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Innovation in INFORMATION TECHNOLOGY 2 Excerpts from Earlier CSTB Reports This section contains excerpts from three CSTB reports: Making IT Better: Expanding Information Technology Research to Meet Society's Needs (2000), Funding a Revolution: Government Support for Computing Research (1999), and Evolving the High Performance Computing and Communications Initiative to Support the Nation's Information Infrastructure (1995). While this synthesis report is based on all the CSTB reports listed in Box 1 in the “Summary and Recommendations,” the excerpts from these three reports are the most general and broad. To keep this report to a reasonable length, nothing was excerpted from the other five reports. Readers are encouraged to read all eight reports, which can be found online at <http://www.nap.edu>. For the sake of simplicity and organizational clarity, footnotes and reference citations appearing in the original texts have been omitted from the reprinted material that follows. A bar in the margins beside the excerpted material is used to indicate that it is extracted text. Section heads show the topics addressed.
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Innovation in INFORMATION TECHNOLOGY MAKING IT BETTER: EXPANDING INFORMATION TECHNOLOGY RESEARCH TO MEET SOCIETY'S NEEDS (2000) CITATION: Computer Science and Telecommunications Board (CSTB), National Research Council. 2000. Making IT Better: Expanding Information Technology Research to Meet Society's Needs. National Academy Press, Washington, D.C. The Many Faces of Information Technology Research (From pp. 23-26): IT research takes many forms. It consists of both theoretical and experimental work, and it combines elements of science and engineering. Some IT research lays out principles or constraints that apply to all computing and communications systems; examples include theorems that show the limitations of computation (what can and cannot be computed by a digital computer within a reasonable time) or the fundamental limits on capacities of communications channels. Other research investigates different classes of IT systems, such as user interfaces, the Web, or electronic mail (e-mail). Still other research deals with issues of broad applicability driven by specific needs. For example, today's high-level programming languages (such as Java and C) were made possible by research that uncovered techniques for converting the high-level state-ments into machine code for execution on a computer. The design of the languages themselves is a research topic: how best to capture a programmer's intentions in a way that can be converted to efficient machine code. Efforts to solve this problem, as is often the case in IT research, will require invention and design as well as the classical scientific techniques of analysis and measurement. The same is true of efforts to develop specific and practical modulation and coding algorithms that approach the fundamental limits of communication on some channels. The rise of digital communication, associated with computer technology, has led to the irreversible melding of what were once the separate fields of communications and computers, with data forming an increasing share of what is being transmitted over the digitally modulated fiber-optic cables spanning the nation and the world. Experimental work plays an important role in IT research. One modality of research is the design experiment, in which a new technique is proposed, a provisional design is posited, and a research prototype is built in order to evaluate the strengths and weaknesses of the design. Although much of the effect of a design can be anticipated using analytic techniques, many of its subtle aspects are uncovered only when the prototype is studied. Some of the most important strides in IT have been made through such experimental research. Time-sharing, for example, evolved
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Innovation in INFORMATION TECHNOLOGY in a series of experimental systems that explored different parts of the technology. How are a computer's resources to be shared among several customers? How do we ensure equitable sharing of resources? How do we insulate each user's program from the programs of others? What resources should be shared as a convenience to the customers (e.g., computer files)? How can the system be designed so it's easy to write computer programs that can be time-shared? What kinds of commands does a user need to learn to operate the system? Although some of these trade-offs may succumb to analysis, others—notably those involving the user's evaluation and preferences—can be evaluated only through experiment. Ideas for IT research can be gleaned both from the research community itself and from applications of IT systems. The Web, initiated by physicists to support collaboration among researchers, illustrates how people who use IT can be the source of important innovations. The Web was not invented from scratch; rather, it integrated developments in information retrieval, networking, and software that had been accumulating over decades in many segments of the IT research community. It also reflects a fundamental body of technology that is conducive to innovation and change. Thus, it advanced the integration of computing, communications, and information. The Web also embodies the need for additional science and technology to accommodate the burgeoning scale and diversity of IT users and uses: it became a catalyst for the Internet by enhancing the ease of use and usefulness of the Internet, it has grown and evolved far beyond the expectations of its inventors, and it has stimulated new lines of research aimed at improving and better using the Internet in numerous arenas, from education to crisis management. Progress in IT can come from research in many different disciplines. For example, work on the physics of silicon can be considered IT research if it is driven by problems related to computer chips; the work of electrical engineers is considered IT research if it focuses on communications or semiconductor devices; anthropologists and other social scientists studying the uses of new technology can be doing IT research if their work informs the development and deployment of new IT applications; and computer scientists and computer engineers address a widening range of issues, from generating fundamental principles for the behavior of information in systems to developing new concepts for systems. Thus, IT research combines science and engineering, even though the popular—and even professional—association of IT with systems leads many people to concentrate on the engineering aspects. Fine distinctions between the science and engineering aspects may be unproductive: computer science is special because of how it combines the two, and the evolution of both is key to the well-being of IT research.
