This document summarizes an ethnographic study of the culture at Carnegie Mellon University (CMU), which the author describes as a "computer intensive campus". Some key points:
1) CMU has built itself as a high-tech university focused on computer science and technology research, with most faculty and students using computers extensively.
2) In contrast to traditional universities focused on arts/sciences, CMU's leading faculty has been engineering and it emphasizes solving problems over basic discovery.
3) The author argues CMU's "Computer Science" culture is more about designing new computer systems than discovering empirical truths, with technology preceding science in the innovation process.
4) This represents a new model of research
Philosophy, Science, Arts, Technology: World Knowledge Grand UnificationAzamat Abdoullaev
Creating the Future
Reality
Worlds
Philosophy
Science
Arts
Technology
Unification
Global Research and Innovation Space
Superscience
Internet of Everything
Intelligent Internet
Smart WWW
Online engagement and information literacy: The Many Face of Digital Visitors...Lynn Connaway
Connaway, L. S. (2018). Online engagement and information literacy: The Many Face of Digital Visitors & Residents. Presented at the Bibliostar Conference, March 15, 2018, Milan, Italy.
Philosophy, Science, Arts, Technology: World Knowledge Grand UnificationAzamat Abdoullaev
Creating the Future
Reality
Worlds
Philosophy
Science
Arts
Technology
Unification
Global Research and Innovation Space
Superscience
Internet of Everything
Intelligent Internet
Smart WWW
Online engagement and information literacy: The Many Face of Digital Visitors...Lynn Connaway
Connaway, L. S. (2018). Online engagement and information literacy: The Many Face of Digital Visitors & Residents. Presented at the Bibliostar Conference, March 15, 2018, Milan, Italy.
Doing the Digital: How Scholars Learned to Stop Worrying and Love the ComputerAndrew Prescott
Slides from keynote presentation to Social Media Knowledge Exchange meeting on Scholarly Communication in the 21st Century, University of Cambridge, 4 June 2015. Examines my changing relationship to scholarly communication, current pressures and drivers, and likely future trends.
Manifesto for synthetic social sciences technologiesArtur Serra
After computer science and other synthetic sciences like bio or nano, it is time now to explore the possibility of synthetic social sciences/technologies. Techno-anthropology can be a first candidate.
Introduction to digital scholarship and digital humanities in the liberal art...kgerber
Introduces the scholarly conversation around the emerging topic of Digital Humanities and how it relates to smaller, liberal arts institutions. The conclusion of the presentation provides examples of ways you can learn more and get involved in the discussion and practice of Digital Humanities and Digital Liberal Arts.
The title of this talk borrows from the title of a chapter in a recently published book by Richard Smiraglia, Cultural Synergy in Information Institutions (7.9: What if There Were a Map?). The use of visualizations in the exploration of bodies of knowledge and for the organization of knowledge has a long history. Think in terms of the tree(s) of knowledge and large-scale maps of science (see Atlas of Science by Katy Börner). This talk introduces the work of a European network of research collaboration (a so-called COST Action) KnoweScape. KnoweScape explores how knowledge maps (from simple to sophisticated) can be made and applied to better understand, navigate, and curate collections held by libraries and archives. In terms of general research methodology, this talk is also a plea for creating overview prior to in-debt analysis and to seek for relative stable reference frameworks against which rapid changes of our knowledge can be interrogated. Looking at results produced by this community of scholars so far, it will become clear why the making of knowledge maps requires the collaboration of physicists, computer scientists, sociologists of knowledge, digital humanities scholars, and information scientists and professionals.
Applying machine learning techniques to big data in the scholarly domainAngelo Salatino
Slides of the Lecture at the 5th International School on Applied Probability Theory,Communications Technologies & Data Science (APTCT-2020)
12 Nov 2020
NG2S: A Study of Pro-Environmental Tipping Point via ABMsKan Yuenyong
A study of tipping point: much less is known about the most efficient ways to reach such transitions or how self-reinforcing systemic transformations might be instigated through policy. We employ an agent-based model to study the emergence of social tipping points through various feedback loops that have been previously identified to constitute an ecological approach to human behavior. Our model suggests that even a linear introduction of pro-environmental affordances (action opportunities) to a social system can have non-linear positive effects on the emergence of collective pro-environmental behavior patterns.
International Journal of Business and Management Invention (IJBMI) is an international journal intended for professionals and researchers in all fields of Business and Management. IJBMI publishes research articles and reviews within the whole field Business and Management, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online
Keynote Address, International Conference of the Learning Sciences, London Festival of Learning
Transitioning Education’s Knowledge Infrastructure:
Shaping Design or Shouting from the Touchline?
