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Responsible Artificial Intelligence
In this book, the author examines the ethical implications of Artificial Intelligence systems as they integrate and replace traditional social structures in new sociocognitive-technological environments. She discusses issues related to the integrity of researchers, technologists, and manufacturers as they design, construct, use, and manage artificially intelligent systems; formalisms for reasoning about moral decisions as part of the behavior of artificial autonomous systems such as agents and robots; and design methodologies for social agents based on societal, moral, and legal values. Throughout the book the author discusses related work, conscious of both classical, philosophical treatments of ethical issues and the implications in modern, algorithmic systems, and she combines regular references and footnotes with suggestions for further reading. This short overview is suitable for undergraduate students, in both technical and non-technical courses, and for interested and concerned researchers, practitioners, and citizens.
Agent-Directed Simulation and Systems Engineering
The only book to present the synergy between modeling and simulation, systems engineering, and agent technologies expands the notion of agent-based simulation to also deal with agent simulation and agent-supported simulation. Accessible to both practitioners and managers, it systematically addresses designing and building agent systems from a systems engineering perspective.
The Oxford Handbook of Ethics of AI
This interdisciplinary and international handbook captures and shapes much needed reflection on normative frameworks for the production, application, and use of artificial intelligence in all spheres of individual, commercial, social, and public life.
Programming Multi-Agent Systems
This book constitutes the thoroughly refereed postproceedings of the Second International Workshop on Programming Multi-Agent Systems, ProMAS 2004, held in New York, NY, USA in July 2004 as a satellite workshop of AAMAS 2004. The 10 revised full papers presented together with two invited articles were carefully selected during two rounds of reviewing and revision. The papers are organized in topical sections on agent-oriented programming, agent platforms and tools, agent languages, and multi-agent systems techniques.
An Introductory Guide to Artificial Intelligence for Legal Professionals
The availability of very large data sets and the increase in computing power to process them has led to a renewed intensity in corporate and governmental use of Artificial Intelligence (AI) technologies. This groundbreaking book, the first devoted entirely to the growing presence of AI in the legal profession, responds to the necessity of building up a discipline that due to its novelty requires the pooling of knowledge and experiences of well-respected experts in the AI field, taking into account the impact of AI on the law and legal practice. Essays by internationally known expert authors introduce the essentials of AI in a straightforward and intelligible style, offering jurists as many p...
Reflections on Artificial Intelligence for Humanity
We already observe the positive effects of AI in almost every field, and foresee its potential to help address our sustainable development goals and the urgent challenges for the preservation of the environment. We also perceive that the risks related to the safety, security, confidentiality, and fairness of AI systems, the threats to free will of possibly manipulative systems, as well as the impact of AI on the economy, employment, human rights, equality, diversity, inclusion, and social cohesion need to be better assessed. The development and use of AI must be guided by principles of social cohesion, environmental sustainability, resource sharing, and inclusion. It has to integrate human r...
Supporting Reuse in Business Case Development
Determining the value of an information system for an organization is challenging, especially before the execution of the project in which the system is put into operation. Many organizations cope with problems when having to identify the potential benefits of the investment, while even more have difficulties with their quantification. An analysis, in which multiple possible investments and approaches are compared with respect to their benefits, costs and risks, is called a ‘business case’ (BC). The current frameworks that can be used to develop BCs offer too little support for the aforementioned challenges. Opportunities to improve BC frameworks, and thereby the efficiency and effectiveness of BC development, are therefore explored in this dissertation.
Machine Learning and Principles and Practice of Knowledge Discovery in Databases
This volume constitutes the papers of several workshops which were held in conjunction with the International Workshops of ECML PKDD 2022 on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2022, held in Grenoble, France, during September 19–23, 2022. The 73 revised full papers and 6 short papers presented in this book were carefully reviewed and selected from 143 submissions. ECML PKDD 2022 presents the following workshops: Workshop on Data Science for Social Good (SoGood 2022) Workshop on New Frontiers in Mining Complex Patterns (NFMCP 2022) Workshop on Explainable Knowledge Discovery in Data Mining (XKDD 2022) Workshop on Uplift Modeling (UMOD 2022) Workshop on IoT, Edge and Mobile for Embedded Machine Learning (ITEM 2022) Workshop on Mining Data for Financial Application (MIDAS 2022) Workshop on Machine Learning for Cybersecurity (MLCS 2022) Workshop on Machine Learning for Buildings Energy Management (MLBEM 2022) Workshop on Machine Learning for Pharma and Healthcare Applications (PharML 2022) Workshop on Data Analysis in Life Science (DALS 2022) Workshop on IoT Streams for Predictive Maintenance (IoT-PdM 2022)
Applications of Artificial Intelligence, Big Data and Internet of Things in Sustainable Development
This book focuses on different algorithms and models related to AI, big data and IoT used for various domains. It enables the reader to have a broader and deeper understanding of several perspectives regarding the dynamics, challenges, and opportunities for sustainable development using artificial intelligence, big data and IoT. Applications of Artificial Intelligence, Big Data and Internet of Things (IoT) in Sustainable Development focuses on IT-based advancements in multidisciplinary fields such as healthcare, finance, bioinformatics, industrial automation, and environmental science. The authors discuss the key issues of security, management, and the realization of possible solutions to hu...
