrink)

Over the last few decades there has been a substantially higher percentage of successful organ transplants but also a significant imbalance between the demand for and the supply of organs, creating the basis for a highly profitable black market trade in human organs. Sometimes there are reports that children have been kidnapped, only to reappear later lacking one kidney, or that they simply disappear and are subsequently killed to have all their transplantable organs removed for profit. The European Union feels (...) that there is a need for action and that it has a duty to act in this field, especially for ethical reasons. There is now established close co-operation between the various European transplant organizations. The legal protection of children with regard to organ transplantation is not specifically mentioned in the existing conventions because this issue was not foreseen at the time of their preparation. However, the issue is covered in a broader sense by more general provisions. There are endless rumours surrounding this area. Members of various organizations who travel in the suspected countries say that the trafficking in children who are sold for transplantation is well known, but it is too difficult and very dangerous to catch the people involved. We have to conclude that it has been impossible to prove or disprove the rumours, but they are consistent and we all, especially in the health care professions, have an obligation to be keenly aware of how and where organs are obtained. (shrink)

In the domain of legal information retrieval, an important challenge is to compute similarity between two legal documents. Precedents play an important role in The Common Law system, where lawyers need to frequently refer to relevant prior cases. Measuring document similarity is one of the most crucial aspects of any document retrieval system which decides the speed, scalability and accuracy of the system. Text-based and network-based methods for computing similarity among case reports have already been proposed (...) in prior works but not without a few pitfalls. Since legal citation networks are generally highly disconnected, network based metrics are not suited for them. Till date, only a few text-based and predominant embedding based methods have been employed, for instance, TF-IDF based approaches, Word2Vec and Doc2Vec based approaches. We investigate the performance of 56 different methodologies for computing textual similarity across court case statements when applied on a dataset of Indian Supreme Court Cases. Among the 56 different methods, thirty are adaptations of existing methods and twenty-six are our proposed methods. The methods studied include models such as BERT and Law2Vec. It is observed that the more traditional methods that rely on a bag-of-words representation performs better than the more advanced context-aware methods for computing document-level similarity. Finally we nominate, via empirical validation, five of our best performing methods as appropriate for measuring similarity between case reports. Among these five, two are adaptations of existing methods and the other three are our proposed methods. (shrink)

This much-needed book provides a thorough account of temporal logic, one of the most important areas of logic in computer science today. The book begins with a solid introduction to semantical and axiomatic approaches to temporal logic. It goes on to cover predicate temporal logic, meta-languages, general theories of axiomatization, many dimensional systems, propositional quantifiers, expressive power, Henkin dimension, temporalization of other logics, and decidability results. With its inclusion of cutting-edge results and unifying methodologies, this book is an indispensable reference (...) for both the pure logician and the theoretical computer scientist. (shrink)

In this short study, the Scroll of Ruth, and especially Ruth's undisclosed motives for following her mother-in-law, are read alongside the situation of foreign, female migrant workers in contemporary Israel—and vice versa. This allows a bi-directional reading that supplies a possible context both for the biblical text and for the evaluation of today's issues.

In this paper, we present a method for introducing law students to the writing of legal documents. The method uses a machine-readable representation of the legal knowledge to support document assembly and to help the students to understand how the assembly is performed. The knowledge base consists of enacted legislation, document templates, and assembly instructions. We propose a system called LEDAS (LEgal Document Assembly System) for the interactive assembly of legal documents. It guides users through the (...) assembly process and provides explanations of the interconnection between input data and claims stated in the document. The system acts as a platform for practicing drafting skills and has great potential as an education tool. It allows teachers to configure the system for the assembly of some particular type of legal document and then enables students to draft the documents by investigating which information is relevant for these documents and how the input data shape the final document. The generated legal document is complemented by a graphical representation of legal arguments expressed in the document. The system is based on existing legal standards to facilitate its introduction in the legal domain. Applicability of the system in the education of future lawyers is positively evaluated by the group of law students and their TA. (shrink)

Provides a comprehensive introduction to ethical frameworks and of many of the modern issues arising in technology ethics including computing, privacy, artificial intelligence, and more.

