In his foundational 1955 article “The Structural Study of Myth,” Claude Lévi-Strauss outlined the program for a structuralist, cross-cultural study of mythology. The basic premise is prototypical structural anthropology: to analyze myths, one must decompose them into their constituent units (or “mythemes”). Thus decomposed, hidden mythical patterns can be made evident. These patterns are the real “content” of myths, according to Lévi-Strauss — they persist across different tellings of the same myth, and they reflect the inner structures of the mind. More important for the structuralist project, they recur in different myths, cross-culturally, reflecting the psychic unity of mankind.¹

Lévi-Strauss’s notecards (1955:435)

Materially, such a structural analysis required note cards. With a mytheme on each card, they could be physically rearranged into a two-dimensional grid, with the rows and columns indicating their shared features.² However, there was a problem. As Lévi-Strauss writes:

At this point it seems unfortunate that, with the limited means at the disposal of French anthropological research, no further advance can be made. […] A variant of average length needs several hundred cards to be properly analyzed. To discover a suitable pattern of rows and columns for those cards, special devices are needed, consisting of vertical boards about two meters long and one and one-half meters high, where cards can be pigeon-holed and moved at will; in order to build up three-dimensional models enabling one to compare the variants, several such boards are necessary, and this in turn requires a spacious workshop, a kind of commodity particularly unavailable in Western Europe nowadays. (443)

This sudden concern for materiality is striking in contrast to Lévi-Strauss’s focus on the abstract structure of mind. According to him, the progress of structuralism is very literally halted by the size of his office! Compounding the problem of proliferating notecards was the proliferation of analytical dimensions. Two or three dimensions could be grasped intuitively and physically, but beyond that, “progress in comparative mythology depends largely on the cooperation of mathematicians who would undertake to express in symbols multi-dimensional relations which cannot be handled otherwise” (436). Computers offered a kind of conceptual space that could substitute for physical space: “as soon as the frame of reference becomes multi-dimensional […] the board-system has to be replaced by perforated cards which in turn require I.B.M. equipment” (443).

Although Lévi-Strauss did not use computers as tools, he used them to imagine the future of structuralist analysis — the recovery of deep patterns from expanding corpora of mythological material, arrayed in dimensions that could only be grasped with the aid of computers. The putative ability of computers to handle boundlessly large data sets and multidimensional relationships between symbols reflects Lévi-Strauss’ structural ideal: the incorporation of all mythological material into a single analysis, sorted along all possible axes. By collapsing boards, cards, and multiple dimensions into a single figurative device, the imagined computer allows Lévi-Strauss’ ideal method to exist, in theory.

Edmund Leach on the computer

In his 1961 Rethinking Anthropology, Edmund Leach focused on a different connection between structuralism and computing: their reliance on binary opposition.

If an engineer tries to explain to you how a digital computer works he doesn’t spend his time classifying different kinds of nuts and bolts. He concerns himself with principles, not with things. He writes out his argument as a mathematical equation of the utmost simplicity, somewhat on the lines of: 0 + 1 = 1; 1 + 1 = 10. (6-7)

In Leach’s imagination, the particularities of actual computers do not matter—they provide a system in which unfathomable (or perhaps simply unfathomed) complexity is spun out from the purest of binaries. This style of explanation, Leach argues, is useful for understanding “what goes on in society, how societies work” (6) and the potency of binary codes: “although the information which can be embodied in such codes may be enormously complex, the basic principles on which the computing machines work is very simple” (7).³ Although imagining culture as 1s and 0s may be “frivolous” (7), Leach nonetheless endorses a kind of mathematical formalism:

The merit of putting a statement into an algebraic form is that one letter of the alphabet is as good or bad as any other. Put the same statement into concept language, with words like paternity and filiation stuck in the middle of it, and God help you! (17)

Algebra — the substitution of variables for constants, so as to describe forms and relationships — allows Leach to think that he can avoid the tangles of “concept language,” purifying cultural heterogeneity into fundamental relationships or topologies. Variables, the language of mathematics and computation, provide the figures Leach desperately wants, neither “good or bad,” but purely symbolic — a status notably unavailable to empirical cultural facts, which tend to be tangled up in all sorts of complicating webs.

To use the ultimate anthropological cliché, we might say that for Leach and Lévi-Strauss, computers proved “good to think.” They served not as tools for calculating, but as tools for thinking about mythical, social, or cultural orders. As computers grew in influence and popularity over the course of Leach’s career, he regularly returned to them as models of mind, society, and culture. In his book on Lévi-Strauss (1970), Leach himself suggested that computers functioned totemically for scientists like classes of animals did for “primitive thought”: as symbolic structures people could use to “make sense of the events of daily life by reference to codes composed of things outside themselves” (95).

The structuralist engagement with computing inaugurated a number of enduring themes for the use of computers in anthropology:

1. Computers frequently function as both tools for studying and metaphors for thinking about objects of anthropological interest, be they minds, social rules, cultural knowledge patterns, or ecological systems.
2. Computers, figured as indefatigable calculating machines, help to imagine promising futures for labor-intensive formal analyses: large-scale data collection and complex symbolic operations are made more plausible by the assumption that imminent technologies will make them easier.
3. Computational methods (or in this case, the imagination of them) draw anthropologists into interdisciplinary methodological discussions about science, systematicity, and rigor: for Lévi-Strauss, this was primarily with mathematicians (see Andre Weil’s mathematical appendix to The Elementary Structures of Kinship); for Leach, with software engineers (Leach was fond of tracing his approach to anthropology back to his own training as an engineer).

