This paper examines some of the possible legal implications of the production, marketing and use of expert systems. The relevance of a legally useful definition of expert systems, comprising systems designed for use both by laymen and professionals, is related to the distinctions inherent in the legal doctrine underlying provision of goods and provision of services. The liability of the sellers and users of, and contributors to, expert systems are examined in terms of (...) professional malpractice as well as product liability. A recurring theme indicates that legislators may be inclined to restrict possibilities of liability suits in order to avoid disincentives to the creation of expert systems. (shrink)

To effectively pursue ethical action, the business community must recognize that the fundamental form of human association is not the "social contract" into which persons enter as atomic individuals, making partial commitments to each other for the purpose of gaining limited common ends or of satisfying certain laws. The fundamental form of human association is rather the face to face community in which ongoing commitments are the rule and in which aspects of every individual''s experience are conditioned by the continuing (...) membership. The following discussion initiates a preliminary phase in the consideration of what constitutes ethical issues associated with the business applications of expert systems. The focus is on knowledge based expert system applications in public accounting, specifically in the audit domain. Prior research on the development and use of expert systems in auditing has focused on a limited set of ethical issues. Niebuhr''s theory of the "the responsible self" is used here to broaden the scope of what constitutes an ethical issue and provides a framework for identifying responsible action. Within this framework, an action is responsible if it takes into consideration ongoing relationships among the stakeholder groups affected. Actions prior to the development of the system along with the potential consequences for the system must be considered. The discursive requirements that provide the context and conditions necessary for implementing the proposed theoretical framework are presented and an illustration of how the responsibility ethic can be implemented in the audit expert system domain is developed. (shrink)

Although Berman and Hafner [Berman 1989, pp. 928–938] presented the possibility to adapt the model of reasoning of development of an expert system for medical diagnosis to the reasoning of a judge when he/she sentences criminals does not resemble the reasoning found in the decisions of physicians, mathematicians or statisticians.When a lawyer reasons, he/she not only looks for the solution of a case; he/she simultaneously looks for the bases on which his/her reasoning can rest [Galindo 1992, pp. 363–367]. That (...) is to say, he/she not only needs to find the solution but moreover he/she has to find the references (laws, jurisprudence and bibliography) that allow him/her to argue the solution. (shrink)

This paper presents a four layer model for working with legal knowledge in expert systems. It distinguishes five sources of knowledge. Four contain basic legal knowledge found in published and unpublished sources. The fifth consists of legal metaknowledge. In the model the four basic legal knowledge sources are placed at the lowest level. The metaknowledge is placed at levels above the other four knowledge sources. The assumption is that the knowledge is represented only once. The use of metaknowledge (...) at various levels should make it possible to use the appropriate knowledge for the problem presented to the system. The knowledge has to be represented as closely to the original format as possible for this purpose. Suitable representation formalisms for the various types of knowledge in the five knowledge sources are discussed. It is not possible to indicate a best representation formalism for each knowledge source. (shrink)

Around the world, private and public organizations use software called legal expert systems to compute taxes. This software must comply with the laws they are designed to implement. As such, a bug or an error in a program that leads to tax miscalculations can have heavy legal and democratic consequences. However, increasing evidence suggests that some legal expert systems may not comply with the law. Moreover, traditional software development processes mean that legal expert systems (...) are difficult to adapt to the continuous flow of new legislation. To prevent further software decay and to reconcile these systems with the growing demand for algorithmic transparency, we argue that there is a need for a new development process for legal expert systems. This new system must be built to comply with the law, in particular the GDPR. It must also respect democratic transparency. For these reasons, we present a solution built by lawyers and computer scientists: C atala, a new programming language coupled with a pair programming development process. (shrink)

