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    • Paper presented at the session on "VIRTUAL COMMUNITIES", sponsored by the Society for the Anthropology of Work and the Society of Psychological Anthropology in the 91th American Anthropological Association Congress, hold in San Francisco, Dec.2-6, 1992. CARNEGIE MELLON : AN AMERICAN COMPUTER UNIVERSITY. Arturo Serra, Ph.D. School of Computer Science 4615 Wean Hall Carnegie Mellon University Pittsburgh. PA 15213 Tel.: (412) 268 6128 Fax: (412) 268 5016 E-mail: as59+@andrew.cmu.edu. ABSTRACT. By content analysis of interviews and written projects gathered in the community, this study seeks to understand the kinds of cultural knowledge that support a computer science culture and their differences with other kinds of cultural knowledge. It also attempts to analyze the meanings of this culture in an American high technology university. This study is based on two year fieldwork at Carnegie Mellon University in 1990-1991 as part of a research project between technologists at CMU and anthropologists from University of Barcelona. The Centre Divulgador de la Informatica de la Generalitat, a Catalan public computer company, sponsored the project. I. CHANGES IN THE ACADEMIC CULTURE: THE COMPUTER UNIVERSITY. The topic of this study is the analysis of a North American research university called Carnegie Mellon as a " computer intensive campus ". In February 1990 a team of three anthropologists from Barcelona University, coordinated by professor Maria J. Buxó, arrived at this community in Pittsburgh, at the invitation of Professor Angel Jordan, a university professor
    • of Electrical and Computer Engineering and, at that time, Provost of the institution. We were interested in information technology, especially in academic organizations. The building of CMU as a “computer intensive campus" seemed very innovative to us. CMU is actually a networked academic community through the ANDREW system. In the 80s it was the first academic experiment of its kind in the country. The Andrew system is a distributed computer network connecting each college, department, and research team in the university. In 1990 there is about one computer for each member of the university, faculty, students and staff. 90 per cent of faculty use computers to prepare documents, 68 per cent use electronic mail and 76 per cent use online library information services. We have tried to understand the so-called "CMU knowledge revolution". This change has been developed under the influential work of several CMU professors: among them, Allen Newell, Alan Perlis, Herbert Simon, Dick Cyert, Raj Reddy, Nico Habermann, Mary Shaw, Angel Jordan. The Simon's idea of a "sciences of artificial" or "sciences of design", defined by along the last 20 years, is a good expression of this culture. For this professor, one of the founding fathers of the Artificial Intelligence, the design activity is a scientific activity and, the scientist, a designer. From a European point of view, this statement seems extremely interesting. Usually science and technology inhabit two different kinds of institutions in Europe, the humanistic-scientific university and the polytechnic one. "Informatique" lives mostly in the last one as a technological field. I have just expent two and one half years doing fieldwork in this university in three different places: the Engineering Design Research Center (EDRC), the School of Computer Science and the Andrew network. This "virtual community" is an INTERNET node, now with more than 5,000 bulletin boards, many of them dedicated to electronic newsletters, courses, organizations, and electronic debates, both national and international. During this time, I made 105 interviews of professors, research scientists, graduates students and staff from the CMU university community as a whole.
    • Progressively , I focused my investigation first in the research area of the university, and then in the School of Computer Science, its main research center. Finally, I have arrived at two apparently banal but useful conclusions: First, that the keystone of a research university is their research projects. And second, that each research project begins with a simple proposal written by a research team. Then I have designed a methodology to deal with this problem. I have called it "project analysis". The basis of this methodology is to try to understand what the goals of a research activity are, and to consider these goals as the value system of a research community. The ethnographic model of this kind of community will be based in its common research projects. We can consider "project analysis" as a application of the "content analysis"to the technological communities. Thanks to the friendly collaboration of Dr. Jordan and other professors, and thanks to the end of the Cold War too, I had access to the documentation of 30 years of defense sponsored research in this school, particularly its original proposals. The result has been the study of 21 large research projects in the four basic research areas in this School: "Artificial Intelligence", "Programming Systems", "Computer Systems" and "Theory", and the selection of 150 papers, technical reports,books, and dissertations of professors, graduate students and researchers of the institution referred to this topic. After this search, we learned several interesting things: First of all, Carnegie Mellon has built a kind of high technology university, or computer university, based on a core research knowledge in computer science and technology. This knowledge is extended to the rest of the campus through education in computer technology skills and a daily practice of networked research and education. At a first look, this university seems similar to the traditional American research university . This dominant model of university was analyzed by Talcott Parsons and Gerald Platt in a book called "The American University" published by Harvard University Press in 1973.