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Innovation in INFORMATION TECHNOLOGY Implications for the Research Enterprise (From pp. 42-43): The trends in IT suggest that the nation needs to reinvent IT research and develop new structures to support, conduct, and manage it. . . . As IT permeates many more real-world applications, additional constituencies need to be brought into the research process as both funders and performers of IT research. This is necessary not only to broaden the funding base to include those who directly benefit from the fruits of the research, but also to obtain input and guidance. An understanding of business practices and processes is needed to support the evolution of e-commerce; insight from the social sciences is needed to build IT systems that are truly user-friendly and that help people work better together. No one truly understands where new applications such as e-commerce, electronic publishing, or electronic collaboration are headed, but business development and research together can promote their arrival at desirable destinations. Many challenges will require the participation and insight of the end user and the service provider communities. They have a large stake in seeing these problems addressed, and they stand to benefit most directly from the solutions. Similarly, systems integrators would benefit from an improved understanding of systems and applications because they would become more competitive in the marketplace and be better able to meet their estimates of project cost and time. Unlike vendors of component technologies, systems integrators and end users deal with entire information systems and therefore have unique perspectives on the problems encountered in developing systems and the feasibility of proposed solutions. Many of the end-user organizations, however, have no tradition of conducting IT research—or technological research of any kind, in fact— and they are not necessarily capable of doing so effectively; they depend on vendors for their technology. Even so, their involvement in the research process is critical. Vendors of equipment and software have neither the requisite experience and expertise nor the financial incentives to invest heavily in research on the challenges facing end-user organizations, especially the challenges associated with the social applications of IT. Of course, they listen to their customers as they refine their products and strategies, but those interactions are superficial compared with the demands of the new systems and applications. Finding suitable mechanisms for the participation of end users and service providers, and engaging them productively, will be a big challenge for the future of IT research. Past attempts at public-private partnerships, as in the emerging arena of critical infrastructure protection, show it is not so easy to get the public
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Innovation in INFORMATION TECHNOLOGY and private sectors to interact for the purpose of improving the research base and implementation of systems: the federal government has a responsibility to address the public interest in critical infrastructure, whereas the private sector owns and develops that infrastructure, and conflicting objectives and time horizons have confounded joint exploration. As a user of IT, the government could play an important role. Whereas historically it had limited and often separate programs to support research and acquire systems for its own use, the government is now becoming a consumer of IT on a very large scale. Just as IT and the widespread access to it provided by the Web have enabled businesses to reinvent themselves, IT could dramatically improve operations and reduce the costs of applications in public health, air traffic control, and social security; government agencies, like private-sector organizations, are turning increasingly to commercial, off-the-shelf technology. Universities will play a critical role in expanding the IT research agenda. The university setting continues to be the most hospitable for higher-risk research projects in which the outcomes are very uncertain. Universities can play an important role in establishing new research programs for large-scale systems and social applications, assuming that they can overcome long-standing institutional and cultural barriers to the needed cross-disciplinary research. Preserving the university as a base for research and the education that goes with it would ensure a workforce capable of designing, developing, and operating increasingly sophisticated IT systems. A booming IT marketplace and the lure of large salaries in industry heighten the impact of federal funding decisions on the individual decisions that shape the university environment: as the key funders of university research, federal programs send important signals to faculty and students. The current concerns in IT differ from the competitiveness concerns of the 1980s: the all-pervasiveness of IT in everyday life raises new questions of how to get from here to there—how to realize the exciting possibilities, not merely how to get there first. A vital and relevant IT research program is more important than ever, given the complexity of the issues at hand and the need to provide solid underpinnings for the rapidly changing IT marketplace. (From p. 93): Several underlying trends could ultimately limit the nation's innovative capacity and hinder its ability to deploy the kinds of IT systems that could best meet personal, business, and government needs. First, expenditures on research by companies that develop IT goods and services and by the federal government have not kept pace with the expanding array of IT. The disincentives to long-term, fundamental research have become more numerous, especially in the private sector,
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Innovation in INFORMATION TECHNOLOGY which seems more able to lure talent from universities than the other way around. Second, and perhaps most significantly, IT research investments continue to be directed at improving the performance of IT components, with limited attention to systems issues and application-driven needs. Neither industry nor academia has kept pace with the problems posed by the large-scale IT systems used in a range of social and business contexts—problems that require fundamental research. . . . New mechanisms may be needed to direct resources to these growing problem areas. (From pp. 6-9): Neither large-scale systems nor social applications of IT are adequately addressed by the IT research community today. Most IT research is directed toward the components of IT systems: the microprocessors, computers, and networking technologies that are assembled into large systems, as well as the software that enables the components to work together. This research nurtures the essence of IT, and continued work is needed in all these areas. But component research needs to be viewed as part of a much larger portfolio, in which it is complemented by research aimed directly at improving large-scale systems and the social applications of IT. The last of these includes some work (such as computer-supported cooperative work and human-computer interaction) traditionally viewed as within the purview of computer science. Research in all three areas—components, systems, and social applications—will make IT systems better able to meet society's needs, just as in the medical domain work is needed in biology, physiology, clinical medicine, and epidemiology to make the nation 's population healthier. Research on large-scale systems and the social applications of IT will require new modes of funding and performing research that can bring together a broad set of IT researchers, end users, system integrators, and social scientists to enhance the understanding of operational systems. Research in these areas demands that researchers have access to operational large-scale systems or to testbeds that can mimic the performance of much larger systems. It requires additional funding to support sizable projects that allow multiple investigators to experiment with large IT systems and develop suitable testbeds and simulations for evaluating new approaches and that engage an unusually diverse range of parties. Research by individual investigators will not, by itself, suffice to make progress on these difficult problems. Today, most IT research fails to incorporate the diversity of perspectives needed to ensure advances on large-scale systems and social applications. Within industry, it is conducted largely by vendors of IT components: companies like IBM, Microsoft, and Lucent Technologies. Few of the companies that are engaged in providing IT services, in integrating large-scale systems (e.g., Andersen Consulting [now Accenture], EDS, or
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Innovation in INFORMATION TECHNOLOGY Lockheed Martin), or in developing enterprise software (e.g., Oracle, SAP, PeopleSoft) have significant research programs. Nor do end-user organizations (e.g., users in banking, commerce, education, health care, and manufacturing) tend to support research on IT, despite their increasing reliance on IT and their stake in the way IT systems are molded. Likewise, there is little academic research on large-scale systems or social applications. Within the IT sector, systems research has tended to focus on improving the performance and lowering the costs of IT systems rather than on improving their reliability, flexibility, or scalability (although systems research is slated to receive more attention in new funding programs). Social applications present an even greater opportunity and have the potential to leverage research in human-computer interaction, using it to better understand how IT can support the work of individuals, groups, and organizations. Success in this area hinges on interdisciplinary research, which is already being carried out on a small scale. One reason more work has not been undertaken in these areas is lack of sufficient funding. More fundamentally, the problems evident today did not reach critical proportions until recently. . . . From a practical perspective, conducting the types of research advocated here is difficult. Significant cultural gaps exist between researchers in different disciplines and between IT researchers and the end users of IT systems.
