CSE 275: Social Aspects of Technology and Science

7. Some Case Studies

The first four subsections below apply some of the concepts and theories that we have been studying, especially ANT, while the last gives some practical motivation for studying them.

7.1 A Database Theory Crisis?

In Database Metatheory: Asking the Big Queries, Christos Papadimitriou (a former UCSD CSE faculty member who recently moved to Berkeley) applies falsifiability and notions from Kuhn to computer science, and in particular, to database theory. His main claim is that theoretical CS is now in a crisis. Although this is certainly true in some sense, due to the phenomenal growth and fragmentation of computer science today, I do not think it is true in Kuhn's more technical sense; part of the problem is that Papadimitriou seems to be using the term "paradigm" for phenomena that are much more fine-grained than intended by Kuhn. The example that Papadimitriou gives of a paradigm shift in the database community, namely the introduction of the relational model, seems very good, and I also like his Figure 1, as a graphical summary of Kuhn (though I doubt that Kuhn would have approved).

The two diagrams in Figure 2 can be considered actor-network diagrams, although Papadimitriou doesn't use (and doesn't know) this theory; his use of properties of random graphs in this connection is very clever. One could extrapolate a fascinating conjecture from his graph-based discussion of the theory/practice split in the database community, namely that normal science correlates with having a single well-connected "random" graph, while crisis correlates with having several major well-connected subgraphs, between which there are only weak links. However, Papadimitriou's discussion would have been better if the graphs in Figure 2 had some genuine empirical content, instead of being "unspecified," i.e., made up by the author.

Papadimitriou also poses the interesting question of what constitutes falsifiability in computer science, and more generally, in a "science of the artificial," but fails to reach a conclusion. Personally, I have doubts about both the notion of falsifiability and that of a "science of the artificial," and so am not very surprised at the inconclusive result here.

7.2 Four Case Studies for Actor Network Theory

In Traduction/Trahison - Notes on ANT, John Law (Department of Sociology, Univeristy of Lancaster, UK) discusses four case studies that apply ANT to various situations, in various ways. The paper is well written, and his comparative discussion is at least as interesting as the case studies themselves, revealing much about the recent evolution and somewhat elusive nature of ANT.

The first case study discussed by Law was done by Madeleine Akrich and concerns technology transfer, a subject on which much has been written; ANT sheds an interesting light on it, since much more gets "translated" during the so called "transfer" than we might expect. This seems to be a counterexample to naive "diffusion" theories, which claim that technologies transfer simply by spreading out through some milieu - basically a form of technological determinism. However the work of Akrich shows instead that there can be complex interactions between the source network (in this case, in Sweden), the target network (in this case, in Nicaragua), and the technology itself (a wood waste compacting machine), during which all three may be changed in significant ways. In this case, it is the technology itself that undergoes the most significant alteration, which is somewhat against the spirit of the original "canonical" actor-network theory, from Paris in the 1980s.

The second study discussed by Law, done by Charis Cussins (while she was at UCSD), concerns a medical procedure called "in vitro fertilization." As Law points out, Cussins pays close attention to inconsistency, and in particular, questions whether "objectification" (being treated as an object, e.g., in a medical procedure) is necessarily a bad thing, as is often assumed without much thought. Law also points out that Cussins' approach differs in some significant respects from canonical ANT, which tended towards making things appear consistent, by finding a place for them in a network. Cussins' study shows that time can play a "dialectical" role (involving a "thesis," "antithesis," and (perhaps) a final "synthesis" or resolution), with network relations changing not only over time and actor, but sometimes reversing in motivated ways, as actors look back and re-evaluate. Even what is said to exist (the "ontology") can change over time. Cussins also emphasizes the work involved in making all this happen. The work needed to make things happen is a common theme in ANT, but the "things" involved here are not so common.

The third case study discussed here is by Vicky Singleton, and concerns another medical procedure, the Cervical Screening Procedure (CSP), in the context of British medicine. Singleton points out a large number of ambiguities and ambivalences in the attitudes of both doctors and patients about this procedure, and then argues that these are not a problem for the CSP, but on the contrary, serve to strengthen it. For example, a woman may feel more comfortable with a doctor who is not highly authoritative and authoritarian. This version of ANT differs significantly from canonical ANT in not speaking of enrolling actors and locking them into continuous chains of translation. Instead, it speaks of the utility of actors changing roles and attitudes, and of the utilities of inconsistency and even of exclusion and conflict. However, the inconsistencies are local and effective parts of the network.