Abstract: Bit by bit, a data-intensive substrate for education is being designed, plumbed in and switched on, powered by digital data from an expanding sensor array, data science and artificial intelligence. The configurations of educational institutions, technologies, scientific practices, ethics policies and companies can be usefully framed as the emergence of a new “knowledge infrastructure” (Paul Edwards).
The idea that we may be transitioning into significantly new ways of knowing – about learning and learners – is both exciting and daunting, because new knowledge infrastructures redefine roles and redistribute power, raising many important questions. For instance, assuming that we want to shape this infrastructure, how do we engage with the teams designing the platforms our schools and universities may be using next year? Who owns the data and algorithms, and in what senses can an analytics/AI-powered learning system be ‘accountable’? How do we empower all stakeholders to engage in the design process? Since digital infrastructure fades quickly into the background, how can researchers, educators and learners engage with it mindfully? If we want to work in “Pasteur’s Quadrant” (Donald Stokes), we must go beyond learning analytics that answer research questions, to deliver valued services to frontline educational users: but how are universities accelerating the analytics innovation to infrastructure transition?
Wrestling with these questions, the learning analytics community has evolved since its first international conference in 2011, at the intersection of learning and data science, and an explicit concern with those human factors, at many scales, that make or break the design and adoption of new educational tools. We are forging open source platforms, links with commercial providers, and collaborations with the diverse disciplines that feed into educational data science. In the context of ICLS, our dialogue with the learning sciences must continue to deepen to ensure that together we influence this knowledge infrastructure to advance the interests of all stakeholders, including learners, educators, researchers and leaders.
Speaking from the perspective of leading an institutional analytics innovation centre, I hope that our experiences designing code, competencies and culture for learning analytics sheds helpful light on these questions.
Resumen del proyecto i2cat, 1999-2003, un proyecto de diseño y desarrollo de la Internet2 en Catalunya, que dió lugar a la creación de la Fundación i2cat en septiembre 2003.
Doing the Digital: How Scholars Learned to Stop Worrying and Love the ComputerAndrew Prescott
Slides from keynote presentation to Social Media Knowledge Exchange meeting on Scholarly Communication in the 21st Century, University of Cambridge, 4 June 2015. Examines my changing relationship to scholarly communication, current pressures and drivers, and likely future trends.
Manifesto for synthetic social sciences technologiesArtur Serra
After computer science and other synthetic sciences like bio or nano, it is time now to explore the possibility of synthetic social sciences/technologies. Techno-anthropology can be a first candidate.
Introduction to digital scholarship and digital humanities in the liberal art...kgerber
Introduces the scholarly conversation around the emerging topic of Digital Humanities and how it relates to smaller, liberal arts institutions. The conclusion of the presentation provides examples of ways you can learn more and get involved in the discussion and practice of Digital Humanities and Digital Liberal Arts.
The title of this talk borrows from the title of a chapter in a recently published book by Richard Smiraglia, Cultural Synergy in Information Institutions (7.9: What if There Were a Map?). The use of visualizations in the exploration of bodies of knowledge and for the organization of knowledge has a long history. Think in terms of the tree(s) of knowledge and large-scale maps of science (see Atlas of Science by Katy Börner). This talk introduces the work of a European network of research collaboration (a so-called COST Action) KnoweScape. KnoweScape explores how knowledge maps (from simple to sophisticated) can be made and applied to better understand, navigate, and curate collections held by libraries and archives. In terms of general research methodology, this talk is also a plea for creating overview prior to in-debt analysis and to seek for relative stable reference frameworks against which rapid changes of our knowledge can be interrogated. Looking at results produced by this community of scholars so far, it will become clear why the making of knowledge maps requires the collaboration of physicists, computer scientists, sociologists of knowledge, digital humanities scholars, and information scientists and professionals.
Applying machine learning techniques to big data in the scholarly domainAngelo Salatino
Slides of the Lecture at the 5th International School on Applied Probability Theory,Communications Technologies & Data Science (APTCT-2020)
12 Nov 2020
NG2S: A Study of Pro-Environmental Tipping Point via ABMsKan Yuenyong
A study of tipping point: much less is known about the most efficient ways to reach such transitions or how self-reinforcing systemic transformations might be instigated through policy. We employ an agent-based model to study the emergence of social tipping points through various feedback loops that have been previously identified to constitute an ecological approach to human behavior. Our model suggests that even a linear introduction of pro-environmental affordances (action opportunities) to a social system can have non-linear positive effects on the emergence of collective pro-environmental behavior patterns.
