The social dimensions of computerization

摘要

While industrialized countries have been rapidly computerizing, the ultimate forms of computerization and their social consequences are still somewhat open-ended. The general directions of equipment developments have been relatively clear - toward computer-based systems which run on faster, smaller, and cheaper hardware; toward equipment architectures which distribute computing (and work); and software which is generally more flexible and more likely to support graceful interactions between person and machine. Computerization is more than placing computing equipment in offices, homes, boats, planes, automobiles, or shopping areas. Computerization refers to the social practices through which computer-based systems and services are made available to various groups, arrangements for training people in the variety of skills they need to use systems effectively, practices that alter accountability, changes in patterns of control, etc. Computerization is a combination of technical, social and political processes [12].

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Computerization touches the lives of millions of people in many key spheres of work, education, commerce, dealing with public agencies, etc. It is tempting to find some simple formula to summarize the consequences of computerization for people, groups, and the larger social order. Simple capsule formulas which concisely summarize a meaning for computerization tend to be deterministic and grossly oversimplified [11]. Our most reliable knowledge about the specific social consequences of computerization comes from careful field studies of specific computer-based systems in specific social settings [10]. There are a myriad of systems and settings and varied computerization practices employed throughout the industrialized nations. Moreover, analysts bring their own differing theoretical assumptions to their studies [6, 10, 22]. Consequently, the findings of research studies sometimes appear inconsistent [1, 10, 19, 21]. There are serious debates about whether computerization will naturally lead to better or worse jobs [4, 7, 8, 17, 23, 24], lead people to make better or worse decisions [20], lead work groups to be more or less flexible [17], reinforce or redistribute patterns of social power [3], make bureacracies less accountable to the public [2], etc.

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Much of the popular and professional discourse about the consequences and conditions of computer use is relatively deterministic. Deterministic stories can be optimistic [5] or pessimistic [7, 23]. During the last decade scholars have begun to develop some interesting explanatory models to help understand how computerization &ldquoworks"" as a social and technical process. Research on the social impacts of computing indicates that few "deterministic" consequences of introducing computer-based systems into social settings such as organizations [12, 18, 20, 25]. Under different conditions and different computerization strategies, jobs may become more or less skilled; work groups may gain or lose flexibility; decisions may be "better" or more confused; power may shift to or from central administrators, etc. Changes such as these depend upon both social and technical contingencies, such as: the kinds of systems introduced, who controls them, the kind of infrastructure devoted to their support, etc [17]. Computer-based systems which can be perfectable under static laboratory conditions and when supported by a rich array of resources may be very problematic when introduced into dynamic social settings, settings rife with social conflict, or when computerization strategies limit support resources. Contextual characteristics, such as these, are a powerful influence on the kinds of computer-based systems adopted, the ways they are organized, and their consequences for people and groups. As a consequence, the simple development of "good technologies" is not sufficient to insure that social life will be improved for many participants.

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This talk will examine some organizing ideas to help understand how computerization strategies and their outcomes depend upon the social contexts in which people sad groups enact them by introducing web models [14,18]. Web models examine the social context in which a computer-based system is adopted, developed, or used; they view the infrastructure for supporting a computer-based system as an integral element of its operational form; and they situate the computing developments being studies in light of the history of related computing developments and related social practices within key social settings. The examples for this talk will be drawn primarily from the computerization of workplaces.

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Web models help explain 1) the social leverage provided by computing arrangements; 2) the co-requisites for smoothly operating systems; and 3) the ways in which the social settings in which computing arrangements are developed and used shape their configurations and consequences.

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We contrast web models with conventionally rational "discrete-entity" models which are a-contextual, a-historical, and assume that adequate infrastructure can always be available as needed. Predictions of computing development sad use based on discrete-entity models usually underestimate the problems of implementation and underestimate the extent to which computer-based systems play important roles other than as direct aids in leveraging information processing capabilities in a work organization.

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Web models shed greater light on socially and technically complex, embedded computing developments than do discrete-entity models. At best, discrete-entity models account for some of the potential (dis)advantages provided by a new technology or organizational arrangements. Since they are context-free, discrete-entity models can be used to describe the results of many simple experiments. In discrete-entity analyses, all things being equal is the rule, while the social setting of technical development and use is largely ignored. That neglect is usually untenable when the organizational setting or the technology itself is complex. Even simple technologies may be compromised by complex, demanding settings [13].

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Web models draw "large" social boundaries around a focal computing resource so that the defining situation includes: the ecology of participants who influence the adoption and use of computer-based technologies, the infrastructures for supporting system development and use, and the history of local computing developments [3, 8, 13, 16].

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The social boundaries for a given computing resource can extend far beyond the work places where it is developed and used. Useful social boundaries contain work groups laced throughout a given organization and through other organizations on which the focal organization depends for resources such as staff, equipment, income, and legitimacy. These boundaries are often ir- regular in that they often do not conform to the formal boundaries of organizations and their subunits. They can also be idiosyncratic in that they differ from one organizational setting to another, even when thesame technologies are in use. Within these social boundaries, web models link computing developments to routine organizational activities and critical negotiations.

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Web models help explain the actual leverage of computing developments, their carrying costs, and the ways that systems are valued by different participants. Computer-based systems increasingly extend beyond the narrow boundaries of a work group or small scale organizational unit and are increasingly an element in more complex social relations. Consequently, discrete-entity models are becoming less relevant as a basis for guiding research on the social dimensions of computerization. Web models of computing appear especially appropriate when 1) the production or support of computer-based systems is socially complex or 2) their adoption or operation depends upon social relations that extend far beyond the behavioral setting in which the technology is developed or used. Web models examine the social simplicity/complexity of computing arrangements, not just their technical simplicity/complexity. As computer-based systems become more socially complex, web models will become increasingly critical as approaches for explaining the development and use of computing.