In attempting to provide protection to individuals and communities, childhood immunization has benefits that far outweigh disease risks. However, some parents decide not to immunize their children with some or all vaccines for reasons including lack of trust in governments, health professionals, and vaccine manufacturers. This article employs a theoretical analysis of trust and distrust to explore how twenty-seven parents with a history of vaccine rejection in two Australian cities view the expert systems central to vaccination policy and (...) practice. Our data show how perceptions of the profit motive generate distrust in the expert systems pertaining to vaccination. Our participants perceived that pharmaceutical companies had a pernicious influence over the systems driving vaccination: research, health professionals, and government. Accordingly, they saw vaccine recommendations in conflict with the interests of their child and “the system” underscored by malign intent, even if individual representatives of this system were not equally tainted. This perspective was common to parents who declined all vaccines and those who accepted some. We regard the differences between these parents—and indeed the differences between vaccine decliners and those whose Western medical epistemology informs reflexive trust—as arising from the internalization of countering views, which facilitates nuance. (shrink)

Legal expert systems are computer applications that can mimic the consultation process of a legal expert to provide advice specific to a given scenario. The core of these systems is the experts’ knowledge captured in a sophisticated and often complex logic or rule base. Such complex systems rely on both knowledge engineers or system programmers and domain experts to maintain and update in response to changes in law or circumstances. This paper describes a pragmatic approach (...) using process modelling techniques that enables a complex legal expert system to be maintained and updated dynamically by a domain expert such as a legal practitioner with little computing knowledge. The approach is illustrated using a case study on the design of an online expert system that allows a user to navigate through complex legal options in the domain of International Family Law. (shrink)

Reasoners compare problems to prior cases to draw conclusions about a problem and guide decision making. All Case-Based Reasoning (CBR) employs some methods for generalizing from cases to support indexing and relevance assessment and evidences two basic inference methods: constraining search by tracing a solution from a past case or evaluating a case by comparing it to past cases. Across domains and tasks, however, humans reason with cases in subtly different ways evidencing different mixes of and mechanisms for these components.In (...) recent CBR research in Artificial Intelligence (AI), five paradigmatic approaches have emerged: statistically-oriented, model-based, planning/design-oriented, exemplar-based, and adversarial or precedent-based. The paradigms differ in the assumptions they make about domain models, the extent to which they support symbolic case comparison, and the kinds of inferences for which they employ cases. (shrink)

From understanding ageing to the creation of artificial membrane‐bounded ‘organisms’, systems biology and synthetic biology are seen as the latest revolutions in the life sciences. They certainly represent a major change of gear, but paradigm shifts? This is open to debate, to say the least. For scientists they open up exciting ways of studying living systems, of formulating the ‘laws of life’, and the relationship between the origin of life, evolution and artificial biological systems. However, the ethical (...) and societal considerations are probably indistinguishable from those of human genetics and genetically modified organisms. There are some tangible developments just around the corner for society, and as ever, our ability to understand the consequences of, and manage, our own progress lags far behind our technological abilities. Furthermore our educational systems are doing a bad job of preparing the next generation of scientists and non‐scientists. (shrink)

Background: The castor bean is a large grassy or semi-wooden shrub or small tree. Any part of the castor plant parts can suffering from a disease that weakens the ability to grow and eliminates its production. Therefore, in this paper will identify the pests and diseases present in castor culture and detect the symptoms in each disease. Also images is showing the symptom form in this disease. Objectives: The main objective of this expert system is to obtain appropriate diagnosis (...) of the disease. Methods: In this paper, the expert system is designed for the ability of agricultural engineers to detect and diagnose disease of castor like as: seeding blight, alternaria blight, cercospora leaf spot, powdery mildew and wilt. This system presents the disease symptoms, survival and spread, favorable conditions and image for each disease. Clips and Delphi expert system languages are used for designing and implementing the proposed expert system. Results: The expert system in the diagnosis of castor diseases was assessed by farmers and agricultural engineers and they were satisfied and accepted with its quality of performance. Conclusions: The expert system is easy for farmers and people have experience in the plant of castor to detect and diagnosis the symptoms that may face this plant from several disease. (shrink)