    • According to these authors, the "American university", or "full university", is an institution centered on a faculty of Arts and Sciences, that conceives the research activity as a primary academic function. Research and education is organized in departments comprised of professors and graduate students. The Arts and Science faculty is organized in three classical categories: humanities, natural sciences and social sciences, each of one divided in well-recognized intellectual disciplines. Usually this kind of university in America has absorbed the professional schools of law, medicine or engineering, conceiving them as a kind of applied professional complement to the basic core knowledge on arts and sciences. But Carnegie Mellon has different characteristics. In the first place, during the most part of its existence ,90 years, Carnegie Mellon has been an institute of technology, not a "full university". Only from 1967, was the institution born with the union of Carnegie Tech and Mellon Institute renamed "university". That means that during the most part of its existence, the arts and sciences have been a complement of technology to improve the knowledge about the design of new technological systems. In other words, the relation of science and technology is just the inverse situation than in the dominant universities of the Ivy League. Second, the leading faculty at Carnegie Mellon has been engineering, not the faculty of arts and sciences. That engineering culture has introduced the “problem solving" mentality as a characteristic feature of this institution. Nevertheless, after the World War II, an important change happened. The computer field was organized at Carnegie Tech by mathematicians and social scientists interested in the new machine, not by engineers. Because of that this new field was called "Computer Science" in Carnegie Tech. But, at the same time, this new "science" was very pragmatically oriented from the beginning. This was one of the reasons why it has been funded for 30 years by a federal entrepreneurial agency, the Advanced Research Project Agency, now DARPA. For decades this agency has supported a kind of fundamental technological research in Artificial Intelligence, Programming,
    • Computer System and Theory. This field was called Computer Science, but in fact this community, known as a "Artificial Intelligence ARPA laboratory" has centered it research in the knowledge about the design of technological systems, more than in its discovery as in the traditional sciences. The contradictory term "scientist of design" expresses this paradoxical situation. As a result of that context the term "science" has a different meaning in this community from that in the natural and social sciences. "Computer Science" at CMU primarily means the creation of knowledge about what kind of computer system the researcher can design and how he can build it. As an example of it, we will quote the goals of the research proposal in Artificial Intelligence at CMU called "Basic Research in Computer Science: Integrated Architectures for Intelligent Systems"(1990-1993): " The basic scientific results of this research will be a technical understanding of what types of total system organizations are capable of integrated intelligent behavior, as well as an understanding of which aspects of the total system belong in the architecture".(CMU-SCS-Basic Research in CS, 1989:6-1). In other words, this scientific activity is similar to a technical understanding about new capabilities of the new systems in construction. As Allen Newell, one of the founding father of CMU Computer Science community, said last year in a university conference at the SCS: " Science is in the techniques... .If a domain cannot get beyond having just discovering... that science is in fact in a pre-paradigmatic state. It is in a very early stage. My idea is that discoveries in physics, in chemistry, in biology all convert routinely into things you can do later" ("Desires and Diversions", April 12 1991.) Consequently, Newell spent the last years of his career designing SOAR, a new intelligent architecture. Discoveries are considered, in the traditional science communities, the highlights of the discipline. But in Computer Science, at least in CMU, discoveries are only means to do something different: to increase the knowledge about what kind of new computer systems are possible and how to design them. That history began with the invention of the Logic Theory Machine, the first Artificial Intelligence program in the 50s, and continues now with the design of