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Innovation in INFORMATION TECHNOLOGY FUNDING A REVOLUTION: GOVERNMENT SUPPORT FOR COMPUTING RESEARCH (1999) CITATION: Computer Science and Telecommunications Board (CSTB), National Research Council. 1999. Funding a Revolution: Government Support for Computing Research. National Academy Press, Washington, D.C. (From p. 1): The computer revolution is not simply a technical change; it is a sociotechnical revolution comparable to an industrial revolution. The British Industrial Revolution of the late 18th century not only brought with it steam and factories, but also ushered in a modern era characterized by the rise of industrial cities, a politically powerful urban middle class, and a new working class. So, too, the sociotechnical aspects of the computer revolution are now becoming clear. Millions of workers are flocking to computing-related industries. Firms producing microprocessors and software are challenging the economic power of firms manufacturing automobiles and producing oil. Detroit is no longer the symbolic center of the U.S. industrial empire; Silicon Valley now conjures up visions of enormous entrepreneurial vigor. Men in boardrooms and gray flannel suits are giving way to the casually dressed young founders of start-up computer and Internet companies. Many of these entrepreneurs had their early hands-on computer experience as graduate students conducting federally funded university research. As the computer revolution continues and private companies increasingly fund innovative activities, the federal government continues to play a major role, especially by funding research. Given the successful history of federal involvement, several questions arise: Are there lessons to be drawn from past successes that can inform future policy making in this area? What future roles might the government play in sustaining the information revolution and helping to initiate other technological developments? Lessons from History (From pp. 5-13): Why has federal support been so effective in stimulating innovation in computing? Although much has depended on the unique characteristics of individual research programs and their participants, several common factors have played an important part. Primary among them is that federal support for research has tended to complement, rather than preempt, industry investments in research. Effective federal research has concentrated on work that industry has limited incentive to pursue: long-term, fundamental research; large system-building efforts that require the talents of diverse communities of scientists and engi-
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Innovation in INFORMATION TECHNOLOGY neers; and work that might displace existing, entrenched technologies. Furthermore, successful federal programs have tended to be organized in ways that accommodate the uncertainties in scientific and technological research. Support for computing research has come from a diversity of funding agencies; program managers have formulated projects broadly where possible, modifying them in response to preliminary results; and projects have fostered productive collaboration between universities and industry. The lessons below expand on these factors. The first three lessons address the complementary nature of government- and industry-sponsored research; the final four highlight elements of the organizational structure and management of effective federally funded research programs. . . . 1. Government supports long-range, fundamental research that industry cannot sustain. Federally funded programs have been successful in supporting long-term research into fundamental aspects of computing, such as computer graphics and artificial intelligence, whose practical benefits often take years to demonstrate. Work on speech recognition, for example, which was begun in the early 1970s (some started even earlier), took until 1997 to generate a successful product for enabling personal computers to recognize continuous speech. Similarly, fundamental algorithms for shading three-dimensional graphics images, which were developed with defense funding in the 1960s, entered consumer products only in the 1990s, though they were available in higher-performance machines much earlier. These algorithms are now used in a range of products in the health care, entertainment, and defense industries. Industry does fund some long-range work, but the benefits of fundamental research are generally too distant and too uncertain to receive significant industry support. Moreover, the results of such work are generally so broad that it is difficult for any one firm to capture them for its own benefit and also prevent competitors from doing so. . . . Not surprisingly, companies that have tended to support the most fundamental research have been those, like AT&T Corporation and IBM Corporation, that are large and have enjoyed a dominant position in their respective markets. As the computing industry has become more competitive, even these firms have begun to link their research more closely with corporate objectives and product development activities. Companies that have become more dominant, such as Microsoft Corporation and Intel Corporation, have increased their support for fundamental research.