One conclusion that Law draws from this and the Cussins study is that in many cases, it may not be possible to tell any single "grand" coherent story of what happened to/in/with a given actor-network; instead, it will be necessary to tell many little stories, which in general will not be consistent with each other. He then "goes meta" (as computer scientists like to say), and claims that ANT now has a similar status, in that it can no longer be told as a single story, but instead has evolved into a set of not necessarily mutually consistent stories.

All this is reminiscent of postmodernism in the version of Lyotard (there are many different mutually inconsistent versions of postmodernism, some of which seem to me a birt crazy). Lyotard speaks of "local language games" (in roughly the sense of late Wittgenstein), i.e., of narrative systems that are not in general mutually consistent.

The fourth case study, by Annemarie Mol, concerns the diagnosis and tratment of arteroschlerosis in the Netherlands (though there is little doubt that the situation is similar in most developed countries). This study perhaps departs furthest from canonical ANT, as it questions the idea that any single coherent pattern actually exists in the data of the study, and Law goes so far as to say

We are in the business of making the objects of our study. Of making realities, and the connections between those realities. Of making the realities that we describe.
This is exactly the kind of extreme position that Sokal wants to discredit: that the social scientists are creating the reality they study, not nature itself, nor even the scientists (or in this case, doctors) that they are studying. However, my opinion is that Mol's study only warrants the weaker view that in some cases there may not be any single coherent story, not even a coherent pattern of inconsistency, like that found by Singleton, but rather there may be just an on-going process of forging links and enduring clashes; and given Law's somewhat loose writing style in this paper, it is not even clear that he would himself subscribe to the extreme position of the above quote - in fact, my own view is that he is probably just presenting it as one more possible evolutionary outgrowth version of ANT.

Law uses the term ontology with various prefixes to describe the several variants of ANT that seem to arise here, from "ontological choreography," a term introduced by Cussins for the work of creating coherence, to "ontological patchwork" for situations like those described by Mol. He concludes that ANT is "diasporic" (i.e., spreading out), being "translated" ("traduction"), and in the process, being "betrayed" ("trahison'), i.e., changing in ways of which the originators of ANT might not approve. His final conclusion is that this is a good thing. I would agree with this, for the reason that growth and change demonstrate vitality. As Kuhn's theory says, any good theory will continue to adapt through periods of normal science, and will inspire revolutionary revisions after a period of crisis. The paper of Law would seem to suggest that ANT is now in a period of crisis; personally, I would consider such a judgement premature.

Some social scientists seem to be interested in the sociology of sociology, and in particular, in applying whatever theory they are working on to itself; they often use the word "reflexive" for this, though computer scientists would say "recursive" or "self-referential." The paper by Law, and to a lesser extent the paper by Bowker and Star discussed in Section Section 7.3 below, are of this kind, and in particular, are interested in the sociology of actor network theory, and apply actor network theory to itself. The results are interesting, though at times perhaps a bit difficult to untangle. Reflectivity in various guises is an important theme in the 20th century arts and humanities, as well as science, and can be seen, for example, in the famous drawings of Escher and short stories of Borges; the play "Six Characters in Search of an Author" by Luigi Pirandello is also well known in the modern theatre community, and there are many other examples. In computer science, I have seen language design guidelines recommend that every feature possible should be made recursive (which seems to me very foolish advice).

7.2.1 Comparing Kuhn with ANT

Now let's be a little reflexive ourselves, and consider how ANT and Kuhn's ideas might illuminate each other, using Law's paper as a basis. The technology in Law's first case study, on technology transfer from Sweden to Nicaragua, might at first seem like a typical example of "normal science," involving adaptations to new conditions. But a closer examination reveals phenomena that are far from those considered by Kuhn, such as the pest Amphiserus Cornutu, and the seasonal schedules of Nicaraguan farm workers. We can claim an analogy between the adaptation of scientific theories to new data, and the transfer of technology to new environments, but more than that would be difficult to justify.

Law's fourth case study, of the diagnosis of arteriosclerosis, seems a good illustration of pre-paradigmatic science, because things do not form a coherent whole, and it also seems reasonable to consider medical diagnosis a kind of science, even though the actants involved here are far more heterogeneous than would be entertained by Kuhn, and the scope of this activity is less than in Kuhn's exemplars.

The second and third case study in Law's paper seem to involve in a central way concepts that are too far from Kuhn's way of thinking for there to be any deep similarities at all.