    • the Mach Operating System in the 80s. In fact, ANDREW was also a CMU Computer Science project . The general consensus in CMU defined Computer Science as " the study of the phenomena surrounding computers". Some professors, such as Herbert Simon, call it a "science of the artificial". For others it is an "experimental science". But the problem is that in this so-called "science" the computer scientist must figure out the new system before discovering its empirical characteristics. He must be a designer before a scientist. In other words, in computer science the empirical science comes after, not before, the design activity. In this sense, this cultural knowledge is a technological one in its nature, not a scientific one. Knowledge is design more than discovery, in the computer intensive campus. II. IMPLICATIONS: A NEW KIND OF RESEARCH MODEL. In this kind of university, the computer design activity precedes the science in a new kind of innovation cycle, driven by the technological activity. Usually, the traditional innovation cycle defined by the R&D policy experts is based in the so called Science &Technology system. This cycle begins with the Science, as the "basic research", and the Technology is conceived as an "application" of it. This model was established by Vanevar Bush and adopted by the National Science Foundation after the World World II. It has been useful for the period where the physicists had the leadership in academic research. But the Cold War is over now and in Computer Science this model does not fit very well. In this computer culture, fundamental or basic design research has been growing for decades independent of basic science. The innovation process begins with this design activity and empirical science follows it. In other words, the computer technology at CMU is not a mere application of the natural or social sciences, but increasingly its own foundation.
    • At the beginning the computer was a simple machine built by mathematicians, like Pascal or Babbage, as a tool to do calculations. But now mathematicians, physicists, cognitive psychologists, linguistics, indeed the natural and social science community are increasingly becoming designers, helping the computer scientists in building the Universal Machine. This new research model is redefining what knowledge means in an advanced information society. In 1988 the Computer Science and Technology Board, a section of the National Research Council, in a rapport called " The National Challenge in Computer Science and Technology" said: " Since computer science is an artificial science (Simon 1981) theoretical computer science plays a very different role within computer science than, say, theoretical physics plays within physics. Theoretical physics seeks to understand the physical universe, which exists independently. Theoretical computer scientists seek to understand all possible architectures or algorithms, which computer scientists create themselves." This change in the cultural meaning of a key cultural knowledge of Western civilization, scientific knowledge, could have enormous consequences in the next future. We are changing from a natural scientific vision of the world, the world as a “natural order", to a technological one in which the world is conceived as a man-made machine, as an artifact. This presents a great danger and a great challenge to anthropologists. The final goal of the Computer Science and Technology community is to design the Universal Machine. In this sense, the new "artificial world" can have the appearance of a world of sophisticated machines served by human beings. Usually, anthropology in computer fields is used to help the engineer in designing a better system. But we have seen in CMU that, before a machine exists, a human being plans for it, designs it, projects for it. The computer as a technology comes certainly before an empirical science of it, but the computer scientist as a human designer comes before his computer. The anthropologists can show that machines are human designs done by human designers. In this sense, the artificial world can have a different meaning: it is not the machine, but the community that builds
    • that machine, the world of designers. As for the applied mathematicians as Turing developed the Universal Machine model, the applied anthropologists working in computer cultures could develop a Turing new one we could call: Multicultural Virtual Community . Our goal would be helping to build new kind of computer-based communities . Until now the anthropology has adopted the empirical approach of the natural sciences. Working in the computer cultures, we need now changing to a computational approach trying to understand, as the theoretical computer scientists do, not only the cultures that live independently but the possible virtual communities which the computer anthropologist can promote by itself. In this sense, the anthropologist working in the computer communities can become a different kind of designer, a designer of cultural communities. Arturo Serra. Pittsburgh, November 30th, 1992. Some references:  Serra,A . 1992. "Design Culture, An ethnographic study on the research projects of the School of Computer Science of CMU, an American Computer-Intensive Campus". Universitat de Barcelona. Doctoral Dissertation.  Simon,H. 1981, The Sciences of the Artificial. 2n.ed.Cambridge MA. The MIT Press.  Simon, H. 1990. Personal interviews. Department of Psychology. (May 1st, Nov 30th, Dec. 17). CMU.