Abstract: Given that the Internet is an engineered system like any other, why should we
distinguish “Internet research” from any other study of technology? One answer is that
computers are distinctive in their direct and systematic relationship to language. Another is
that the Internet, through its layered architecture, is highly appropriable. Even so, the
Internet does not cause a revolution or define a wholly separate “cyber” sphere. Instead,
due to its distinctive qualities, it participates in somewhat distinctive ways in the ongoing
political life of institutions.
When I was going to graduate school at MIT, most of the professors around me were
embarrassed to be called computer scientists. Their complaint was this: why should there
be a separate field of computer science, any more than there is a separate field of
refrigerator science? In their view, computers were just complex physical artifacts like any
others. Following Simon (1969), they argued that design principles such as modularity are
not specific to software, but are properties of the universe in general. The structures that
evolve are modular because modular structures are more stable than others. Computers
were simply a special case of these universal laws.
This perspective on computer science differs from the view in most textbooks. In the
textbooks, a computer is a device that can compute any function that any particular Turing
machine can compute. The professors at MIT would have none of this. Of course the
mathematics of computability was interesting, but it reflected only one corner of a much
larger space of inquiry. What they found most interesting was not the mapping from single
inputs to single outputs but the relationship between the structure of a computational
device and the organization of the computational process that arose when the device was
set running.
The physical realization of computational processes was, however, only half the story. The
other half lay in the analysis of problem domains. This is a profound aspect of computer
work — and all engineering work — that is almost invisible to outsiders. Computers are
general-purpose machines in that they can be applied to problems in any sphere. A system
designer might work on an accounting application in the morning and an astronomical
simulation in the afternoon. As the problems in these domains are translated into
computational terms, certain patterns recur, and engineers abstract these patterns into
layers of settled technique.
Here is an example. I once consulted with a company that wanted to automate the design
of some complex mechanical artifacts. The designer of these artifacts might have to make
several dozen design decisions. I spent several weeks sitting with an engineer and
marching through a stack of manuals for the design of this category of artifacts. We needed
the answer to a critical question: in working forward from requirements to design, does the
designer ever need to backtrack? Is it ever necessary to make a design decision that might
have to be retracted later? If backtracking was required, the companys task would become
much harder. After working several cases by hand, it became clear that backtracking was
not only necessary but ubiquitious, and that the company needed to hire someone who
could build a general-purpose architecture for the backtracking of parameterized
constraints. Backtracking is an example of a structure that recurs frequently in the analysis
of problem domains. The resulting analogy among domains can be pursued, and might be
illuminating all around.
For the professors at MIT, then, engineering consists of a dialectical engagement between
two activities: analyzing the ontology of a domain and realizing that domains
decision-making processes in the physical world. (“Realize” here means “make physically
real” rather than “mentally understand”.) Ideas about computational structure exist for the
purpose of translating back and forth between these two aspects of the engineers work.
This is a profound conception of engineering. And nothing about it is specific to
computers.
This story is appealing because it dissolves the concept of the computer, which normally
connotes a sharp break with the past, into the great historical tradition of engineering
design. It is certainly an improvement on the standard story based on computability theory.
Still, I believe that both stories overlook one area in which design is different for
computers than for anything else. That area pertains to language.
Computers, whatever their other virtues, at least give people something to talk about. Your
friends in China may not be having the same weather, but they are having the same virus
outbreaks. Computers not only transcend geographical boundaries; they also bridge
disciplines. Physicists and literary critics may not be able to discuss their research, but they
can discuss their computers. Soldiers and media artists struggle with the same software.
This kind of universality arises precisely from the analytical phase of the design process.
Computers, in this sense, provide a trading zone” (Galison 1997) for discussions across
different disciplinary languages. Computers are a shared layer in a wide variety of
activities, and many activities have been reconstructed on top of the platform that
computer standards provide. In these ways and more, computers are densely bound up with
language (Hirschheim, Klein, and Lyytinen 1996; Swanson and Ramiller 1997;
Theoharakis and Wong 2002; Weill and Broadbent 1998).
Saying this, however, does not identify what is distinctive about computers. The answer is:
computers are distinctive in their relation to discourse. Discourses about the world — that
is, about people and their lives, the natural environment, business processes, social
relationships, and so on — are inscribed into the workings of computers. It does not follow,
of course, that computers then turn around and reinscribe those discourses into the
activities of the people who use them. Every social setting takes hold of its computers in its
own distinctive way (Orlikowski 2000). But neither is a computer a blank slate. Every
system affords a certain range of interpretations, and that range is determined by the
discourses that have been inscribed into it. To understand what is distinctive about the
inscription of discourses into computers, as opposed to their inscription into other sorts of
artifacts, it helps to distinguish among three progressively more specific meanings of the
idea of inscription.
(1) Shaping. Sociologists refer to the social shaping of technology” (Dierkes and Hoffman
1992, MacKenzie and Wajcman 1985, Wiebe and Bijker 1992). Newly invented
technologies typically exist in competing variants, but that political conflicts and other
social processes eventually settle on particular designs. One prototype of social shaping is
“how the refrigerator got its hum” (Cowan 1985): early refrigerators came in both electric
and gas varieties, but the electric variety won the politics of infrastructure and regulation.
Social shaping is also found in the styling of artifacts, for example tailfins on cars, and
elsewhere. Social shaping analyses can be given for every kind of technology, and while
language is certainly part of the process, the concept of social shaping does not turn on any
specific features of language.
(2) Roles. One type of social shaping is found in the presuppositions that a technology can
make about the people who use it. Akrich (1992a, 1992b) gives examples of both
successes and failures that turned on the designers understandings of users. A company
created a device consisting of a solar cell, a battery, and a lamp, intended for use in
countries with underdeveloped infrastructures. Rather than study the web of relationships
in which those people lived, though, the company sought to make its device foolproof, for
example by making it hard to take apart and by employing components that were not
available on the local market. When ordinary problems arose, such as the short wire
between the battery and the lamp, the users were unable to adapt it. By contrast, a
videocassette player embodied elaborate ideas about the user, for example as a person
subject to copyright laws, that its very design was largely successful in enforcing. In each
case, the designer, through a narrative that was implicit or explicit in the design process,
tried to enlist the user into a certain social role. And language is geared to the construction
of narratives about roles and relationships. (See also Barley (1990), Feenberg (1991:
80-82), Latour (1996), Lea and Giordano (1997), Mackay, Carne, and Beynon-Davies
2000, Sharrock and Button (1997), and Woolgar (1991).) Even so, nothing here is specific
to computers either.
(3) Grammar. Where computers are really distinctive is in their relationship to grammar.
Systems analysis does not exactly analyze a domain, as the professors at MIT would have
it. Rather, it analyzes a discourse for talking about a domain. (Or perhaps a domain must
be understood as a discourse bound up with the objects it describes.) To be sure, much of
the skill of systems analysis consists in assimilating this discourse to known techniques for
realizing a decision-making process in the physical world (Suchman and Trigg 1993). But
the substance of the work is symbolic. Computer people are ontologists, and their work
consists of stretching whatever discourse they find upon the ontological grid that is
provided by their particular design methodology, whether entity-relationship data models
(Simsion 2001), object-oriented programming (Booch 1996), or the language-action
perspective (Winograd and Flores 1986). In each case, the systems analyst performs a