Now let's try to look at ANT itself in Kuhnian terms, which though it may require some broadening of Kuhn's notion of science, seems to be quite reasonable. Is the diversity revealed by Laws' case studies a crisis, or normal science, or pre-paradigmatic science? Or is perhaps a revolution happening? Despite pronouncements by Latour that ANT is dead, I am inclined to say that this is normal science, with concepts and theories adapting and evolving in the light of new data, despite the fact that these concepts and theories are far more vague than in physics, and that close examination reveals many actants that Kuhn would not have considered, such as professional societies, manifestos, and death pronouncements.

By way of summary and synthesis, although I do feel that there is much of value in Kuhn's work, comparing it carefully with ANT produces a sense of its being overgeneralized, of lacking attention to the details of how science is achieved, including the actual work of science, and its infrastructure and its institutions. Moreover, we have seen that there is considerably more anbiguity, conflict, instability, diversity, confusion and even chaos than Kuhn's framework admits, even in normal science.

In fact, ANT provides more refined, more nuanced reflections of Kuhn's ideas. Instead of a crude classification into pre-paradigmatic, normal and crisis, ANT would consider in detail which actants are enrolled, and to what extent; it would also consider the degree to which various translations are successful, at various times. Instead of a dramatic revolution, we can look for many different kinds of change, some of which may be very slow, yet still yield a very different final state, others of which may affect only small parts of a large network. Similarly, Kuhn's notion of retrospective reinterpretation is too absolute and total; in ANT, reinterpretation is merely retranslation, which may occur to a certain extent in some, but not all parts of a network, and may happen in different ways, at different rates, at different times, or even not at all.

So we conclude that the phenomena described by Kuhn do occur, but are relatively rare, extreme forms of much more common phenomena that are often much more complex and subtle. Kuhn does not provide a language for describing such phenomena, but in they are a basic aspect of ANT.

7.3 Classification, Standards and Databases

In How things (actor-net)work: Classification, magic and the ubiquity of standards, Geoffrey Bowker and Susan Leigh Star (technical report, from the University of Illinois at Champaign-Urbana, 1998 - though both are now at UCSD) give a most interesting discussion of classifications and standards, showing how treating them with ANT allows addressing political and ethical issues, through making infrastructure non-transparent. (Help with the actor-network theory can be obtained from the Section 6.1, and the paper by Law discussed in Section 7.2 above.) This case study considers the Nursing Intervention Classification (NIC), an attempt by nurses to develop a new classification system for their activities that better represents what they see as important, such as comforting patients. Their classification system is a move in the struggle of nurses to fit better into a healthcare environment dominated by HMOs with their heavy emphasis on accountancy. Two sample categories from the NIC are "hope installation" and "humor," where the latter is defined as "facilitating the patient to perceive, appreciate and express what is funny, amusing, or ludicrous in order to establish relationships."

From a computer science perspective, I would highlight the ways in which this paper raises important issues about the role of databases in healthcare (and other areas). Databases are significant for this study, because they mediate so much of modern healthcare. Classifications and standards are important, because standard representations of classified items are needed in order to enter information into a database. For this reason, the classification of work activities became a key area for debate between nurses and hospital administrators. But even if some administrators believed that something not represented in any database was important, they would still have difficulty in justifying this belief unless relevant figures could be included in the reports that are read by administrators higher up the "chain of translations." However these reports are generated by application programs that take their data from the hospital databases, so that they cannot include details about the work of nurses if they are not in these databases.

Many facets of an organization's life are reflected in its databases, including the non-representation of certain features. The reason the nurses wanted to get their concerns into the hospital databases is that there is a tendency to regard only what is explicitly represented in such databases as "real," with the rest being implicit, or in the terminology of Bowker and Star, relegated to an invisible infrastructure. That which is not explicitly represented will have trouble getting the attention that it may deserve. On the other hand, some groups of nurses oppose the NIC on the grounds that not being represented gives them more flexibility, also noting that classifications and standards provide a basis for more detailed and oppressive monitoring of their work, and that high status groups, like doctors, are in general subject to less detailed description and supervision.

There is also a tendency for database intensive organizations to resist change, and hence to freeze a status quo, because it can be very difficult to change the structure of a large database once it has been deployed; hospital databases are some of the best examples one can find of legacy systems. The difficulty of changing database strucuture also implies that any associated classification schemes and standards will be difficult to change. Moreover, mechanistic and reductionist views of organizational operation tend to be reinforced, because they are easier to implement in a database and its application programs for analysis and reporting, than would be the more "holistic," "humane," or "ecological" views that the nurses might tend to favor; for the same reason, quantification is reinforced.