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Innovation in INFORMATION TECHNOLOGY 2. Government supports large system-building efforts that have advanced technology and created large communities of researchers. In addition to funding long-term fundamental research, federal programs have been effective in supporting the construction of large systems that have both motivated research and demonstrated the feasibility of new technological approaches. The Defense Advanced Research Projects Agency's (DARPA's) decision to construct a packet-switched network (called the ARPANET) to link computers at its many contractor sites prompted considerable research on networking protocols and the design of packet switches and routers. It also led to the development of structures for managing large networks, such as the domain name system, and development of useful applications, such as e-mail. Moreover, by constructing a successful system, DARPA demonstrated the value of large-scale packet-switched networks, motivating subsequent deployment of other networks, like the National Science Foundation's NSFnet, which formed the basis of the Internet. Efforts to build large systems demonstrate that, especially in computing, innovation does not flow simply and directly from research, through development, to deployment. Development often precedes research, and research rationalizes, or explains, technology developed earlier through experimentation. Hence attempts to build large systems can identify new problems that need to be solved. Electronic telecommunications systems were in use long before Claude Shannon developed modern communications theory in the late 1940s, and the engineers who developed the first packet switches for routing messages through the ARPANET advanced empirically beyond theory. Building large systems generated questions for research, and the answers, in turn, facilitated more development. Much of the success of major system-building efforts derives from their ability to bring together large groups of researchers from academia and industry who develop a common vocabulary, share ideas, and create a critical mass of people who subsequently extend the technology. Examples include the ARPANET and the development of the Air Force's Semi-Automatic Ground Environment (SAGE) project in the 1950s. Involving researchers from MIT, IBM, and other research laboratories, the SAGE project sparked innovations ranging from real-time computing to core memories that found widespread acceptance throughout the computer industry. Many of the pioneers in computing learned through hands-on experimentation with SAGE in the 1950s and early 1960s. They subsequently staffed the companies and laboratories of the nascent computing and communications revolution. The impact of SAGE was felt over the course of several decades.
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Innovation in INFORMATION TECHNOLOGY 3. Federal research funding has expanded on earlier industrial research. In several cases, federal research funding has been important in advancing a technology to the point of commercialization after it was first explored in an industrial research laboratory. For example, IBM pioneered the concept of relational databases but did not commercialize the technology because of its perceived potential to compete with more-established IBM products. National Science Foundation (NSF)-sponsored research at UC-Berkeley allowed continued exploration of this concept and brought the technology to the point that it could be commercialized by several start-up companies—and more-established database companies (including IBM). This pattern was also evident in the development of reduced instruction set computing (RISC). Though developed at IBM, RISC was not commercialized until DARPA funded additional research at UC-Berkeley and Stanford University as part of its Very Large Scale Integrated Circuit (VLSI) program of the late 1970s and early 1980s. A variety of companies subsequently brought RISC-based products to the marketplace, including IBM, the Hewlett-Packard Company, the newly formed Sun Microsystems, Inc., and another start-up, MIPS Computer Systems. For both relational databases and VLSI, federal funding helped create a community of researchers who validated and improved on the initial work. They rapidly diffused the technology throughout the community, leading to greater competition and more rapid commercialization. 4. Computing research has benefited from diverse sources of government support. Research in computing has been supported by multiple federal agencies, including the Department of Defense (DOD)—most notably the Defense Advanced Research Projects Agency and the military services—the National Science Foundation, National Aeronautics and Space Administration (NASA), Department of Energy (DOE), and National Institutes of Health (NIH). Each has its own mission and means of supporting research. DARPA has tended to concentrate large research grants in so-called centers of excellence, many of which over time have matured into some of the country's leading academic computer departments. The Office of Naval Research (ONR) and NSF, in contrast, have supported individual researchers at a more diverse set of institutions. They have awarded numerous peer-review grants to individual researchers, especially in universities. NSF has also been active in supporting educational and research needs more broadly, awarding graduate student fellowships and providing funding for research equipment and infrastructure. Each of these organizations employs a different set of mechanisms to support research,
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Innovation in INFORMATION TECHNOLOGY The Changing Federal Role (From pp. 98-107): The forces driving government support changed during the 1960s. The Cold War remained a paramount concern, but to it were added the difficult conflict in Vietnam, the Great Society programs, and the Apollo program, inaugurated by President Kennedy 's 1961 challenge. New political goals, new technologies, and new missions provoked changes in the federal agency population. Among these, two agencies became particularly important in computing: the new Advanced Research Projects Agency and the National Science Foundation. The Advanced Research Projects Agency The founding of the Advanced Research Projects Agency (ARPA) in 1958, a direct outgrowth of the Sputnik scare, had immeasurable impact on computing and communications. ARPA, specifically charged with preventing technological surprises like Sputnik, began conducting long-range, high-risk research. It was originally conceived as the DOD's own space agency, reporting directly to the Secretary of Defense in order to avoid interservice rivalry. Space, like computing, did not seem to fit into the existing military service structure. ARPA 's independent status not only insulated it from established service interests but also tended to foster radical ideas and keep the agency tuned to basic research questions: when the agency-supported work became too much like systems development, it ran the risk of treading on the territory of a specific service. ARPA's status as the DOD space agency did not last long. Soon after NASA 's creation in 1958, ARPA retained essentially no role as a space agency. ARPA instead focused its energies on ballistic missile defense, nuclear test detection, propellants, and materials. It also established a critical organizational infrastructure and management style: a small, high-quality managerial staff, supported by scientists and engineers on rotation from industry and academia, successfully employing existing DOD laboratories and contracting procedures (rather than creating its own research facilities) to build solid programs in new, complex fields. ARPA also emerged as an agency extremely sensitive to the personality and vision of its director. ARPA's decline as a space agency raised questions about its role and character. A new director, Jack Ruina, answered the questions in no uncertain terms by cementing the agency's reputation as an elite, scientifically respected institution devoted to basic, long-term research projects. Ruina, ARPA's first scientist-director, took office at the same time as Kennedy and McNamara in 1961, and brought a similar spirit to the
