These proceedings represent the work of contributors to the European Conference on the Impact of Artificial Intelligence and Robotics (ECIAIR 2019), hosted by EM-Normandie Business School on 31 October-1 November 2019. The Conference Chair is Paul Griffiths from EM-Normandie Business School and the Programme Chair is Mitt Nowshade Kabir, from Trouvus, Canada. The motivation to launch the European Conference on the Impact of AI and Robotics (ECIAIR) has come about as a result of the maturing of artificial intelligence and robotics, particularly of the cognitive computing kind, which is producing an unprecedented revolution in the role of work and professionals in society. So this Conference aims to focus not so much on the technology itself, but rather its consequence on knowledge work and society. The opening keynote presentation is given by Dr Mariano E. Giménez, from the University of Strasbourg, France on the topic of Hybrid Operating Rooms and Image-Guided Surgery, the way to Automation. Then an afternoon screening of the Netflix Film "The Great Hacked" followed by a Q&A. The second day of the conference will open with an address by Dr Mitt Nowshade Kabir, who will talk about Artificial General Intelligence, Consciousness and the Future of AI. The conference will close on Friday with a Panel of Philosophers: What limits should humans set on Artificial Intelligence? With an initial submission of 104 abstracts, after the double blind, peer review process there are 44 Academic research papers, 4 PhD research papers, 1 Masters Research papers, 4 non-academic papers and 4 work-in-progress papers published in these Conference Proceedings. These papers represent research from Australia, Belarus, Canada, China, Denmark, Finland, France, Germany, India, Iran, Iraq, Italy, Japan, Lithuania, Netherlands, Norway, Poland, Portugal, Romania, Russia, South Africa, Spain, Sweden, Taiwan, Thailand, UAE, UK and USA.

This book constitutes the refereed proceedings of the 4th Symposium of the Norwegian AI Society, NAIS 2022, held in Oslo, Norway, during May 31–June 1, 2022. The 11 full papers included in this book were carefully reviewed and selected from 17 submissions. They were organized in topical sections as follows: robotics and intelligent systems; ai in cyber and digital sphere; ai in biological applications and medicine; and towards new ai methods. This is an open access book.

This cutting-edge Handbook offers a comprehensive introduction to the emerging research field of artificial intelligence (AI) in human resource management (HRM). Broadly mapping AI fields relevant for HR, it not only considers the more well-known areas of machine learning and natural language processing, but also lesser-known fields such as affective computing and robotic process automation.

This book focuses on different applications of multimedia with supervised and unsupervised data engineering in the modern world. It includes AI-based soft computing and machine techniques in the field of medical diagnosis, biometrics, networking, manufacturing, data science, automation in electronics industries, and many more relevant fields. Multimedia Data Processing and Computing provides a complete introduction to machine learning concepts, as well as practical guidance on how to use machine learning tools and techniques in real-world data engineering situations. It is divided into three sections. In this book on multimedia data engineering and machine learning, the reader will learn how to prepare inputs, interpret outputs, appraise discoveries, and employ algorithmic strategies that are at the heart of successful data mining. The chapters focus on the use of various machine learning algorithms, neural net- work algorithms, evolutionary techniques, fuzzy logic techniques, and deep learning techniques through projects, so that the reader can easily understand not only the concept of different algorithms but also the real-world implementation of the algorithms using IoT devices. The authors bring together concepts, ideas, paradigms, tools, methodologies, and strategies that span both supervised and unsupervised engineering, with a particular emphasis on multimedia data engineering. The authors also emphasize the need for developing a foundation of machine learning expertise in order to deal with a variety of real-world case studies in a variety of sectors such as biological communication systems, healthcare, security, finance, and economics, among others. Finally, the book also presents real-world case studies from machine learning ecosystems to demonstrate the necessary machine learning skills to become a successful practitioner. The primary users for the book include undergraduate and postgraduate students, researchers, academicians, specialists, and practitioners in computer science and engineering.

How people judge humans and machines differently, in scenarios involving natural disasters, labor displacement, policing, privacy, algorithmic bias, and more. How would you feel about losing your job to a machine? How about a tsunami alert system that fails? Would you react differently to acts of discrimination depending on whether they were carried out by a machine or by a human? What about public surveillance? How Humans Judge Machines compares people's reactions to actions performed by humans and machines. Using data collected in dozens of experiments, this book reveals the biases that permeate human-machine interactions. Are there conditions in which we judge machines unfairly? Is our judgment of machines affected by the moral dimensions of a scenario? Is our judgment of machine correlated with demographic factors such as education or gender? César Hidalgo and colleagues use hard science to take on these pressing technological questions. Using randomized experiments, they create revealing counterfactuals and build statistical models to explain how people judge artificial intelligence and whether they do it fairly. Through original research, How Humans Judge Machines bring us one step closer tounderstanding the ethical consequences of AI.

On what basis can we challenge Artificial Intelligence (AI) - its infusion, investment, and implementation across the globe? This book answers this question by drawing on a range of critical approaches from the social sciences and humanities, including posthumanism, ethics and human values, surveillance studies, Black feminism, and other strategies for social and political resistance. The authors analyse timely topics, including bias and language processing, responsibility and machine learning, COVID-19 and AI in health technologies, bio-AI and nanotechnology, digital ethics, AI and the gig economy, representations of AI in literature and culture, and many more. This book is for those who are currently working in the field of AI critique and disruption as well as in AI development and programming. It is also for those who want to learn more about how to doubt, question, challenge, reject, reform and otherwise reprise AI as it been practiced and promoted.

This book reports on cutting-edge legal, ethical, social and economic issues relating to robotics and automation, human-machine interaction and artificial intelligence, in different application areas. It discusses important problems such as robotic taxation, social inequality, protection of neuro-human and children rights, among others. It describes current advances and challenges in robotic regulation and governance, as well as findings relating to sustainability of robotic industries, thus filling an important gap in the robotic and AI literature. Chapters consists of revised and extended contributions to the workshop session “Debate on legal, ethical & socio-economic aspects of interactive robotics” of INBOTS 2021, held virtually on May 18-20, 2021.