Artificial intelligence (AI) is a transformative technology that holds promise for tremendous societal and economic benefit. AI has the potential to revolutionize how we live, work, learn, discover, and communicate. AI research can further our national priorities, including increased economic prosperity, improved educational opportunities and quality of life, and enhanced national and homeland security. Because of these potential benefits, the U.S. government has invested in AI research for many years. Yet, as with any significant technology in which the Federal government has interest, there are not only tremendous opportunities but also a number of considerations that must be taken into account in guiding the overall direction of Federally-funded R&D in AI. On May 3, 2016, the Administration announced the formation of a new NSTC Subcommittee on Machine Learning and Artificial intelligence, to help coordinate Federal activity in AI.1 This Subcommittee, on June 15, 2016, directed the Subcommittee on Networking and Information Technology Research and Development (NITRD) to create a National Artificial Intelligence Research and Development Strategic Plan. A NITRD Task Force on Artificial Intelligence was then formed to define the Federal strategic priorities for AI R&D, with particular attention on areas that industry is unlikely to address. This National Artificial Intelligence R&D Strategic Plan establishes a set of objectives for Federally-funded AI research, both research occurring within the government as well as Federally-funded research occurring outside of government, such as in academia. The ultimate goal of this research is to produce new AI knowledge and technologies that provide a range of positive benefits to society, while minimizing the negative impacts.

For any organization to be successful, it must operate in such a manner that knowledge and information, human resources, and technology are continually taken into consideration and managed effectively. Business concepts are always present regardless of the field or industry – in education, government, healthcare, not-for-profit, engineering, hospitality/tourism, among others. Maintaining organizational awareness and a strategic frame of mind is critical to meeting goals, gaining competitive advantage, and ultimately ensuring sustainability. The Encyclopedia of Organizational Knowledge, Administration, and Technology is an inaugural five-volume publication that offers 193 completely new and previously unpublished articles authored by leading experts on the latest concepts, issues, challenges, innovations, and opportunities covering all aspects of modern organizations. Moreover, it is comprised of content that highlights major breakthroughs, discoveries, and authoritative research results as they pertain to all aspects of organizational growth and development including methodologies that can help companies thrive and analytical tools that assess an organization’s internal health and performance. Insights are offered in key topics such as organizational structure, strategic leadership, information technology management, and business analytics, among others. The knowledge compiled in this publication is designed for entrepreneurs, managers, executives, investors, economic analysts, computer engineers, software programmers, human resource departments, and other industry professionals seeking to understand the latest tools to emerge from this field and who are looking to incorporate them in their practice. Additionally, academicians, researchers, and students in fields that include but are not limited to business, management science, organizational development, entrepreneurship, sociology, corporate psychology, computer science, and information technology will benefit from the research compiled within this publication.

In today's complex, dynamic competitive landscape, management of technology can mean the difference between success and failure. Managers and researchers alike need effective ways to conceptualize and develop technology strategies. Richard Goodman and Michael Lawless provide tools needed to integrate firms' technology capabilities with their competitive direction. Technology and Strategy presents models that help put technology and its market impacts into perspective. It addresses the broad questions of how technology and markets evolve, how technology can re-order the "rules" of competition, and how it can shift the balance of individual firms' competitive advantage. It also blends topics currently capturing attention in business circles--such as Total Quality Management and the resource-based view of the firm--into a clear view of technology management programs. Technology and Strategy also describes methods to develop specific strategies to cope with challenges facing executives--like evaluating promising, but untried, new technologies. Using actual case studies from the electronics and bio-tech industries, Goodman and Lawless demonstrate the use of new techniques to formulate strategy, including Technology Mapping and the Innovation Audit. Both were created to help executives choose the approach to technology best suited to their firms' particular capabilities. Offering clear, practical guidance through a complex, fast-changing world of competition, this new analysis of technology and strategy is a valuable guide for general managers, R&D and manufacturing managers, strategic planners, and academics.

Technology roadmapping is a significant method to help companies gain orientation concerning future challenges. This work contains a description of technology roadmapping in four major parts, providing expert knowledge on framing/embedding of technology roadmapping, processes of technology roadmapping, implementing technology roadmapping and linking technology roadmapping to other instruments of strategic planning. The book provides a comprehensive survey of technology roadmapping since it contains papers by leading European, American and Asian experts, provides orientation regarding different methods of technology roadmapping and their interconnections, supplies readers with a compilation of the most important submethods, and embeds and links technology roadmapping in the framework of management research. This book aims at becoming the leading compendium on technology roadmapping.

A primary objective of this document is to outline the key Big Data R&D strategies necessary to keep the Nation competitive in data science and innovation and to prepare for the data-intensive challenges of tomorrow. As a strategic plan, this document provides guidance for Federal agencies and policymakers in determining how to direct limited resources into activities that have the greatest potential to generate the greatest impact. The Plan profiles R&D areas that span multiple disciplines, surfacing intersections of common interest that could stimulate collaboration among researchers and technical experts in government, private industry, and academia. The Plan also offers ideas for decision makers to consider when deliberating about investments in Big Data in their respective domains. Additionally, this Plan is the Big Data SSG's response to Recommendation 11c of the 2015 review of NITRD by the President's Council of Advisors on Science and Technology (PCAST) to "coordinate a process to publish and publicly discuss periodically a research and coordination plan for its area of interest." The Plan is built around the following seven strategies that represent key areas of importance for Big Data research and development (R&D): Strategy 1: Create next-generation capabilities by leveraging emerging Big Data foundations, techniques, and technologies. Strategy 2: Support R&D to explore and understand trustworthiness of data and resulting knowledge, to make better decisions, enable breakthrough discoveries, and take confident action. Strategy 3: Build and enhance research cyberinfrastructure that enables Big Data innovation in support of agency missions. Strategy 4: Increase the value of data through policies that promote sharing and management of data. Strategy 5: Understand Big Data collection, sharing, and use with regard to privacy, security, and ethics. Strategy 6: Improve the national landscape for Big Data education and training to fulfill increasing demand for both deep analytical talent and analytical capacity for the broader workforce. Strategy 7: Create and enhance connections in the national Big Data innovation ecosystem.