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Innovation in INFORMATION TECHNOLOGY agency. Ruina decentralized management at ARPA and began the tradition of relying heavily on independent office directors and program managers to run research programs. Ruina also valued scientific and technical merit above immediate relevance to the military. Ruina believed both of these characteristics—independence and intellectual quality—were critical to attracting the best people, both to ARPA as an organization and to ARPA-sponsored research. Interestingly, ARPA's managerial success did not rely on innovative managerial techniques per se (such as the computerized project scheduling typical of the Navy's Polaris project) but rather on the creative use of existing mechanisms such as “no-year money,” unsolicited proposals, sole-source procurement, and multiyear forward funding. ARPA and Information Technology. From the point of view of computing, the most important event at ARPA in the early 1960s, indeed in all of ARPA's history, was the establishment of the Information Processing Techniques Office, IPTO, in 1962. The impetus for this move came from several directions, including Kennedy's call a year earlier for improvements in command-and-control systems to make them “more flexible, more selective, more deliberate, better protected, and under ultimate civilian authority at all times. ” Computing as applied to command and control was the ideal ARPA program—it had no clearly established service affinity; it was “a new area with relatively little established service interest and entailed far less constraint on ARPA's freedom of action,” than more familiar technologies. Ruina established IPTO to be devoted not to command and control but to the more fundamental problems in computing that would, eventually, contribute solutions. Consistent with his philosophy of strong, independent, and scientific office managers, Ruina appointed J.C.R. Licklider to head IPTO. The Harvard-trained psychologist came to ARPA in October 1962, primarily to run its Command and Control Group. Licklider split that group into two discipline-oriented offices: Behavioral Sciences Office and IPTO. Licklider had had extensive exposure to the computer research of the time and had clearly defined his own vision of “man-computer symbiosis,” which he had published in a landmark paper of 1960 by the same name. He saw human-computer interaction as the key, not only to command and control, but also to bringing together the then-disparate techniques of electronic computing to form a unified science of computers as tools for augmenting human thought and creativity. Licklider formed IPTO in this image, working largely independently of any direction from Ruina, who spent the majority of his time on higher-profile and higher-funded missile defense issues. Licklider's timing was opportune: the 1950s had produced a stable technology of digital computer hardware, and the big systems
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Innovation in INFORMATION TECHNOLOGY projects had shown that programming these machines was a difficult but interesting problem in its own right. Now the pertinent questions concerned how to use “this tremendous power . . . for other than purely numerical scientific calculations.” Licklider not only brought this vision to IPTO itself, but he also promoted it with missionary zeal to the research community at large. Licklider's and IPTO's success derived in large part from their skills at “selling the vision” in addition to “buying the research.” Another remarkable feature of IPTO, particularly during the 1960s, was its ability to maintain the coherent vision over a long period of time; the office director was able to handpick his successor. Licklider chose Ivan Sutherland, a dynamic young researcher he had encountered as a graduate student at MIT and the Lincoln Laboratory, to succeed him in 1964. Sutherland carried on Licklider's basic ideas and made his own impact by emphasizing computer graphics. Sutherland 's own successor, Robert Taylor, came in 1966 from a job as a program officer at NASA and recalled, “I became heartily subscribed to the Licklider vision of interactive computing.” While at IPTO, Taylor emphasized networking. The last IPTO director of the 1960s, Lawrence Roberts, came, like Sutherland, from MIT and Lincoln Laboratory, where he had worked on the early transistorized computers and had conducted ARPA research in both graphics and communications. During the 1960s, ARPA and IPTO had more effect on the science and technology of computing than any other single government agency, sometimes raising concern that the research agenda for computing was being directed by military needs. IPTO's sheer size, $15 million in 1965, dwarfed other agencies such as ONR. Still, it is important to note, ONR and ARPA worked closely together; ONR would often let small contracts to researchers and serve as a talent agent for ARPA, which would then fund promising projects at larger scale. ARPA combined the best features of existing military research support with a new, lean administrative structure and innovative management style to fund high-risk projects consistently. The agency had the freedom to administer large block grants as well as multiple-year contracts, allowing it the luxury of a long-term vision to foster technologies, disciplines, and institutions. Further, the national defense motivation allowed IPTO to concentrate its resources on centers of scientific and engineering excellence (such as MIT, Carnegie Mellon University, and Stanford University) without regard for geographical distribution questions with which NSF had to be concerned. Such an approach helped to create university-based research groups with the critical mass and stability of funding needed to create significant advances in particular technical areas. But although it trained generations of young researchers in those areas, ARPA's funding style did little to help them pursue the
