Books  |  ,   |  September 21, 2016

Social Machines: The Coming Collision of Artificial Intelligence, Social Networking, and Humanity

By James Hendler and Alice M. Mulvehill.
Published by Apress.
174 pages.

Will your next doctor be a human being―or a machine? Will you have a choice? If you do, what should you know before making it? This book introduces the reader to the pitfalls and promises of artificial intelligence (AI) in its modern incarnation and the growing trend of systems to “reach off the Web” into the real world. The convergence of AI, social networking, and modern computing is creating an historic inflection point in the partnership between human beings and machines with potentially profound impacts on the future not only of computing but of our world and species.

AI experts and researchers James Hendler―co-originator of the Semantic Web (Web 3.0)―and Alice Mulvehill―developer of AI-based operational systems for DARPA, the Air Force, and NASA―explore the social implications of AI systems in the context of a close examination of the technologies that make them possible. The authors critically evaluate the utopian claims and dystopian counterclaims of AI prognosticators.

Social Machines: The Coming Collision of Artificial Intelligence, Social Networking, and Humanity is your richly illustrated field guide to the future of your machine-mediated relationships with other human beings and with increasingly intelligent machines.

What Readers Will Learn

  • What the concept of a social machine is and how the activities of non-programmers are contributing to machine intelligence
  • How modern artificial intelligence technologies, such as Watson, are evolving and how they process knowledge from both carefully produced information (such as Wikipedia and journal articles) and from big data collections
  • The fundamentals of neuromorphic computing, knowledge graph search, and linked data, as well as the basic technology concepts that underlie networking applications such as Facebook and Twitter
  • How the change in attitudes towards cooperative work on the Web, especially in the younger demographic, is critical to the future of Web applications

Who This Book Is For
General readers and technically engaged developers, entrepreneurs, and technologists interested in the threats and promises of the accelerating convergence of artificial intelligence with social networks and mobile web technologies.

Table of Contents

  1. Introduction: Why This Book?
  2. Who Will Be Your Next Doctor?
  3. The Games We Play
  4. The Limits of Humans
  5. What Computers Can’t Do–Yet
  6. Augmenting Human Capabilities with AI
  7. Social Machines: Embracing the Blur
  8. Social Challenges for the Social Machine
  9. Conclusion: Social Machines and the New Future

About the Authors

James Hendler is the Director of the Institute for Data Exploration and Applications and the Tetherless World Professor of Computer, Web and Cognitive Sciences at RPI. Hendler has authored numerous books, technical papers and articles in the areas including the Semantic Web, artificial intelligence, agent-based computing and high performance processing. An early researcher in the Semantic Web area, he is a former member of the US Air Force Science Advisory Board, and is a Fellow of the AAAI, the BCS, the IEEE and the AAAS. He is also the former Chief Scientist of the Information Systems Office at the US Defense Advanced Research Projects Agency (DARPA) and was awarded a US Air Force Exceptional Civilian Service Medal in 2002.

Alice M. Mulvehill is a research scientist and provides consulting through her company, Memory Based Research, LLC. She was previously a lead scientist at Raytheon/BBN Technologies where she led the development of several advanced decision support systems for the Air Force and DARPA. She was a participant in the DARPA/Rome Lab Planning Initiative and participated in the development of operationally-oriented AI-based systems for DARPA, the Air Force, and NASA.  She has authored or co-authored numerous technical papers in the areas of knowledge acquisition and representation, model development and adaptation; case-based reasoning; semantic web technology; and applications of these technologies to support logistics, planning and prediction.