The question whether international law is a system is one of the modern topics discussed by specialists of international law. The text of P. Saganek poses this question with respect to the rules on international responsibility. The two aims are to establish whether the rules on state responsibility are a system themselves and whether they may prima facie support the idea of international law as such a system. The two prima facie answers are positive. Every violation of international law gives (...) rise to state responsibility if it can be attributed to a state and no circumstance precluding wrongfulness is in place. In this sense the rules on state responsibility form a sub-system supporting the thesis on the systemic nature of international law. On a closer analysis one can encounter several doubts as to both answers. Paradoxically those rules are too ideal, too systemic. The author – without denying the necessity of several if not the majority of the identified rules – refers to a tendency of presenting as law some non-binding documents prepared by expert groups. This is a part of a wider process of ‘paper-law’. In this sense expert groups engage in ‘creating the language’ in which the true subjects of international law are expected to speak. (shrink)

Background: Depression (major depressive disorder) is a common and serious medical illness that negatively affects how you feel, the way you think and how you act. Fortunately, it is also treatable. Depression causes feelings of sadness and/or a loss of interest in activities once enjoyed. It can lead to a variety of emotional and physical problems and can decrease a person’s ability to function at work and at home. Depression affects an estimated one in 15 adults (6.7%) in any given (...) year. And one in six people (16.6%) will experience depression at some time in their life. Depression can strike at any time, but on average, first appears during the late teens to mid-20s. Women are more likely than men to experience depression. Some studies show that one-third of women will experience a major depressive episode in their lifetime. Objectives: The main goal of this expert system is to get the appropriate diagnosis of disease and the correct treatment and give the appropriate method of treatment through several tips that concern the disease and how to treat it and we will see it through the application on the expert system. Methods: in this paper the design of the proposed Expert System which was produced to help Psychologist in diagnosing depression disease through its symptoms such as: a loss of energy, a change in appetite, sleeping more or less, anxiety, reduced concentration, indecisiveness, restlessness, feelings of worthlessness, guilt or hopelessness and thoughts of self-harm or suicide. The proposed expert system presents an overview about depression disease is given, the cause of diseases is outlined and the treatment of disease whenever possible is given out. SL5 Object Expert System language was used for designing and implementing the proposed expert system. Results: The proposed depression disease diagnosis expert system was evaluated by psychologist students and they were satisfied with its performance. Conclusions: The Proposed expert system is very useful for psychologist, patients with depression and newly graduated psychologist. (shrink)

Background: Arthritis is very common but is not well understood. Actually, “arthritis” is not a single disease; it is an informal way of referring to joint pain or joint disease. There are more than 100 different types of arthritis and related conditions. People of all ages, sexes and races can and do have arthritis, and it is the leading cause of disability in America. More than 50 million adults and 300,000 children have some type of arthritis. It is most common (...) among women and occurs more frequently as people get older. Common arthritis joint symptoms include swelling, pain, stiffness and decreased range of motion. Symptoms may come and go. They can be mild, moderate or severe. They may stay about the same for years, but may progress or get worse over time. Severe arthritis can result in chronic pain, inability to do daily activities and make it difficult to walk or climb stairs. Arthritis can cause permanent joint changes. These changes may be visible, such as knobby finger joints, but often the damage can only be seen on X-ray. Some types of arthritis also affect the heart, eyes, lungs, kidneys and skin as well as the joints. Objectives: The main goal of this expert system is to get the appropriate diagnosis of disease and the correct treatment and give the appropriate method of treatment through several tips that concern the disease and how to treat it and we will see it through the application on the expert system. Methods: in this paper the design of the proposed Expert System which was produced to help Orthopedist in diagnosing Arthritis disease through its symptoms such as: pain on pressure in a joint , Inflammation indicated by joint swelling, Stiffness especially in the morning , Loss of flexibility of joint, Limited, joint movement, Deformity of the joints , Weight loss and fatigue , Non-specific fever and Crepitus. The proposed expert system presents an overview about Arthritis disease is given, the cause of diseases is outlined and the treatment of disease whenever possible is given out. SL5 Object Expert System language was used for designing and implementing the proposed expert system. Results: The proposed Arthritis disease diagnosis expert system was evaluated by Orthopedics students and they were satisfied with its performance. Conclusions: The Proposed expert system is very useful for Orthopedist, patients with arthritis and newly graduated Orthopedics students. (shrink)