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Innovation in INFORMATION TECHNOLOGY same lines of work at other universities. As an indirect and possibly unintended consequence, the research approaches and tools and the generic technologies developed under ARPA's patronage were disseminated more rapidly and widely, and so came to be applied in new nonmilitary contexts by the young M.S. and Ph.D. graduates who had been trained in that environment but could not expect to make their research careers within it. ARPA's Management Style. To evaluate research proposals, IPTO did not employ the peer-review process like NSF, but rather relied on internal reviews and the discretion of program managers as did ONR. These program managers, working under office managers such as Licklider, Sutherland, Taylor, and Roberts, came to have enormous influence over their areas of responsibility and became familiar with the entire field both personally and intellectually. They had the freedom and the resources to shape multiple R&D contracts into a larger vision and to stimulate new areas of inquiry. The education, recruiting, and responsibilities of these program managers thus became a critical parameter in the character and success of ARPA programs. ARPA frequently chose people who had training and research experience in the fields they would fund, and thus who had insight and opinions on where those fields should go. To have such effects, the program managers were given enough funds to let a large enough number of contracts and to shape a coherent research program, with minimal responsibilities for managing staffs. Program budgets usually required only two levels of approval above the program manager: the director of IPTO and the director of ARPA. One IPTO member described what he called “the joy of ARPA. . . . You know, if a program manager has a good idea, he has got two people to convince that that is a good idea before the guy goes to work. He has got the director of his office and the director of ARPA, and that is it. It is such a short chain of command.” Part of ARPA's philosophy involved aiming at radical change rather than incremental improvement. As Robert Taylor put it, for example, incremental innovation would be taken care of by the services and their contractors, but, ARPA's aim was “an order of magnitude difference.” ARPA identified good ideas and magnified them. This strategy often necessitated funding large, group-oriented projects and institutions rather than individuals. Taylor recalled, “I don't remember a single case where we ever funded a single individual's work. . . . The individual researcher who is just looking for support for his own individual work could [potentially] find many homes to support that work. So we tended not to fund those, because we felt that they were already pretty well covered. Instead, we funded larger groups—teams.” NSF's peer-review process worked
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Innovation in INFORMATION TECHNOLOGY well for individual projects, but was not likely to support large, team-oriented research projects. Nor did it, at this point in history, support entire institutions and research centers, like the Laboratory for Computer Science at MIT. IPTO's style meshed with its emphasis on human-machine interaction, which it saw as fundamentally a systems problem and hence fundamentally team oriented. In Taylor's view, the university reward structure was much more oriented toward individual projects, so “systems research is most difficult to fund and manage in a university.” This philosophy was apparent in ARPA's support of Project MAC, an MIT-led effort on time-shared computing. . . . ARPA, with its clearly defined mission to support DOD technology, could also afford to be elitist in a way that NSF, with a broader charter to support the country's scientific research, could not. “ARPA had no commitment, for example, to take geography into consideration when it funded work.” Another important feature of ARPA's multiyear contracts was their stability, which proved critical for graduate students who could rely on funding to get them through their Ph.D. program. ARPA also paid particular attention to building communities of researchers and disseminating the results of its research, even beyond traditional publications. IPTO would hold annual meetings for its contract researchers at which results would be presented and debated. These meetings proved effective not only at advancing the research itself but also at providing valuable feedback for the program managers and helping to forge relationships between researchers in related areas. Similar conferences were convened for graduate students only, thus building a longer-term community of researchers. ARPA also put significant effort into getting the results of its research programs commercialized so that DOD could benefit from the development and expansion of a commercial industry for information technology. ARPA sponsored conferences that brought together researchers and managers from academia and industry on topics such as timesharing, for example. Much has been made of ARPA's management style, but it would be a mistake to conclude that management per se provided the keys to the agency's successes in computing. The key point about the style, in fact, was its light touch. Red tape was kept to a minimum, and project proposals were turned around quickly, frequently into multiple-year contracts. Typical DOD research contracts involved close monitoring and careful adherence to requirements and specifications. ARPA avoided this approach by hiring technically educated program managers who had continuing research interests in the fields they were managing. This reality counters the myth that government bureaucrats heavy-handedly selected R&D problems and managed the grants and contracts. Especially during the 1960s and 1970s, program managers and office directors were not
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Innovation in INFORMATION TECHNOLOGY bureaucrats but were usually academics on a 2-year tour of duty. They saw ARPA as a pulpit from which to preach their visions, with money to help them realize those visions. The entire system displayed something of a self-organizing, self-managing nature. As Ivan Sutherland recalled, “Good research comes from the researchers themselves rather than from the outside.” National Science Foundation While ARPA was focusing on large projects and systems, the National Science Foundation played a large role in legitimizing basic computer science research as an academic discipline and in funding individual researchers at a wide range of institutions. Its programs in computing have evolved considerably since its founding in 1950, but have tended to balance support for research, education, and computing infrastructure. Although early programs tended to focus on the use of computing in other academic disciplines, NSF subsequently emerged as the leading federal funder of basic research in computer science. NSF was formed before computing became a clearly defined research area, and it established divisions for chemistry, physics, and biology, but not computing. NSF did provide support for computing in its early years, but this support derived more from a desire to promote computer-related activities in other disciplines than to expand computer science as a discipline, and as such was weighted toward support for computing infrastructure. For example, NSF poured millions of dollars into university computing centers so that researchers in other disciplines, such as physics and chemistry, could have access to computing power. NSF noted that little computing power was available to researchers at American universities who were not involved in defense-related research and that “many scientists feel strongly that further progress in their field will be seriously affected by lack of access to the techniques and facilities of electronic computation.” As a result, NSF began supporting computing centers at universities in 1956 and, in 1959, allocated a budget specifically for computer equipment purchases. Recognizing that computing technology was expensive, became obsolete rapidly, and entailed significant costs for ongoing support, NSF decided that it would, in effect, pay for American campuses to enter the computer age. In 1962, it established its first office devoted to computing, the program for Computers and Computing Science within the Mathematical Sciences Division. By 1970, the Institutional Computing Services (or Facilities) program had obligated $66 million to university computing centers across the country. NSF intended that use of the new facilities would result in trained personnel to fulfill increasing needs for computer proficiency in industry, government, and academia.