Named entity recognition (NER) is a very relevant task for text information retrieval in natural language processing (NLP) problems. Most recent state-of-the-art NER methods require humans to annotate and provide useful data for model training. However, using human power to identify, circumscribe and label entities manually can be very expensive in terms of time, money, and effort. This paper investigates the use of prompt-based language models (OpenAI’s GPT-3) and weak supervision in the legal domain. We apply both strategies as (...) alternative approaches to the traditional human-based annotation method, relying on computer power instead human effort for labeling, and subsequently compare model performance between computer and human-generated data. We also introduce combinations of all three mentioned methods (prompt-based, weak supervision, and human annotation), aiming to find ways to maintain high model efficiency and low annotation costs. We showed that, despite human labeling still maintaining better overall performance results, the alternative strategies and their combinations presented themselves as valid options, displaying positive results and similar model scores at lower costs. Final results demonstrate preservation of human-trained models scores averaging 74.0% for GPT-3, 95.6% for weak supervision, 90.7% for GPT + weak supervision combination, and 83.9% for GPT + 30% human-labeling combination. (shrink)

In this paper, we present an informal introduction to Logical English and illustrate its use to standardise the legal wording of the Automatic Early Termination clauses of International Swaps and Derivatives Association Agreements. LE can be viewed both as an alternative to conventional legal English for expressing legal documents, and as an alternative to conventional computer languages for automating legal documents. LE is a controlled natural language, which is designed both to be computer-executable and to be (...) readable by English speakers without special training. The basic form of LE is syntactic sugar for logic programs, in which all sentences have the same standard form, either as rules of the form conclusion if conditions or as unconditional sentences of the form conclusion. However, LE extends normal logic programming by introducing features that are present in other computer languages and other logics. These features include typed variables signalled by common nouns, and existentially quantified variables in the conclusions of sentences signalled by indefinite articles. Although LE translates naturally into a logic programming language such as Prolog or ASP, it can also serve as a neutral standard, which can be compiled into other lower-level computer languages. (shrink)

What principles explain or justify legal institutions or decisions, thereby transforming coercion to authority? Are there or could there be any such universal principles? Can any philosophical theory account for such principles? How, if at all, do philosophical theories of law and politics apply to particular issues? And finally, what, if any, do such practical applications tell us about general theories and principles? The essays in this volume represent the efforts of an international group of scholars to understand these (...) general aspects of legal philosophy. (shrink)

Biobanks represent an invaluable research tool and, as a result of their intrinsic and extrinsic nature, may be looked upon as archives or repositories largely made up of libraries, or collections of content where the content is the biological material derived from different individuals or species, representing valuable tangible assets. Biobanks analyses aspects of the commons and common intellectual property relating to the concepts of private property, not only concerning data but biological materials as well, and the advantages and (...) disadvantages of patents in scientific research. Several recent initiatives in biomedical research have attempted to make their data freely available to others, so as to foster innovation. Many of these initiatives have adopted the open source model, which has gained widespread recognition in the computer industry. This title is structured into eight chapters and begins with an introduction, which is followed by chapters that discuss how the term 'biobank' came about in scientific literature; legal matters relating to biobanks; and intellectual and physical property. Later chapters comprehensively analyse the intellectual property of biobanks within the sphere of copyright; biotechnological inventions and research patentability; open data sharing in biobanks; and biobanks as commons or vault. Considers biobanks as both repositories and as collections of tangible assets Argues that the data in biobanks represents a high value intangible asset Explores regulatory gaps exploited by the private sector. (shrink)

Ever since 1956 when details of the Logic Theorist were published by Newell and Simon, a large literature has accumulated on computational models and theories of the creative process, especially in science, invention and design. But what exactly do these computational models/theories tell us about the way that humans have actually conducted acts of creation in the past? What light has computation shed on our understanding of the creative process? Addressing these questions, we put forth three propositions: (I) Computational models (...) of the creative process are fundamentally flawed as theories of human creativity. Rather, the universal power of computational models lies elsewhere: (II) Computational models of particular acts of creation can serve as effective experiments to test universal hypotheses about creative processes and mechanisms; and (III) Computation-based architectures of the creative mind provide metaphorical frameworks that, like all good metaphors, can serve as rich sources of insight into aspects of the creative process. In this paper, we provide evidence for these three propositions by drawing upon some particular episodes in the cognitive history of science, technology, and art. (shrink)

The workshop will discuss new insights in the interaction between logic and law, and more precisely the study of different answers to the question: What role does logic play in legal reasoning? It will present both current challenges and historical perspectives in the relation between logic and law. The perspectives to be discussed involve the interface of the following studies.