By studying several cases of expert systems' use, a variety of difficulties were identified as directly depending on specific characteristics of experts and their tasks. This concerns more than the questions: “May experts be replaced by machines?” or “Is experts' knowledge explicable?”. The organisational structure of their work as well as the cyclic, non-plannable way of their task performing have further relevance. The paper introduces the concept of experts' systems to deal with diversities of their expertise and (...) complexities of their work. It draws a distinction between non-monotonic problem solving, exploration, medium and modification, and argues that these modes are not reducible to yet another improved input/output strategy or dialogue style but introduce additional functions supporting the human-computer interaction according to experts' needs. In the first few sections, the paper covers the theoretical and empirical results of our research, whereas Section 4 introduces our design suggestions for experts' systems. (shrink)

There is a disparity between the multitude of apparently successful expert system prototypes and the scarcity of expert systems in real everyday use. Modern tools make it deceptively easy to make reasonable prototypes, but these prototypes are seldom made subject to serious evaluation. Instead the development team confronts their product with a set of cases, and the primary evaluation criterion is the percentage of correct answers: we are faced with a “95% syndrome”. Other aspects related to the (...) use of the system are almost ignored. There is still a long way to go from a promising prototype to a final system.It is maintained in the article that a useful test must be performed by future users in a situation that is as realistic as possible. If this is not done claims of usefulness cannot be justified. It is also stated that prototyping does not make “traditional” analysis and design obsolete, although the contents of these activities will change.In order to discuss the effects of using the systems a distinction between expert systems as media, tools and experts is proposed. (shrink)

After the setbacks suffered in the 1970s as a result of the ‘Lighthill Report’ (Lighthill, 1973), the science of Artificial Intelligence (AI) has undergone a dramatic revival of fortunes in the 1980s. But despite the obvious enormity and complexity of the problems tackled by AI, it still remains rather parochial in relation to the import of alternative though potentially fruitful ideas from other disciplines. With this in mind, the aim of the present paper is to utilise ideas from the sociology (...) of science in order to explore some current issues in AI and, in particular, the branch of expert systems.It is argued that the sociology of sciences shares a common focus of enquiry along with AI — namely, the nature of knowledge — and has a role to play in the understanding, design and future development of expert systems. (shrink)

The paper seeks to identify how teacher expertise is implicitly and explicitly conceptualised in current English education policy in respect of the professional development of teachers. We focus specifically on conceptualisations of expertise in the Early Career Framework (ECF), both in terms of the policy documentation produced by the Department for Education and in terms of a selection of publicly available materials produced by the lead providers of the ECF. We aim to locate these conceptualisations in terms of broader sociological (...) and philosophical debates about the nature of expertise and its relationship to professional work, in addition to recent research on the policy context of teacher education and professional development in England. Our analysis reveals the inappropriacy of ‘expert systems’ approaches to expertise in educational contexts, the underlying assumptions embedded in policy in terms of what constitutes high-quality teaching practice and the insufficiency of relying on an appointed advisory group and organisations preferred by government for identifying and iterating criteria for expertise. (shrink)

Often, knowledge engineers become so involved in the development process of the expert system that they fail to look further down the road toward the expert system's institutionalization within the organization. Institutionalization is an important component of the expert system planning process. More specifically, the legal issues associated with expert systems development and deployment are critical institutionalization factors. This paper looks at some expert system institutionalization guidelines, and then focuses on legal considerations.

Expert systems are being developed in a multitude of domains worldwide. The usage of expert systems within organizations is growing; however, many expert systems projects still fail due to poor ‘institutionalization’ practices. This paper addresses various strategies for providing the transfer of expert systems technology within organizations. Specifically, this paper will address expert system technology transfer strategies using examples from United States and Mexican organizations.