The view that computer systems tend to foster institutional inertia rather than institutional change is also made in a handout, The Myth of the Computer Revolution, by Neville Holmes, IEEE Computer, November 1998, pp 121-122. (Although Holmes sounds like a bit of curmudgeon, his piece is fun and easy to read; he makes his points clearly, although he tends to overgeneralize, and his arguments aren't always very tight.)

7.4 Information Technology "on the Fringe"

Last summer (9 September 1999), I participated in a panel discussion at a conference in Buenos Aires, Argentina, on information technology in developing nations. The panel was entitled "Information Technology on the Fringe," and during my short presentation, I used ANT to clarify (I hoped) some terms that are often used in discussing this issue.

It turned out that the word "fringe" refered here to what are often called "developing" countries, and sometimes called "second world" countries, among which Argentina may be included. (It is interesting to notice that these terms are all euphemsms, used instead of something crude like "poor country," and that "fringe" is a new euphemism.) However, the term "fringe" is suggestive, and can be given a fairly precise meaning, by saying that it refers to geographical areas where the density of links in the relevant network is low-ish, but not very low (being very low would bring us into "undeveloped" or "third world" countries). So Silicon Valley, with its very high connectivity, is definitely not fringe, nor is the Pacific Ocean, with its very low connectivity. (Actually, the word "fringe" makes the most sense if there is a sudden drop in density, rather than a smooth gradual drop.)

For two other examples, the term "appropriate technology" can be defined as a technology the required links of which will fit in well with links that are already in place; those existing links are then considered "infrastructure" for the new technology, again relative to the network that is appropriate. For example, PCs need reliable electrical power, good repair technicians, quickly available spare parts, and a reasonable telephone system. ("Appropriate technology" is often recommended as a powerful guideline for introducing technology into developing countries, following the work of E.F. Schumacher, well known as author of the book Small is Beautiful.)

It is important here that both the technology and its context are represented as networks, so that we can talk about the relationships between them; it is also important that these networks are heterogeneous, including both human and non-human actors. Of course, my definitions are no big deal, and in particular, they are not very precise by scientific standards. Moreover, following the discussions in Section 7.2, there will often be problems with applying them in practice. But they can bring a greater degree of precision than is usual to discussions of this important topic, by encouraging us not to ignore the infrastructure that is generally invisible in developed countries, and to include both human and non-human agents in that infrastructure.

Discuss Baudrillard and "the spectacle" here.

7.5 So What?

It seems that one can see certain errors repeated again and again in information technology businesses. One of these is making an overly ambitious and overly precise business plan, and then trying to follow it to the bitter end. This is particularly common in startups, which by their nature are often committed to going all out after an ambitious goal. But what we have learned from actor network theory suggests that business plans should avoid being overly committed and precise, and instead should include contingency planning: they should sketch and cost out one or more scenarios that seem, at that time, the most plausible, and explicitly budget for replanning at a certain point, where the most plausible scenarios will again be sought. We all know that IPOs are a gamble, and that this gamble usually fails; this empirical fact can be seen as a good argument for the impossibility of making precise predictions about the social effects of technology.

Anyone who has worked in the computer industry, and especially in software development, will have seen many instances of the phenomena described by actor network theory, and will also have seen many instances of the kinds of myth and foolishness that it is capable of exposing, including naive optimism, hagiography, and technological determinism. In my opinion, a careful contemplation of actor network theory, including a number of good case studies, would be excellent preparation for high technology managers.

7.5.1 Simplified Guidelines

Here are some hints on how to use ideas from ANT in a "quick and dirty" style that may help in resolving business decisions:

  1. Make a list of the most important actants, being sure to include both humans and non-humans (e.g. institutions, equipment, standards, regulations - things that are important influences, constraints, allies, enemies, etc.)
  2. Describe the roles played by each actant, and also significant other roles that they might be able to play.
  3. Work out the most important relations among these actants, and sketch the resulting sociogram; this will often lead to discovering more actants and further relationships, and so on recursively. Think about what translations are going on, and more generally, what ongoing work is being done to maintain these links.
  4. Look for instances of infrastructural submersion, e.g., work done by "low level" people, systems taken for granted. etc.
  5. Think about possibilities for conflict, ambiguity and instability, as well as for cooperation; annotate the sociogram with most the important of these.
  6. Think about the possible evolution of the network; if some scenarios seem especially important, sketch sociograms for possible future states.
  7. Try out your analysis on colleagues; important new ideas will often arise in the discussions that result from this process.

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Last modified 5 November 2000