The time of the economic crisis, the prolonged collisions between the opposition and the main branches of power, the permanent election process, and the general instability of society, characteristic to modern Ukraine, give birth to the state of emotional and psychological stress - from sorrow, despair, and a sense of hopelessness to complete eclecticism of public opinion and opposition, even within one family.

This article seeks to address the problem of the ‘resource consumption bottleneck’ of creating legal semantic technologies manually. It describes a semantic role labeling based information extraction system to extract definitions and norms from legislation and represent them as structured norms in legal ontologies. The output is intended to help make laws more accessible, understandable, and searchable in a legal document management system.

This study examines the interplay between text summarization techniques and embeddings from Language Models (LMs) in constructing expert systems dedicated to the retrieval of legal precedents, with an emphasis on achieving cost-efficiency. Grounded in the growing domain of Artificial Intelligence (AI) in law, our research confronts the perennial challenges of computational resource optimization and the reliability of precedent identification. Through Named Entity Recognition (NER) and part-of-speech (POS) tagging, we juxtapose various summarization methods to distill legal documents into a (...) convenient form that retains their essence. We investigate the effectiveness of these methods in conjunction with state-of-the-art embeddings based on Large Language Models (LLMs), particularly ADA from OpenAI, which is trained on a wide range of general-purpose texts. Utilizing a dataset from one of Brazil’s administrative courts, we explore the efficacy of embeddings derived from a Transformer model tailored to legal corpora against those from ADA, gauging the impact of parameter size, training corpora, and context window on retrieving legal precedents. Our findings suggest that while the full text embedded with ADA’s extensive context window leads in retrieval performance, a balanced combination of POS-derived summaries and ADA embeddings presents a compelling trade-off between performance and resource expenditure, advocating for an efficient, scalable, intelligent system suitable for broad legal applications. This study contributes to the literature by delineating an optimal approach that harmonizes the dual imperatives of computational frugality and retrieval accuracy, propelling the legal field toward more strategic AI utilization. (shrink)

ABSTRACTThis essay aims to contribute robust grounds to question the Susskinds’ influential, consequentialist logic when it comes to the legitimacy of automation within the legal profession. It does so by questioning their minimalist understanding of the professions. If it is our commitment to moral equality that is at stake every time lawyers hail the specific vulnerability inherent in their professional relationship, the case for wholesale automation is turned on its head. One can no longer assume that, as a rule, (...) wholesale automation is both legitimate and desirable, provided it improves the quality and accessibility of legal services. The assumption, instead, is firmly in favour of designing systems that better enable legal professionals to live up to their specific responsibility. The rest of the essay outlines key challenges in the design of such profession-specific, ‘ethics aware’ decision-support systems. (shrink)

Sentence boundary detection (SBD) represents an important first step in natural language processing since accurately identifying sentence boundaries significantly impacts downstream applications. Nevertheless, detecting sentence boundaries within legal texts poses a unique and challenging problem due to their distinct structural and linguistic features. Our approach utilizes deep learning models to leverage delimiter and surrounding context information as input, enabling precise detection of sentence boundaries in English legal texts. We evaluate various deep learning models, including domain-specific transformer models like (...) LegalBERT and CaseLawBERT. To assess the efficacy of our deep learning models, we compare them with a state-of-the-art domain-specific statistical conditional random field (CRF) model. After considering model size, F1-score, and inference time, we identify the Convolutional Neural Network Model (CNN) as the top-performing deep learning model. To further enhance performance, we integrate the features of the CNN model into the subsequent CRF model, creating a hybrid architecture that combines the strengths of both models. Our experiments demonstrate that the hybrid model outperforms the baseline model, achieving a 4% improvement in the F1-score. Additional experiments showcase the superiority of the hybrid model over SBD open-source libraries when confronted with an out-of-domain test set. These findings underscore the importance of efficient SBD in legal texts and emphasize the advantages of employing deep learning models and hybrid architectures to achieve optimal performance. (shrink)