Expert systems have had little impact as computing artifacts. In this paper we argue that the reason for this stems from the underlying assumption of most builders of expert systems that an expert system needs to acquire information and to control the interaction between the human user and itself. We show that this assumption has serious linguistic and usability flaws which diminish the likelihood of producing socially acceptable expert systems. We propose a reversal (...) of this paradigm, for the design of expert systems, by assuming that it is the human user who needs to acquire information and to control the interaction between themselves and the system. (shrink)

Three case studies were conducted on the implications of the use of expert systems for the work of clerks and operators in Britain. An expert system had been introduced in a process control application. The operators' work was deskilled. The second case was a fault diagnosis application. An operator was very happy with his new work. In the third case, insurance clerks received training to operate an expert system which extended the scope of their work. In (...) conclusion, it is suggested that expert systems extend the range of work which can be automated, but may not have unique impacts. (shrink)

Expert systems provide new languages and a new methodology for automating knowledge-intensive processes. Whilst the benefits expected are ubiquitously stated, probable negative impacts are seldom admitted by the dominant actors in the field. We deal with probable problematic impacts on employment as well as contents and structure of work both in production and the service and administration areas and make some suggestions concerning measures to be taken to account for these impacts assuming no radical change as to the (...) prevailing ideology of working organization. (shrink)

Today’s everyone normal life can include a normal rate of playing computer games or video games; but what about an excessive or compulsive use of video games that impact on our life? Our kids, who usually spend a lot of time in playing video games will likely have a trouble in paying attention to their school lessons. In this paper, we introduce an expert system to help users in getting the correct diagnosis of the health problem of video game (...) addictions that range from (Musculoskeletal issues, Vision problems and Obesity). Moreover, this expert system provides information about the problem and tell us how we can solve it. SL5 Object expert system language was used to design and implement the expert system. (shrink)

The data mining field in computer science specializes in extracting implicit information that is distributed across the stored data records and/or exists as associations among groups of records. Criminal databases contain information on the crimes themselves, the offenders, the victims as well as the vehicles that were involved in the crime. Among these records lie groups of crimes that can be attributed to serial criminals who are responsible for multiple criminal offenses and usually exhibit patterns in their operations, by specializing (...) in a particular crime category (i.e., rape, murder, robbery, etc.), and applying a specific method for implementing their crimes. Discovering serial criminal patterns in crime databases is, in general, a clustering activity in the area of data mining that is concerned with detecting trends in the data by classifying and grouping similar records. In this paper, we report on the different statistical and neural network approaches to the clustering problem in data mining in general, and as it applies to our crime domain in particular. We discuss our approach of using a cascaded network of Kohonen neural networks followed by heuristic processing of the networks outputs that best simulated the experts in the field. We address the issues in this project and the reasoning behind this approach, including: the choice of neural networks, in general, over statistical algorithms as the main tool, and the use of Kohonen networks in particular, the choice for the cascaded approach instead of the direct approach, and the choice of a heuristics subsystem as a back-end subsystem to the neural networks. We also report on the advantages of this approach over both the traditional approach of using a single neural network to accommodate all the attributes, and that of applying a single clustering algorithm on all the data attributes. (shrink)

Actual AI research began auspiciously around 1955 with Allen Newell and Herbert Simon's work at the RAND Corporation. Newell and Simon proved that computers could do more than calculate. They demonstrated that computers were physical symbol systems whose symbols could be made to stand for anything, including features of the real world, and whose programs could be used as rules for relating these features. In this way computers could be used to simulate certain important aspects intelligence. Thus the information-processing (...) model of the mind was born. But, looking back over these fifty years, it seems that theoretical AI with its promise of a robot like HAL appears to be a perfect example of what Imre Lakatos has called a "degenerating research program". (shrink)

