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The Second Symposium on Professional Practice in AI 2006 is a conference within the IFIP World Computer Congress 2006, Santiago, Chile. The Symposium is organised by the IFIP Technical Committee on Artificial Intelligence (Technical Committee 12) and its Working Group 12.5 (Artificial Intelligence Applications). The First Symposium in this series was one of the conferences in the IFIP World Computer Congi-ess 2004, Toulouse France. The conference featured invited talks by Rose Dieng, John Atkinson, John Debenham and Max Bramer. The Symposium was a component of the IFIP AI 2006 conference, organised by Professor Max Bramer. I should like to thank the Symposium General Chair, Professor Bramer for his considerable assistance in making the Symposium happen within a very tight deadline. These proceedings are the result of a considerable amount of hard work. Beginning with the preparation of the submitted papers, the papers were each reviewed by at least two members of the international Program Committee. The authors of accepted papers then revised their manuscripts to produce their final copy. The hard work of the authors, the referees and the Program Committee is gratefully aclaiowledged. The IFIP AI 2006 conference and the Symposium are the latest in a series of conferences organised by IFIP Technical Committee 12 dedicated to the techniques of Aitificial Intelligence and their real-world applications. Further infoirmation about TC12 can be found on our website http;//www.ifiptcI2.org.
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 practical examples and business cases as possible so that they are able to understand the real application of this technology and its impact on their jobs and lives. Elements of the analysis include the following: crucial terms: natural language processing, machine learning and deep learning; regulations in force in major jurisdictions; ethical and social issues; labour and employment issues, including the impact that robots have on employment; prediction of outcome in the legal field (judicial proceedings, patent granting, etc.); massive analysis of documents and identification of patterns from which to derive conclusions; AI and taxation; issues of competition and intellectual property; liability and responsibility of intelligent systems; AI and cybersecurity; AI and data protection; impact on state tax revenues; use of autonomous killer robots in the military; challenges related to privacy; the need to embrace transparency and sustainability; pressure brought by clients on prices; minority languages and AI; danger that the existing gap between large and small businesses will further increase; how to avoid algorithmic biases when AI decides; AI application to due diligence; AI and non-disclosure agreements; and the role of chatbots. Interviews with pioneers in the field are included, so readers get insights into the issues that people are dealing with in day-to-day actualities. Whether conceiving AI as a transformative technology of the labour market and training or an economic and business sector in need of legal advice, this introduction to AI will help practitioners in tax law, labour law, competition law and intellectual property law understand what AI is, what it serves, what is the state of the art and the potential of this technology, how they can benefit from its advantages and what are the risks it presents. As the global economy continues to suffer the repercussions of a framework that was previously fundamentally self-regulatory, policymakers will recognize the urgent need to formulate rules to properly manage the future of AI.
This book has been developed with an intellectual framework to focus on the challenges and specific qualities applicable to graduates on the threshold of their careers. Young professionals have to establish their competence in complying with multifaceted sets of ethical, environmental, social, and technological parameters. This competence has a vital impact on the curricula of higher education programs, because professional bodies today rely on accredited degrees as the main route for membership. Consequently, this four-part book makes a suitable resource for a two-semester undergraduate course in professional practice and career development in universities and colleges. With its comprehensive coverage of a large variety of topics, each part of the book can be used as a reference for other related courses where sustainability, leadership, systems thinking and professional practice are evident and increasingly visible. Features Identifies the values that are unique to the engineering and computing professions, and promotes a general understanding of what it means to be a member of a profession Explains how ethical and legal considerations play a role in engineering practice Discusses the importance of professional communication and reflective practice to a range of audiences Presents the practices of leadership, innovation, entrepreneurship, safety and sustainability in engineering design Analyzes and discusses the contemporary practices of project management, artificial intelligence, and professional career development.
Cyber-solutions to real-world business problems Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine learning to solve problems. Presenting 50 case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe. The rapidly evolving field of artificial intelligence has expanded beyond research labs and computer science departments and made its way into the mainstream business environment. Artificial intelligence and machine learning are cited as the most important modern business trends to drive success. It is used in areas ranging from banking and finance to social media and marketing. This technology continues to provide innovative solutions to businesses of all sizes, sectors and industries. This engaging and topical book explores a wide range of cases illustrating how businesses use AI to boost performance, drive efficiency, analyse market preferences and many others. Best-selling author and renowned AI expert Bernard Marr reveals how machine learning technology is transforming the way companies conduct business. This detailed examination provides an overview of each company, describes the specific problem and explains how AI facilitates resolution. Each case study provides a comprehensive overview, including some technical details as well as key learning summaries: Understand how specific business problems are addressed by innovative machine learning methods Explore how current artificial intelligence applications improve performance and increase efficiency in various situations Expand your knowledge of recent AI advancements in technology Gain insight on the future of AI and its increasing role in business and industry Artificial Intelligence in Practice: How 50 Successful Companies Used Artificial Intelligence to Solve Problems is an insightful and informative exploration of the transformative power of technology in 21st century commerce.
