A proposal that we think about digital technologies such as machine learning not in terms of artificial intelligence but as artificial communication. Algorithms that work with deep learning and big data are getting so much better at doing so many things that it makes us uncomfortable. How can a device know what our favorite songs are, or what we should write in an email? Have machines become too smart? In Artificial Communication, Elena Esposito argues that drawing this sort of analogy between algorithms and human intelligence is misleading. If machines contribute to social intelligence, it will not be because they have learned how to think like us but because we have learned how to communicate with them. Esposito proposes that we think of “smart” machines not in terms of artificial intelligence but in terms of artificial communication. To do this, we need a concept of communication that can take into account the possibility that a communication partner may be not a human being but an algorithm—which is not random and is completely controlled, although not by the processes of the human mind. Esposito investigates this by examining the use of algorithms in different areas of social life. She explores the proliferation of lists (and lists of lists) online, explaining that the web works on the basis of lists to produce further lists; the use of visualization; digital profiling and algorithmic individualization, which personalize a mass medium with playlists and recommendations; and the implications of the “right to be forgotten.” Finally, she considers how photographs today seem to be used to escape the present rather than to preserve a memory.

Communication and artificial intelligence (AI) are closely related. It is communication – particularly interpersonal conversational interaction – that provides AI with its defining test case and experimental evidence. Likewise, recent developments in AI introduce new challenges and opportunities for communication studies. Technologies such as machine translation of human languages, spoken dialogue systems like Siri, algorithms capable of producing publishable journalistic content, and social robots are all designed to communicate with users in a human-like way. This timely and original textbook provides educators and students with a much-needed resource, connecting the dots between the science of AI and the discipline of communication studies. Clearly outlining the topic's scope, content and future, the text introduces key issues and debates, highlighting the importance and relevance of AI to communication studies. In lively and accessible prose, David Gunkel provides a new generation with the information, knowledge, and skills necessary to working and living in a world where social interaction is no longer restricted to humans. The first work of its kind, An Introduction to Communication and Artificial Intelligence is the go-to textbook for students and scholars getting to grips with this crucial interdisciplinary topic.

This cutting-edge resource offers practical overview of cognitive radio, a paradigm for wireless communications in which a network or a wireless node changes its transmission or reception parameters. The alteration of parameters is based on the active monitoring of several factors in the external and internal radio environment. This book offers a detailed description of cognitive radio and its individual parts. Practitioners learn how the basic processing elements and their capabilities are implemented as modular components. Moreover, the book explains how each component can be developed and tested independently, before integration with the rest of the engine. Practitioners discover how cognitive radio uses artificial intelligence to achieve radio optimization. The book also provides an in-depth working example of the developed cognitive engine and an experimental scenario to help engineers understand its performance and behavior.

This book presents various recent applications of Artificial Intelligence in Information and Communication Technologies such as Search and Optimization methods, Machine Learning, Data Representation and Ontologies, and Multi-agent Systems. The main aim of this book is to help Information and Communication Technologies (ICT) practitioners in managing efficiently their platforms using AI tools and methods and to provide them with sufficient Artificial Intelligence background to deal with real-life problems.

Despite increasing scholarly attention to artificial intelligence (AI), studies at the intersection of AI and communication remain ripe for exploration, including investigations of the social, political, cultural, and ethical aspects of machine intelligence, interactions among agents, and social artifacts. This book tackles these unexplored research areas with special emphasis on conditions, components, and consequences of cognitive, attitudinal, affective, and behavioural dimensions toward communication and AI. In doing so, this book epitomizes communication, journalism and media scholarship on AI and its social, political, cultural, and ethical perspectives. Topics vary widely from interactions between humans and robots through news representation of AI and AI-based news credibility to privacy and value toward AI in the public sphere. Contributors from such countries as Brazil, Netherland, South Korea, Spain, and United States discuss important issues and challenges in AI and communication studies. The collection of chapters in the book considers implications for not only theoretical and methodological approaches, but policymakers and practitioners alike. The chapters in this book were originally published as a special issue of Communication Studies.

Castel Ivano, originally built in 1375, is one of many beautiful and impressive castles strategically placed atop hills in Trentino's Valsugana in Northern Italy. It was in this castle on a series of brilliant sunny crisp November days in 1990 that an international group of computer scientists and cognitive scientists met at a workshop to discuss theoretical and applied issues concerning communi cation from an Artificial Intelligence and Cognitive Science perspective. About forty people, representing nine countries, participated in the workshop, either as speakers, discussants, or observers. The main motivationfor the workshop wasto address the questionofwhether and how current computational approaches to communication can or might be able to accommodate the range of complexities that characterize both human human and human-machine communication. The chapters in this book are based on the papers that were presented at the workshop. They are presented in an order that is determined primarily by the specificity of the topics they address. The initial chapters are more theoretical in nature with an emphasis on formal approaches to communication. The middle chapters focus on particular application issues, such as the generation ofmultimedia documents and the role of planning in building systems to support human-human or human-machine interaction. The final few chapters consider more general issues relating to com munication, such as the influence ofsocial structure on, and the role of affect in communication.

COMMUNICATION NETWORKS AND SERVICE MANAGEMENT IN THE ERA OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING Discover the impact that new technologies are having on communication systems with this up-to-date and one-stop resource Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning delivers a comprehensive overview of the impact of artificial intelligence (AI) and machine learning (ML) on service and network management. Beginning with a fulsome description of ML and AI, the book moves on to discuss management models, architectures, and frameworks. The authors also explore how AI and ML can be used in service management functions like the generation of workload profiles, service provisioning, and more. The book includes a handpicked selection of applications and case studies, as well as a treatment of emerging technologies the authors predict could have a significant impact on network and service management in the future. Statistical analysis and data mining are also discussed, particularly with respect to how they allow for an improvement of the management and security of IT systems and networks. Readers will also enjoy topics like: A thorough introduction to network and service management, machine learning, and artificial intelligence An exploration of artificial intelligence and machine learning for management models, including autonomic management, policy-based management, intent based ­management, and network virtualization-based management Discussions of AI and ML for architectures and frameworks, including cloud ­systems, software defined networks, 5G and 6G networks, and Edge/Fog networks An examination of AI and ML for service management, including the automatic ­generation of workload profiles using unsupervised learning Perfect for information and communications technology educators, Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning will also earn a place in the libraries of engineers and professionals who seek a structured reference on how the emergence of artificial intelligence and machine learning techniques is affecting service and network management.