Ask someone “how are you?” and answer honestly, in detail, about your actual physical and emotional state, and you’ll watch a normal social exchange come apart at the seams. Nobody told you the real rule — that “how are you?” is usually a greeting formula expecting “fine, thanks,” not a genuine medical inquiry — and yet everyone fluent in the culture already knows it. Those unstated rules, the ones so obvious they’re invisible until someone breaks them, are exactly what a field called ethnomethodology was built to study.
The Study of Ordinary Sense-Making
Sociologist Harold Garfinkel coined the term ethnomethodology in the 1960s from “ethno” (the people) and “methodology” (methods) — literally, the methods ordinary people use, moment to moment, to make sense of situations and recognize them as orderly, normal, and meaningful. Rather than treating social order as something imposed from outside — laws, institutions, formal rules — ethnomethodology treats it as something people continuously produce themselves, through countless small, usually unnoticed interpretive acts: recognizing a queue as a queue, reading a pause in conversation as a signal to speak, knowing without being told which version of “fine” a greeting is asking for.
This is closely related to how linguists think about pragmatics — meaning built from context and shared expectation rather than from words alone — except ethnomethodology asks the question about social behavior generally, with talk as one especially rich example.
Breaching Experiments
Garfinkel’s most famous method for revealing these invisible rules was to deliberately break them and watch what happened. In his so-called breaching experiments, he had students do things like respond to an ordinary greeting with pedantic literalism — asked “how are you?”, answering “how am I in regard to what? My health, my finances, my school work?” — or act like a polite boarder in their own family home for an evening. The results were rarely dramatic; mostly they were small, and telling: confusion, irritation, accusations of being weird or rude. The strength of people’s reactions to a minor, harmless violation was itself the evidence — proof of how much invisible, shared interpretive work normally holds an interaction together without anyone noticing it’s happening.
From Sociology to Screens
This is the tradition researcher Lucy Suchman drew on directly when she set out to study why people struggled with an “intelligent” 1980s office photocopier, work published in her 1987 book Plans and Situated Actions. Rather than treating the users’ confusion as user error, or the machine’s failure as a simple bug, Suchman applied an ethnomethodological lens: she asked what invisible, taken-for-granted interpretive work people normally rely on to make sense of an interaction — and then showed exactly where a machine’s design failed to support that work. That approach, combined with close analysis of recorded conversation in the tradition of conversation analysis, let her show precisely why a system that looked “smart” on paper kept breaking down with real users doing real, situated things.
Why This Approach Still Shapes Tech Design
The direct line from Garfinkel’s sociology to Suchman’s human-computer interaction research is still visible in how serious technology design gets done today. Contextual inquiry, ethnographic field research, and usability testing that watches people use a product in their own environment rather than asking them to describe their behavior afterward — all of it descends from the ethnomethodological premise that people’s actual, situated methods for making sense of things are worth observing directly, because they won’t otherwise be visible or reportable in the abstract.
What This Means for You
Across this series, the throughline has been the same: communication, whether between two people or between a person and a machine, depends on an enormous amount of invisible, shared interpretive work that’s easy to overlook precisely because it works so well, most of the time. Ethnomethodology is the discipline built specifically to notice that work — and Lucy Suchman’s application of it to computers is why, forty years later, we have a genuine vocabulary for describing exactly why a device can seem to speak your language and still miss what you mean.