The integration of machine learning algorithms into the legal recommendation system marks a burgeoning area of research, with a particular focus on enhancing the accuracy and efficiency of judicial decision-making processes. The application of Bayesian Network (BN) emerges as a potent tool in this context, promising to address the inherent complexities and unique nuances of legal texts and individual case subtleties. However, the challenge of achieving high accuracy in BN parameter learning, especially under conditions of limited data, remains a significant (...) hurdle. This study proposes an Enhanced Maximum Parameter Learning (EMPL) algorithm, tailored for BN parameter optimization in scenarios characterized by small sample sizes. The EMPL algorithm, innovatively incorporating the Synthetic Minority Over-sampling Technique (SMOTE), begins with the formulation of inequality constraints derived from domain expertise. It establishes a minimal dataset threshold necessary for effective parameter learning. Through the introduction of an index weighting factor function that dynamically adjusts according to the sample size, the algorithm facilitates the derivation of refined BN parameters. The core innovation of the EMPL algorithm lies in its use of an exponentially weighted factor function, designed to be responsive to variations in sample size, and its capacity to expand the parameter space using SMOTE to align with qualitative constraints from expert insights. This approach enables the integration of data-derived parameters with those obtained through expert experience in an exponentially weighted manner, culminating in the optimization of BN parameters. Comparative analysis reveals that the EMPL algorithm achieves superior learning accuracy over traditional Maximum Likelihood Estimation (MLE) and qualitative maximum a posteriori (QMAP) approach, particularly in contexts of sparse data. Furthermore, it demonstrates enhanced performance relative to variable weight learning algorithms, underscoring its potential to significantly improve decision-making processes in the legal domain through advanced BN parameter learning. (shrink)

Expert Systems (ES) are as yet imperfectly defined. Their two consistently cited characteristics are domain knowledge and expert-level performance. We propose that current structural definitions are inadequate and suggest a view of ES as communication channels. We proceed to explore the factors influencing applicability of ES technology to an enterprise and the impacts that could be expected. A consequence of this view is the idea of incremental information loss on the path from the expert to the (...) ES user. Strategies for minimizing this loss derive naturally from our perspective and are evident in successful ES. (shrink)

On the example of the online game Akinator, the basic principles on which programs of this type are built are considered. Effective technics have been proposed by which artificial intelligence systems can build logical inferences that allow to identify an unknown subject from its description. To confirm the considered hypotheses, the terminological analysis of definition of the program "Akinator" offered by the author is carried out. Starting from the assumptions given by the author's definition, the article complements their definitions (...) presented by other researchers and analyzes their constituent theses. Finally, some proposals are made for the next steps in improving the program. The Akinator program, at one time, became one of the most famous online games using artificial intelligence. And although this was not directly stated, it was clear to the experts in the field of artificial intelligence that the program uses the techniques of expert systems and is built on inference rules. At the moment, expert systems have lost their positions in comparison with the direction of neural networks in the field of artificial intelligence, however, in the case considered in the article, we are talking about techniques using both directions – hybrid systems. Games for filling semantics interact with the user, expanding their semantic base and use certain strategies to achieve the best result. The playful form of such semantics filling programs is beneficial for researchers by involving a large number of players. The article examines the techniques used by the Akinator program, and also suggests possible modifications to it in the future. This study, first of all, focuses on how the knowledge base of the Akinator program is built, it consists of incomplete sets, which can be filled and adjusted as a result of further iterations of the program launches. It is important to note our assumption that the order of questions used by the program during the game plays a key role, because it determines its strategy. It was identified that the program is guided by the principles of nonmonotonic logic – the assumptions constructed by the program are not final and can be rejected by it during the game. The three main approaches to acquisite semantics proposed by Jakub Šimko and Mária Bieliková are considered, namely, expert work, crowdsourcing and machine learning. Paying attention to machine learning, the Akinator program using machine learning to build an effective strategy in the game presents a class of hybrid systems that combine the principles of two main areas in artificial intelligence programs – expert systems and neural networks. (shrink)

For quite some time, the research in artificial intelligence has focused on expert systems, because here are to be found practical applications at the experimental stage which may soon become widespread. This focus makes more pressing the need to link the debate about the fundamental efficiency of artificial intelligence with those activities that aim at the application of specialized expert systems. In this paper, I begin by considering the stages and the development of human expertise. As (...) a frame of reference I propose a polar dialectic model of the development of human acting and thinking that explicitly deals with the interplay of calculating rationality and intuition. This suggests the use of expert systems as decision aids particularly in the field of maintenance work on the shop-floor. With regard to this case, some theses concerning the human-centred shaping of technology and work are presented. (shrink)