Without engaging computation practically or materially, Leach and Lévi-Strauss mine it symbolically for homologies. If computers can spin great complexity out of simple binaries, why not culture? If “explanation” can be reduced to a statement of fundamental principles for the computer, then why not for society? The fact that their computer is an imagined one makes the homology all the more powerful: Leach can think that computers are only about 1s and 0s and Lévi-Strauss can imagine them freeing up the space in his office, working with pure and decontextualized symbols, because these computers do not exist. There is no hot room full of engineers, troubleshooting, coding, and constructing the image of purity and unflappable logic that appears in these texts. The computer, for Leach and Lévi-Strauss, is just an object to think with, providing a decontextualized, rigorously symbolic, and tirelessly iterating model of structuralism taken to its logical limits.

The fundamental requirement of anthropology is that it begin with a personal relation and end with a personal experience, but […] in between there is room for plenty of computers.
– Claude Lévi-Strauss, epigraph to The Use of Computers in Anthropology ¹

Recent years have seen the growth of what we might call “alternate universe anthropology.” People with little or no training in anthropology are taking on big sociocultural questions, and they’re doing it with computers. We find PhDs in Electrical Engineering trying to algorithmically define musical genres, computer scientists modeling family ties in social networks, and autodidact software developers designing “content discovery” apps around their own theories of cultural influence and flow. If sociocultural anthropology didn’t already exist, people might reasonably assign the name to this stuff.

To academically-trained anthropologists, these computery projects can seem like they come from another planet. Anthropology, we know, is the stuff of notebooks, close friendships, and handkerchiefs tucked into your glasses. The social theories that pop out of companies like Facebook and the cultural analyses produced under the banner of big data are typically objects of scorn among anthropologists. We do not see them like we might see the “cultural” theories of members of an Amazonian tribe or the “social” theories of members of an ethnic enclave in southern Europe. We see them as simply wrong.

However, the fact that we have competition in producing accounts of culture and society should be no surprise: as Nicholas Thomas has written, “the objects of anthropological knowledge […] have never been exclusively anthropology’s own.”² One could argue that the defining epistemic feature of sociocultural anthropology is its necessary coexistence with competing explanations, both from the people anthropologists study and the others who study them.

I conduct my own fieldwork with the developers of algorithmic music recommender systems in the US (think Pandora, iTunes Radio, etc.), and my goal is to investigate their theories about “culture,” how they think about those theories, and how they mediate between the idea that culture is intrinsically subjective while algorithms are intrinsically objective. Trying to relate stories from the field to other anthropologists, I find that we tend to see this cultural theorizing as the work of uneducated interlopers who are solely driven by economic or technical concerns. There are some serious issues with this situational suspension of anthropology’s trademark interpretive charity (Do we really think that engineers have succeeded in becoming homo economicus or that their theories of culture are simply errors to be dismissed?), but one of the most vexing is the idea that these knowledge projects, because they are essentially computational, are not really “anthropological.”

This is a case of selective memory: For nearly as long as computers have existed, there have been anthropologists making use of them.³ In my attempts to make sense of the knowledge practices I encounter in the field and to remind my own discipline that computers did not arrive from some distant land to cause us trouble, I’ve been studying the history of computing in sociocultural anthropology. Although much has changed in terms of hardware, software, and popular imaginaries about computers since we started messing around with them in the 1950s, there are some remarkably persistent debates that keep popping up — about formalism, quantification, and the division of research labor, among others. In many cases, computers were embraced by parts of the discipline that were later disavowed by the mainstream as we moved down a more symbolic, interpretive, literary path.

Returning to some of our past disciplinary engagements with computers might help us think about how we imagine the boundaries of our discipline, and it can help us make sense of this strange world of “alternate universe anthropology,” where ideas about culture we’ve cast out have been picked back up or reinvented. Over the next two weeks, I’ll be posting a series of sketches from this history. They are by no means exhaustive, and they are missing plenty of interesting work,⁴ but I think they are instructive. I hope that you, dear readers, will take to the comments to point out gaps and oversights and, hopefully, to share your own histories and experiences from the trading zone between computers and anthropologists.

A hint of what’s to come:

• Structuralism: Thinking with Computers: Structuralists like Claude Lévi-Strauss and Edmund Leach were fascinated by digital computers both as metaphors for cultural processes and as tools which might fulfill structuralism’s methodological promises.
• Ethnoscience: Being Scientific with Computers: As the scientific standing of sociocultural anthropology was debated in the post-war period, computers became tied up in broader debates about the merits of quantitative and formal methods.
• Cultural Ecology: Modeling with Computers: For cultural ecologists and cyberneticians, analog computers offered models for feedback systems in the mind and the environment.
• Personal Computing: Ordinariness and Materiality: The introduction of the personal computer allowed computing to happen in the field, which led to a number of new problems regarding dirt, humidity, and the typing up of field notes.
• Computing: From Method to Object: At the close of the 1980s, as computers moved into anthropologists’ traditional field sites and those field sites expanded to include “high tech” settings, computers shifted from being primarily a tool to being an object of study in their own right. With computers as both objects of and tools for anthropological inquiry, we are thrust into the clutches of reflexivity, and hopefully it is not all that bad.