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.
"The landscape for education has been rapidly changing in the last years: demographic changes affecting the makeup of families, multiple school options available to children, wealth disparities, the global economy demanding new skills from workers, and continued breakthroughs in technology are some of the factors impacting education. Given these changes, how can schools continue to prepare students for the future? In a world where information is readily available online, how can schools continue to be relevant? The emergence of Artificial Intelligence (AI) has exacerbated the need to have these conversations. Its impact on education and the multiple possibilities that it offers are putting pressure on educational leaders to reformulate the school curriculum and the channels to deliver it. The book "Artificial Intelligence in Education, Promises and Implications for Teaching and Learning" by the Center for Curriculum Redesign immerses the reader in a discussion on what to teach students in the era of AI and examines how AI is already demanding much needed updates to the school curriculum, including modernizing its content, focusing on core concepts, and embedding interdisciplinary themes and competencies with the end goal of making learning more enjoyable and useful in students' lives. The second part of the book dives into the history of AI in education, its techniques and applications -including the way AI can help teachers be more effective, and finishes on a reflection about the social aspects of AI. This book is a must-read for educators and policy-makers who want to prepare schools to face the uncertainties of the future and keep them relevant." --Amada Torres, VP, Studies, Insights, and Research, National Association of Independent School (NAIS) "The rapid advances in technology in recent decades have already brought about substantial changes in education, opening up new opportunities to teach and learn anywhere anytime and providing new tools and methods to improve learning outcomes and support innovative teaching and learning.Research into artificial intelligence and machine learning in education goes back to the late 1970s. Artificial intelligence methods were generally employed in two ways: to design and facilitate interactive learning environments that would support learning by doing, and to design and implement tutoring systems by adapting instructions with respect to the students' knowledge state.But this is just the beginning. As Artificial Intelligence in Education shows, AI is increasingly used in education and learning contexts. The collision of three areas - data, computation and education - is set to have far-reaching consequences, raising fundamental questions about the nature of education: what is taught and how it is taught. Artificial Intelligence in Education is an important, if at times disturbing, contribution to the debate on AI and provides a detailed analysis on how it may affect the way teachers and students engage in education. The book describes how artificial intelligence may impact on curriculum design, on the individualisation of learning, and on assessment, offering some tantalising glimpses into the future (the end of exams, your very own lifelong learning companion) while not falling victim to tech-hype. The enormous ethical, technical and pedagogical challenges ahead are spelt out, and there is a real risk that the rapid advances in artificial intelligence products and services will outstrip education systems' capacity to understand, manage and integrate them appropriately. As the book concludes: "We can either leave it to others (the computer scientists, AI engineers and big tech companies) to decide how artificial intelligence in education unfolds, or we can engage in productive dialogue."I commend this book to anyone concerned with the future of education in a digital world." --Marc Durando, Executive Director, European Schoolnet
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.
"a provocative new book" — The New York Times AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value. Now with a new preface that explores how the coronavirus crisis compelled organizations such as Massachusetts General Hospital, Verizon, and IKEA to transform themselves with remarkable speed, Marco Iansiti and Karim R. Lakhani show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have restricted business growth for hundreds of years. From Airbnb to Ant Financial, Microsoft to Amazon, research shows how AI-driven processes are vastly more scalable than traditional processes, allow massive scope increase, enabling companies to straddle industry boundaries, and create powerful opportunities for learning—to drive ever more accurate, complex, and sophisticated predictions. When traditional operating constraints are removed, strategy becomes a whole new game, one whose rules and likely outcomes this book will make clear. Iansiti and Lakhani: Present a framework for rethinking business and operating models Explain how "collisions" between AI-driven/digital and traditional/analog firms are reshaping competition, altering the structure of our economy, and forcing traditional companies to rearchitect their operating models Explain the opportunities and risks created by digital firms Describe the new challenges and responsibilities for the leaders of both digital and traditional firms Packed with examples—including many from the most powerful and innovative global, AI-driven competitors—and based on research in hundreds of firms across many sectors, this is your essential guide for rethinking how your firm competes and operates in the era of AI.
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.
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 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."
One of Forbes's Top Ten Technology Books of the Year How to redesign ‘big, old’ companies for digital success—featuring a survey of 300+ business leaders and 30+ global organizations, including Amazon, Uber, LEGO, Toyota North America, Philips, and USAA. Most established companies have deployed such digital technologies as the cloud, mobile apps, the internet of things, and artificial intelligence. But few established companies are designed for digital. This book offers an essential guide for retooling organizations for digital success through 5 key building blocks: • Shared Customer Insights • Operational Backbone • Digital Platform • Accountability Framework • External Developer Platform In the digital economy, rapid pace of change in technology capabilities and customer desires means that business strategy must be fluid. As a result, business design has become a critical management responsibility. Effective business design enables a company to quickly pivot in response to new competitive threats and opportunities. Most leaders today, however, rely on organizational structure to implement strategy, unaware that structure inhibits, rather than enables, agility. In companies that are designed for digital, people, processes, data, and technology are synchronized to identify and deliver innovative customer solutions—and redefine strategy. Digital design, not strategy, is what separates winners from losers in the digital economy. Designed for Digital offers practical advice on digital transformation, with examples that include Amazon, BNY Mellon, DBS Bank, LEGO, Philips, Schneider Electric, USAA, and many other global organizations. Drawing on 5 years of research and in-depth case studies, the book is an essential guide for companies that want to disrupt rather than be disrupted in the new digital landscape.
Refactoring is gaining momentum amongst the object oriented programming community. It can transform the internal dynamics of applications and has the capacity to transform bad code into good code. This book offers an introduction to refactoring.