As new technologies and data become essential for the delivery of optimal care, nurses will play an increasingly vital role in developing and implementing digital health strategies. This timely book is designed to help you develop proficiency and confidence to lead this digital transformation.Harnessing Digital Technology and Data for Nursing Practice provides comprehensive coverage of the historical, theoretical and practical dimensions of the digital transformation in nursing. It considers a wide range of topics, from person-centred practice and user-centred design to nursing workforce development, evolving nursing practices, and the role of data in improving patient care and research. Expert insights are supported by learning activities and real-life case studies, with application of theory to practice throughout.Aimed at nurses in all settings and working at all professional levels, this book will leave the reader with an appreciation of how an array of digital technologies and data can positively impact nurses' wellbeing, support and improve your daily practice, and ultimately ensure patient-centred, safe and effective care. - Written specifically for nurses and midwives – explains how you can play a central role in shaping the digital future of health care - Provides historical, theoretical and practical perspectives – offers a sound base from which to understand the role of data technology in your work - Covers a wide spectrum of topics, including: - digital transformation of health care - nursing informatics - user-centred design - data-driven practice - person-centred care - health inequalities - telehealth and remote monitoring - ethical and legal considerations - population health - research - Provides practical insights and case studies to help you apply digital technologies in practice - Acknowledges the challenges in adopting digital health, and stresses the importance of digital literacy and nurse involvement in the design and implementation of digital solutions - Globally relevant and future oriented – creates a vision for nurses as co-navigators of care who make decisions informed by real-time patient analytics - Ancillary videos to support learning
This book problematizes and explores appropriate ways of using AI technology that can augment educational practice, especially in K-12 teaching and learning. Since the launch of OpenAI ChatGPT in November 2022, people have been debating “to chat or to cheat” while more and more educators have started to explore “to add or to integrate” it into teaching and learning. A list of questions has been on the way. What can ChatGPT produce? How accurate can the contents produced by the GPT be? What are the considerations that an instructor should have when using AI technology for student learning? To what extent can ChatGPT compete with humans in terms of learning? ChatGPT is just a technology tool, but it drops a huge bomb in the field of education, and even changes the way many think about education. The contributors of this book, as well as probing the ethical conundrums presented by generative AI and other new technologies in AI&ED, summarize an overview of practice, provided first-hand experiences, and suggested strategies and methods that are workable in the field. This cutting-edge volume will be of interest to researchers, scholars and practitioners of education, education technology, sociology, ethics and artificial intelligence. It was originally published as a special issue of Computers in the Schools.
This book enables readers to interrogate the technical, rhetorical, theoretical, and socio-ethical challenges and opportunities involved in the development and adoption of augmentation technologies and artificial intelligence. The core of our human experience and identity is forever affected by the rise of augmentation technologies that enhance human capability or productivity. These technologies can add cognitive, physical, sensory, and emotional enhancements to the body or environment. This book demonstrates the benefits, risks, and relevance of emerging augmentation technologies such as brain–computer interaction devices for cognitive enhancement; robots marketed to improve human social interaction; wearables that extend human senses, augment creative abilities, or overcome physical limitations; implantables that amplify intelligence or memory; and devices, AI generators, or algorithms for emotional augmentation. It allows scholars and professionals to understand the impact of these technologies, improve digital and AI literacy, and practice new methods for their design and adoption. This book will be vital reading for students, scholars, and professionals in fields including technical communication, UX design, computer science, human factors, information technology, sociology of technology, and ethics. Artifacts and supplemental resources for research and teaching can be found at https://fabricofdigitallife.com and www.routledge.com/9781032263755.
This volume tackles a quickly-evolving field of inquiry, mapping the existing discourse as part of a general attempt to place current developments in historical context; at the same time, breaking new ground in taking on novel subjects and pursuing fresh approaches. The term "A.I." is used to refer to a broad range of phenomena, from machine learning and data mining to artificial general intelligence. The recent advent of more sophisticated AI systems, which function with partial or full autonomy and are capable of tasks which require learning and 'intelligence', presents difficult ethical questions, and has drawn concerns from many quarters about individual and societal welfare, democratic decision-making, moral agency, and the prevention of harm. This work ranges from explorations of normative constraints on specific applications of machine learning algorithms today-in everyday medical practice, for instance-to reflections on the (potential) status of AI as a form of consciousness with attendant rights and duties and, more generally still, on the conceptual terms and frameworks necessarily to understand tasks requiring intelligence, whether "human" or "A.I."
Introduces Machine Learning Techniques and Tools and Provides Guidance on How to Implement Machine Learning Into Chemical Safety and Health-related Model Development There is a growing interest in the application of machine learning algorithms in chemical safety and health-related model development, with applications in areas including property and toxicity prediction, consequence prediction, and fault detection. This book is the first to review the current status of machine learning implementation in chemical safety and health research and to provide guidance for implementing machine learning techniques and algorithms into chemical safety and health research. Written by an international team of authors and edited by renowned experts in the areas of process safety and occupational and environmental health, sample topics covered within the work include: An introduction to the fundamentals of machine learning, including regression, classification and cross-validation, and an overview of software and tools Detailed reviews of various applications in the areas of chemical safety and health, including flammability prediction, consequence prediction, asset integrity management, predictive nanotoxicity and environmental exposure assessment, and more Perspective on the possible future development of this field Machine Learning in Chemical Safety and Health serves as an essential guide on both the fundamentals and applications of machine learning for industry professionals and researchers in the fields of process safety, chemical safety, occupational and environmental health, and industrial hygiene.