Our research explores the application of Large Language Models for enhancing legal advice through AI-driven conversational agents, focusing on the analysis and interpretation of user-generated content from a prominent online legal community. By leveraging BERTopic for topic modeling and GPT-3.5 for labeling of user intents, we constructed a dataset that served as the foundation for fine-tuning the Mistral 7B language model. This process involved Supervised Fine Tuning and Direct Preference Optimization, culminating in the creation of a Domain Specific (...) Language Model for legal expertise. This model was then employed to guide GPT-3.5 responses, ensuring domain-specific relevance and contextual appropriateness. The evaluation of these responses was conducted using GPT-4, supplemented by human assessment, to gauge the quality of the models' outputs. We leverage an innovative end-to-end pipeline, building upon the framework proposed by Wang et al. (Empower large language model to perform better on industrial domain-specific question answering, 2023. arXiv:2305.11541), specifically adapted for the legal domain. This pipeline provides a foundational framework for developing sophisticated and scalable user-facing chatbots, presenting an alternative to the more common retrieval augmented generation techniques. Our contributions include providing datasets for further research on Legal Question Answering systems and advancements in human alignment of responses from chatbots. This research advances the technical frontier in AI-driven legal assistance and opens new avenues for enhancing the accessibility and quality of legal support through conversational AI technologies. (shrink)

Similar case analysis (SCA) is an essential topic in legal artificial intelligence, serving as a reference for legal professionals. Most existing works treat SCA as a traditional text classification task and ignore some important legal elements that affect the verdict and case similarity, like legal events, and thus are easily misled by semantic structure. To address this issue, we propose a Legal Event-Context Model named LECM to improve the accuracy and interpretability of SCA based on (...) Chinese legal corpus. The event-context integration mechanism, which is an essential component of the LECM, is proposed to integrate the legal event and context information based on the attention mechanism, enabling legal events to be associated with their corresponding relevant contexts. We introduce an event detection module to obtain the legal event information, which is pre-trained on a legal event detection dataset to avoid labeling events manually. We conduct extensive experiments on two SCA tasks, i.e., similar case matching (SCM) and similar case retrieval (SCR). Compared with baseline models, LECM is validated by about 13% and 11% average improvement in terms of mean average precision and accuracy respectively, for SCR and SCM tasks. These results indicate that LECM effectively utilizes event-context knowledge to enhance SCA performance and its potential application in various legal document analysis tasks. (shrink)

The interplay between computability and randomness has been an active area of research in recent years, reflected by ample funding in the USA, numerous workshops, and publications on the subject. The complexity and the randomness aspect of a set of natural numbers are closely related. Traditionally, computability theory is concerned with the complexity aspect. However, computability theoretic tools can also be used to introduce mathematical counterparts for the intuitive notion of randomness of a set. Recent research shows that, conversely, concepts (...) and methods originating from randomness enrich computability theory.The book covers topics such as lowness and highness properties, Kolmogorov complexity, betting strategies and higher computability. Both the basics and recent research results are desribed, providing a very readable introduction to the exciting interface of computability and randomness for graduates and researchers in computability theory, theoretical computer science, and measure theory. (shrink)

Intentionalism must be distinguished from computational psychology. The former is a mentalist-realist metatheoretical stance vis-a-vis the latter, which is a research programme devoted to the construction of informationally-characterized simulation models for human behavior, perception, cognition, etc. Intentionalism has its attractive aspects, but unfortunately it is plagued by severe conceptual difficulties. Recent attempts to justify the intentionalist interpretation of computational models, by J.A. Fodor and by C. Graves, J.J. Katz et al., fail to secure a conceptually adequate and genuinely intentional (...) sense for the intentional idiom they employ. (shrink)