International Journal of Business and Management Invention (IJBMI) is an international journal intended for professionals and researchers in all fields of Business and Management. IJBMI publishes research articles and reviews within the whole field Business and Management, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online
Keynote Address, International Conference of the Learning Sciences, London Festival of Learning
Transitioning Education’s Knowledge Infrastructure:
Shaping Design or Shouting from the Touchline?
Abstract: Bit by bit, a data-intensive substrate for education is being designed, plumbed in and switched on, powered by digital data from an expanding sensor array, data science and artificial intelligence. The configurations of educational institutions, technologies, scientific practices, ethics policies and companies can be usefully framed as the emergence of a new “knowledge infrastructure” (Paul Edwards).
The idea that we may be transitioning into significantly new ways of knowing – about learning and learners – is both exciting and daunting, because new knowledge infrastructures redefine roles and redistribute power, raising many important questions. For instance, assuming that we want to shape this infrastructure, how do we engage with the teams designing the platforms our schools and universities may be using next year? Who owns the data and algorithms, and in what senses can an analytics/AI-powered learning system be ‘accountable’? How do we empower all stakeholders to engage in the design process? Since digital infrastructure fades quickly into the background, how can researchers, educators and learners engage with it mindfully? If we want to work in “Pasteur’s Quadrant” (Donald Stokes), we must go beyond learning analytics that answer research questions, to deliver valued services to frontline educational users: but how are universities accelerating the analytics innovation to infrastructure transition?
Wrestling with these questions, the learning analytics community has evolved since its first international conference in 2011, at the intersection of learning and data science, and an explicit concern with those human factors, at many scales, that make or break the design and adoption of new educational tools. We are forging open source platforms, links with commercial providers, and collaborations with the diverse disciplines that feed into educational data science. In the context of ICLS, our dialogue with the learning sciences must continue to deepen to ensure that together we influence this knowledge infrastructure to advance the interests of all stakeholders, including learners, educators, researchers and leaders.
Speaking from the perspective of leading an institutional analytics innovation centre, I hope that our experiences designing code, competencies and culture for learning analytics sheds helpful light on these questions.
Resumen del proyecto i2cat, 1999-2003, un proyecto de diseño y desarrollo de la Internet2 en Catalunya, que dió lugar a la creación de la Fundación i2cat en septiembre 2003.
Living Labs, Social Innovation Ecosystems and CollaboratoriesArtur Serra
Global Societal Challenges needs Global Social Innovation Ecosystem to deal with. Collaboratorociies, prototypes of such new kind of innovation ecosystems, can help. Colab CatSud is a first project in Southern Catalunya that explor such new approach.
Article aparegut al llibre Disseny del futur, editat per Miquel Barceló. 2002. https://www.todocoleccion.net/libros-segunda-mano/el-disseny-futur-miquel-barcelo-coord-ed-proa-catala~x136332542
Internet es el resultado de un nuevo tipo de conocimiento y de organización del mismo. Este tipo de conocimiento fusión de ciencia y tecnologia cambiará las politicas culturales del siglo XXI.
Article in the book HiperCatalunya, Territoris de Recerca
https://www.agapea.com/Grupo-Metapolis/Hipercatalunya-Territoris-de-recerca-9788495951380-i.htm
Open Science new strategies need new science structures to be developed. We call it: open labs, new research and innovation environments based on a synthesis of current structures (academic research groups, companies, civic organitzations, public bodies,...). These open labs are currently emerging as living labs, fablabs, citizen labs, xlabs....
Until now new technologies have connected old economic, social, political structures. Nevertheless new structures are emerging.
Bibliolabs, les Biblioteques com a centres de coneixementArtur Serra
Bibliolab es un programa pioner per convertir les biblioteques pùbliques de Barcelona en living labs. Col.labora amb el programa Catlabs de la Generalitat de Catalunya
After computer science and technology, we need a living lab science and technology, a new social high tech for the design of the new social structures of the digital era, beyond the digital platforms.
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Safalta Digital marketing institute in Noida, provide complete applications that encompass a huge range of virtual advertising and marketing additives, which includes search engine optimization, virtual communication advertising, pay-per-click on marketing, content material advertising, internet analytics, and greater. These university courses are designed for students who possess a comprehensive understanding of virtual marketing strategies and attributes.Safalta Digital Marketing Institute in Noida is a first choice for young individuals or students who are looking to start their careers in the field of digital advertising. The institute gives specialized courses designed and certification.
for beginners, providing thorough training in areas such as SEO, digital communication marketing, and PPC training in Noida. After finishing the program, students receive the certifications recognised by top different universitie, setting a strong foundation for a successful career in digital marketing.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
Natural birth techniques - Mrs.Akanksha Trivedi Rama University
Aaa92 new
1. 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
2. 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.
3. 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.
4. 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,
5. 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
6. 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.
7. 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
8. 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.