The paper questions the expert system paradigm, both in terms of its range of application, and as a significant contribution to the understanding of artificial intelligence. The viewpoint is that of the systems designer who must judge the applicability of these methods in imminent and future systems. The expert system paradigm, (ESP for short), is criticised not because it is ubiquitously wrong, but because its range of application appears to be very limited, and much promise is (...) made of its application in areas where its success is likely to be little more than a matter of luck. The paper considers the success in both academic and commercial settings. It is suggested that the contribution of the ESP to the wider ambitions of AI is modest, and to the practical user is still a considerable and largely unquantifiable risk. (shrink)

Rapid developments in Artificial Intelligence are leading to an increasing human reliance on machine decision making. Even in collaborative efforts with Decision Support Systems (DSSs), where a human expert is expected to make the final decisions, it can be hard to keep the expert actively involved throughout the decision process. DSSs suggest their own solutions and thus invite passive decision making. To keep humans actively ‘on’ the decision-making loop and counter overreliance on machines, we propose a ‘reflection (...) machine’ (RM). This system asks users questions about their decision strategy and thereby prompts them to evaluate their own decisions critically. We discuss what forms RMs can take and present a proof-of-concept implementation of a RM that can produce feedback on users’ decisions in the medical and law domains. We show that the prototype requires very little domain knowledge to create reasonably intelligent critiquing questions. With this prototype, we demonstrate the technical feasibility to develop RMs and hope to pave the way for future research into their effectiveness and value. (shrink)

Antimicrobial resistance is a critical public health challenge, and the contribution of the widespread use of antimicrobials in food animals to bacterial drug resistance and human infection demands greater policymaker attention. Global consumption of antimicrobials in food animal production by 2030 is projected to rise by two-thirds due to increases in both food animal production and demand for animal products. In the United States, the volume of antibiotics sold for use in food-producing animals is at least three times greater than (...) that sold for human use. A One Health approach that emphasizes the connections among the health of humans, animals, and the environment is needed to address antibiotic resistance in an integrated manner. This approach holds the promise of collaboration across multiple disciplines, including doctors, veterinarians, food safety professionals, and environmental health experts. (shrink)

The European Union’s Artificial Intelligence Act (AI Act) is a groundbreaking regulatory framework that integrates technical concepts and terminology from the rapidly evolving ecosystems of AI research and innovation into the legal domain. Precise definitions accessible to both AI experts and lawyers are crucial for the legislation to be effective. This paper provides an interdisciplinary analysis of the concepts of AI system, general purpose AI system, foundation model and generative AI across the different versions of the legal text (Commission proposal, (...) Parliament position and Council General Approach) before the final political agreement. The goal is to help bridge the understanding of these key terms between the technical and legal communities and contribute to a proper implementation of the AI Act. We provide an analysis of the concept of AI system considering its scientific foundation and the crucial role that it plays in the regulation, which requires a sound definition both from legal and technical standpoints. We connect the outcomes of this discussion with the analysis of the concept of general purpose AI system and its evolution during the negotiations. We also address the distinct conceptual meanings of AI system vs AI model and explore the technical nuances of the term foundation model. We conclude that rooting the definition of foundation model to its general purpose capabilities following standardised evaluation methodologies appears to be most appropriate approach. Lastly, we tackle the concept of generative AI, arguing that definitions of AI system that include “content” as one of the system’s outputs already captures it, and concluding that not all generative AI is based on foundation models. (shrink)

This paper combines three computational argumentation systems to model the sequence of argumentation in a famous murder trial and the appeal procedure that followed. The paper shows how the argumentation scheme for argument from expert opinion can be built into a testing procedure whereby an argument graph is used to interpret, analyze and evaluate evidence-based natural language argumentation of the kind found in a trial. It is shown how a computational argumentation system can do this by combining argument (...) schemes with argumentation graphs. Frighteningly, it is also shown by this example that when there are potentially confusing conflicting arguments from expert opinion, a jury can only too easily accept a conclusion prematurely before considering critical questions that need to be asked. (shrink)