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Innovation in INFORMATION TECHNOLOGY NSF provided some funding for computer-related research in its early years. Originally, such funding came out of the mathematics division in the 1950s and grew out of an interest in numerical analysis. By 1955, NSF began to fund basic research in computer science theory with its first grants for the research of recursion theory and one grant to develop an analytical computer program under the Mathematical Sciences Program. Although these projects constituted less than 10 percent of the mathematics budget, they resulted in significant research. In 1967, NSF united all the facets of its computing support into a single office, the Office of Computing Activities (OCA). The new office incorporated elements from the directorates of mathematics and engineering and from the Facilities program, unifying NSF's research and infrastructure efforts in computing. It also incorporated an educational element that was intended to help meet the radically increasing demand for instruction in computer science. The OCA was headed by Milton Rose, the former head of the Mathematical Sciences Section, and reported directly to the director of NSF. Originally, the OCA's main focus was improving university computing services. In 1967, $11.3 million of the office's $12.8 million total budget went toward institutional support. Because not all universities were large enough to support their own computing centers but would benefit from access to computing time at other universities, the OCA also began to support regional networks linking many universities together. In 1968, the OCA spent $5.3 million, or 18.6 percent of its budget, to provide links between computers in the same geographic region. In the 1970s, the computer center projects were canceled, however, in favor of shifting emphasis toward education and research. Beginning in 1968, through the Education and Training program, the OCA began funding the inauguration of university-level computer science programs. NSF funded several conferences and studies to develop computer science curricula. The Education and Training program obligated $12.3 million between 1968 and 1970 for training, curricula development, and support of computer-assisted instruction. Although the majority of the OCA's funding was spent on infrastructure and education, the office also supported a broad range of basic computer science research programs. These included compiler and language development, theoretical computer science, computation theory, numerical analysis, and algorithms. The Computer Systems Design program concentrated on computer architecture and systems analysis. Other programs focused on topics in artificial intelligence, including pattern recognition and automatic theory proving.
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Innovation in INFORMATION TECHNOLOGY 1970-1990: Retrenching and International Competition (From p. 107): Despite previous successes, the 1970s opened with computing at a critical but fragile point. Although produced by a large and established industry, commercial computers remained the expensive, relatively esoteric tools of large corporations, research institutions, and government. Computing had not yet made its way to the common user, much less the man in the street. This movement would begin in the mid-1970s with the introduction of the microprocessor and then unfold in the 1980s with even greater drama and force. If the era before 1960 was one of experimentation and the 1960s one of consolidation and diffusion in computing, the two decades between 1970 and 1990 were characterized by explosive growth. Still, this course of events was far from clear in the early 1970s. Accomplishing Federal Missions (From pp. 141-142): In addition to supporting industrial innovation and the economic benefits that it brings, federal support for computing research has enabled government agencies to accomplish their missions. Investments in computing research by the Department of Energy (DOE), the National Aeronautics and Space Administration (NASA), and the National Institutes of Health (NIH), as well as the Department of Defense (DOD), are ultimately based on agency needs. Many of the missions these agencies must fulfill depend on computing technologies. DOD, for example, has maintained a policy of achieving military superiority over potential adversaries not through numerical superiority (i.e., having more soldiers) but through better technology. Computing has become a central part of information gathering, management, and analysis for commanders and soldiers alike. Similarly, DOE and its predecessors would have been unable to support their mission of designing nuclear weapons without the simulation capabilities of large supercomputers. Such computers have retained their value to DOE as its mission has shifted toward stewardship of the nuclear stockpile in an era of restricted nuclear testing. Its Accelerated Strategic Computing Initiative builds on DOE's earlier success by attempting to support development of simulation technologies needed to assess nuclear weapons, analyze their performance, predict their safety and reliability, and certify their functionality without testing them. In addition, NASA could not have accomplished its space exploration or its Earth observation and monitoring missions without reliable computers for controlling spacecraft and managing data. New computing capabilities, including the World Wide Web, have enabled the National Library of Medicine to expand access to medical information and have provided tools for researchers who are sequencing the human genome.
