Abstract
AbstractThis chapter lays out some necessary context for the book by examining how the problem it addresses first came about as systems design encountered the need to engage more concretely with the social. We start by looking at the interdisciplinary character of work in systems design and how Human Computer Interaction (HCI) arose as an area of interest within it. A point of particular focus here is how systems design has mistakenly presumed social science to be a relatively univocal affair whereas, in fact, it contains a concatenation of different voices. A naïve conflation of ethnography and social science therefore overlooks the contested character of ethnography within social science itself. Thus, when called upon to consider ‘new’ approaches to ethnography design is therefore confronted with a choice between a number of divergent perspectives upon the social. Much of design’s engagement with the social to date has been through collaboration with ethnomethodologists, who locate expertise in the social milieu. This contrasts with ‘new’ approaches, which locate expertise in the long-standing traditions of social science. This being the case we seek to highlight the real nature of the choice designers are being asked to consider. In the ethnomethodological approaches that characterise much of design’s early engagement with the social, the expertise design is being asked to engage with is the expertise of the members of society themselves who populate the settings that are investigated for design purposes. By contrast ‘new’ approaches, built upon traditional understandings of ethnography within social science, invite design to engage with the social scientist as expert, where the goal is to replace members’ expertise with the theoretical and conceptual machinery of social science.KeywordsSocial ScienceSystem DesignSocial OrderRequirement EngineerComputer Support Cooperative WorkThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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