This book explores the transformational impact of new technological developments on legal practice. More specifically, it addresses knowledge management, communication, and e-discovery related technologies, and helps readers develop the project management and data analysis skills needed to effectively navigate the current, and future, landscapes. It studies the impact of current trends on business practices, as well as the ethical, procedural, and evidentiary concerns involved. Introducing novel interactive technologies as well as traditional content, the book reflects expertise from across the (...) legal industry, including practitioners, the bench, academia, and legal technology consultants. All of the contributing authors currently teach aspiring lawyers and/or paralegals and have identified a gap in the available instructional material. Rapid technology advances have radically changed the way we all live and work, and the legal profession is by no means exempt from the impact of these changes. In order to better assist their clients, and to better compete on the legal market, it is imperative for lawyers to understand the ethical, functional, and business consequences of new technologies on their respective practices. This book provides the necessary content by including legal technology texts, information about novel pedagogical technologies, helpful tools for managing legal technologies and IT staff, statistical methods, tips and checklists. (shrink)

Transparency is now a fundamental principle for data processing under the General Data Protection Regulation. We explore what this requirement entails for artificial intelligence and automated decision-making systems. We address the topic of transparency in artificial intelligence by integrating legal, social, and ethical aspects. We first investigate the ratio legis of the transparency requirement in the General Data Protection Regulation and its ethical underpinnings, showing its focus on the provision of information and explanation. We then discuss the pitfalls (...) with respect to this requirement by focusing on the significance of contextual and performative factors in the implementation of transparency. We show that human–computer interaction and human-robot interaction literature do not provide clear results with respect to the benefits of transparency for users of artificial intelligence technologies due to the impact of a wide range of contextual factors, including performative aspects. We conclude by integrating the information- and explanation-based approach to transparency with the critical contextual approach, proposing that transparency as required by the General Data Protection Regulation in itself may be insufficient to achieve the positive goals associated with transparency. Instead, we propose to understand transparency relationally, where information provision is conceptualized as communication between technology providers and users, and where assessments of trustworthiness based on contextual factors mediate the value of transparency communications. This relational concept of transparency points to future research directions for the study of transparency in artificial intelligence systems and should be taken into account in policymaking. (shrink)

Legal text retrieval serves as a key component in a wide range of legal text processing tasks such as legal question answering, legal case entailment, and statute law retrieval. The performance of legal text retrieval depends, to a large extent, on the representation of text, both query and legal documents. Based on good representations, a legal text retrieval model can effectively match the query to its relevant documents. Because legal documents often contain (...) long articles and only some parts are relevant to queries, it is quite a challenge for existing models to represent such documents. In this paper, we study the use of attentive neural network-based text representation for statute law document retrieval. We propose a general approach using deep neural networks with attention mechanisms. Based on it, we develop two hierarchical architectures with sparse attention to represent long sentences and articles, and we name them Attentive CNN and Paraformer. The methods are evaluated on datasets of different sizes and characteristics in English, Japanese, and Vietnamese. Experimental results show that: (i) Attentive neural methods substantially outperform non-neural methods in terms of retrieval performance across datasets and languages; (ii) Pretrained transformer-based models achieve better accuracy on small datasets at the cost of high computational complexity while lighter weight Attentive CNN achieves better accuracy on large datasets; and (iii) Our proposed Paraformer outperforms state-of-the-art methods on COLIEE dataset, achieving the highest recall and F2 scores in the top-N retrieval task. (shrink)

Der Honeywell Kitchen Computer von 1969 ist einer der ersten Rechner, der für den Heimgebrauch hergestellt wurde. Schon allein aufgrund seines wenig benutzerfreundlichen Interfaces, das im Widerspruch zur nicht-professionellen Nutzung in der häuslichen Sphäre steht, stellt er eine Kuriosität dar. Zugleich weist er Aspekte auf, die die Idee eines Computers zu Hause plausibilisieren. Dazu gehört u.a. die Gestaltung des Interfaces, aber auch die Küche als Ort der heimischen Arbeit. In 1969, the Honeywell Kitchen Computer was the first data processor that (...) was built explicitly for home use. Resembling something of an oddity, most of all because of its non-user-friendly interface that conflicts with the conditions of non-professional domestic use, the Honeywell Kitchen Computer at the same time shows some aspects which make the use of a computer at home plausible, i. a. the design of the interface and the factor of a kitchen being the place of domestic work. (shrink)