A look at how new technologies can be put to use in the creation of a more just society. Artificial Intelligence (AI) is not likely to make humans redundant. Nor will it create superintelligence anytime soon. But it will make huge advances in the next two decades, revolutionize medicine, entertainment, and transport, transform jobs and markets, and vastly increase the amount of information that governments and companies have about individuals. AI for Good leads off with economist and best-selling author Daron Acemoglu, who argues that there are reasons to be concerned about these developments. AI research today pays too much attention to the technological hurtles ahead without enough attention to its disruptive effects on the fabric of society: displacing workers while failing to create new opportunities for them and threatening to undermine democratic governance itself. But the direction of AI development is not preordained. Acemoglu argues for its potential to create shared prosperity and bolster democratic freedoms. But directing it to that task will take great effort: It will require new funding and regulation, new norms and priorities for developers themselves, and regulations over new technologies and their applications. At the intersection of technology and economic justice, this book will bring together experts--economists, legal scholars, policy makers, and developers--to debate these challenges and consider what steps tech companies can do take to ensure the advancement of AI does not further diminish economic prospects of the most vulnerable groups of population.

Design is an important research topic in engineering and architecture, since design is not only a means of change but also one of the keystones of economic competitiveness and the fundamental precursor to manufacturing. However, our understanding of design as a process and our ability to model it are still very limited. The development of computational models founded on the artificial intelligence paradigm has provided an impetus for much of current design research -- both computational and cognitive. Notwithstanding their immaturity noticeable advances have been made both in extending our understanding of design and in developing tools based on that understanding. The papers in this volume are from the Third International Conference on Artificial Intelligence in Design held in August 1994 in Lausanne, Switzerland. They represent the cutting edge of research and development in this field. They are of particular interest to researchers, developers and users of computer systems in design. This volume demonstrates both the breadth and depth of artificial intelligence in design and points the way forward for our understanding of design as a process and for the development of computer-based tools to aid designers.

Recent evolutions, such as pervasive networking and other enabling technologies, have been increasingly changing human life, knowledge acquisition, and the way works are performed and students learn. In this societal change, educational institutions must maintain their leading role. They have therefore embraced digitally enhanced learning to provide increased flexibility and access for their students. The Handbook of Research on Redesigning Teaching, Learning, and Assessment in the Digital Era provides insights into the transformation of education in the digital era and responds to the needs of learners of any context and background through relevant studies that include sound pedagogical and content knowledge. Covering key topics such as hybrid learning, media, remote learning, and social media, this major reference work is ideal for administrators, policymakers, academicians, researchers, scholars, practitioners, librarians, instructors, and students.

This book offers readers a deeper understanding of the Cyberspace, of how institutions and industries are reinventing themselves, helping them excel in the transition to a fully digitally connected global economy. Though technology plays a key part in this regard, societal acceptance is the most important underlying condition, as it poses pressing challenges that cut across companies, developers, governments and workers. The book explores the challenges and opportunities involved, current and potential future concepts, critical reflections and best practices. It addresses connected societies, new opportunities for governments, the role of trust in digital networks, and future education networks. In turn, a number of representative case studies demonstrate the current state of development in practice.

This book introduces the reader to Artificial Intelligence and its importance to our future. Campbell uses behavioural psychology, explores technology, economics, real-life and historical examples to predict five future scenarios with AI. Illustrating through speculative fiction, she describes possible futures after AI exceeds human capabilities. We are at a tipping point in history and must plan to ensure a successful co-existence with artificial intelligence. This book explains how to design for a future with AI so that, rather than herald our downfall, it helps us achieve a new renaissance.

Early rules-based artificial intelligence demonstrated intriguing decision-making capabilities but lacked perception and didn't learn. AI today, primed with machine learning perception and deep reinforcement learning capabilities, can perform superhuman decision-making for specific tasks. This book shows you how to combine the practicality of early AI with deep learning capabilities and industrial control technologies to make robust decisions in the real world. Using concrete examples, minimal theory, and a proven architectural framework, author Kence Anderson demonstrates how to teach autonomous AI explicit skills and strategies. You'll learn when and how to use and combine various AI architecture design patterns, as well as how to design advanced AI without needing to manipulate neural networks or machine learning algorithms. Students, process operators, data scientists, machine learning algorithm experts, and engineers who own and manage industrial processes can use the methodology in this book to design autonomous AI. This book examines: Differences between and limitations of automated, autonomous, and human decision-making Unique advantages of autonomous AI for real-time decision-making, with use cases How to design an autonomous AI from modular components and document your designs

It is well-known that some 85% of the resources necessary to design and bring to market a product are committed by decisions taken in the first 10% of the design activity. This together with the wish to reduce further the time-to-market of high quality innovative products has increased the need for computer support at the conceptual design stage of the engineering design process life-style. This proceedings firmly focuses on the continuing research into new uses of Artificial Intelligence (AI) during the conceptual design process. It shows how novel applications of AI may be integrated with aspects of solid modelling, simulation optimisation and multiple criterion decision- making. A particular emphasis is placed on the use of AI methods in the overall design of products from major Civil Engineering structures to Consumer Electronics.