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Innovation in INFORMATION TECHNOLOGY EVOLVING THE HIGH PERFORMANCE COMPUTING AND COMMUNICATIONS INITIATIVE TO SUPPORT THE NATION'S INFORMATION INFRASTRUCTURE (1995) CITATION: Computer Science and Telecommunications Board (CSTB), National Research Council. 1995. Evolving the High Performance Computing and Communications Initiative to Support the Nation's Information Infrastructure. National Academy Press, Washington, D.C. Continued Federal Investment Is Necessary to Sustain Our Lead (From pp. 23-25): What must be done to sustain the innovation and growth needed for enhancing the information infrastructure and maintaining U.S. leadership in information technology? Rapid and continuing change in the technology, a 10- to 15-year cycle from idea to commercial success, and successive waves of new companies are characteristics of the information industry that point to the need for a stable source of expertise and some room for a long-term approach. Three observations seem pertinent. 1. Industrial R&D cannot replace government investment in basic research. Very few companies are able to invest for a payoff that is 10 years away. Moreover, many advances are broad in their applicability and complex enough to take several engineering iterations to get right, and so the key insights become “public” and a single company cannot recoup the research investment. Public investment in research that creates a reservoir of new ideas and trained people is repaid many times over by jobs and taxes in the information industry, more innovation and productivity in other industries, and improvements in the daily lives of citizens. This investment is essential to maintain U.S. international competitiveness. . . . Because of the long time scales involved in research, the full effect of decreasing investment in research may not be evident for a decade, but by then, it may be too late to reverse an erosion of research capability. Thus, even though many private-sector organizations that have weighed in on one or more policy areas relating to the enhancement of information infrastructure typically argue for a minimal government role in commercialization, they tend to support a continuing federal presence in relevant basic research. 2. It is hard to predict which new ideas and approaches will succeed. Over the years, federal support of computing and communications research in universities has helped make possible an environment for exploration and experimentation, leading to a broad range of diverse ideas from which the marketplace ultimately has selected winners and losers. . . . [I]t is
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Innovation in INFORMATION TECHNOLOGY difficult to know in advance the outcome or final value of a particular line of inquiry. But the history of development in computing and communications suggests that innovation arises from a diversity of ideas and some freedom to take a long-range view. It is notoriously difficult to place a specific value on the generation of knowledge and experience, but such benefits are much broader than sales of specific systems. 3. Research and development in information technology can make good use of equipment that is 10 years in advance of current “commodity ” practice. When it is first used for research, such a piece of equipment is often a supercomputer. By the time that research makes its way to commercial use, computers of equal power are no longer expensive or rare. . . . The large-scale systems problems presented both by massive parallelism and by massive information infrastructure are additional distinguishing characteristics of information systems R&D, because they imply a need for scale in the research effort itself. In principle, collaborative efforts might help to overcome the problem of attaining critical mass and scale, yet history suggests that there are relatively few collaborations in basic research within any industry, and purely industrial (and increasingly industry-university or industry-government) collaborations tend to disseminate results more slowly than university-based research. The government-supported research program . . . is small compared to industrial R&D . . . but it constitutes a significant portion of the research component, and it is a critical factor because it supports the exploratory work that is difficult for industry to afford, allows the pursuit of ideas that may lead to success in unexpected ways, and nourishes the industry of the future, creating jobs and benefits for ourselves and our children. The industrial R&D investment, though larger in dollars, is different in nature: it focuses on the near term—increasingly so, as noted earlier—and is thus vulnerable to major opportunity costs. The increasing tendency to focus on the near term is affecting the body of the nation's overall R&D. Despite economic studies showing that the United States leads the world in reaping benefits from basic research, pressures in all sectors appear to be promoting a shift in universities toward near-term efforts, resulting in a decline in basic research even as a share of university research. Thus, a general reduction in support for basic research appears to be taking place. It is critical to understand that there are dramatic new opportunities that still can be developed by fundamental research in information technology—opportunities on which the nation must capitalize. These include high-performance systems and applications for science and engineering; high-confidence systems for applications such as health care, law enforcement, and finance; building blocks for global-scale information utilities (e.g., electronic payment); interactive environments for applica-
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Innovation in INFORMATION TECHNOLOGY tions ranging from telemedicine to entertainment; improved user interfaces to allow the creation and use of ever more sophisticated applications by ever broader cross sections of the population; and the creation of the human capital on which the next generation's information industries will be based. Fundamental research in computing and communications is the key to unlocking the potential of these new applications. How much federal research support is proper for the foreseeable future and to what aspects of information technology should it be devoted? Answering this question is part of a larger process of considering how to reorient overall federal spending on R&D from a context dominated by national security to one driven more by other economic and social goals. It is harder to achieve the kind of consensus needed to sustain federal research programs associated with these goals than it was under the national security aegis. Nevertheless, the fundamental rationale for federal programs remains: That R&D can enhance the nation's economic welfare is not, by itself, sufficient reason to justify a prominent role for the federal government in financing it. Economists have developed a further rationale for government subsidies. Their consensus is that most of the benefits of innovation accrue not to innovators but to consumers through products that are better or less expensive, or both. Because the benefits of technological progress are broadly shared, innovators lack the financial incentive to improve technologies as much as is socially desirable. Therefore, the government can improve the performance of the economy by adopting policies that facilitate and increase investments in research. [Linda R. Cohen and Roger G. Noll. 1994. “Privatizing Public Research,” Scientific American 271(3): 73]
Representative terms from entire chapter: