Human centered systems in the perspective of organizational and social informatics -- Rob Kling

Human Centered Systems in the
Perspective of Organizational and Social Informatics [PDF]

Rob Kling Center for Social Informatics School of Information and Library Science 10th and Jordan, Library 012 Indiana University Bloomington, IN 47405-1801	Leigh Star Department of Communication University of California, San Diego 9500 Gilman Drive La Jolla, CA 92093- 0503

Published in: Computers and Society 28(1)(March 1998):22-29

1.0 Introduction
In 1993, the term "digital libraries" was popularized when it became the focus of a $24 million research program jointly sponsored by ARPA, NASA, and NSF. Many computer scientists, in fields such as human-computer interaction, artificial intelligence, information retrieval, and information systems, who had not previously been concerned with the design of libraries became keenly interested in this research opportunity. Imaginative entrepreneurial computer scientists and information scientists soon began organizing research conferences on digital libraries, and a new field was soon born.
The example of digital libraries is but one example where a coalition of research agencies (or even a single agency) effectively initiate new fields and even name them. In 1997, there were several sustained discussions within the NSF about organizing research around new field labels -- "human centered systems" and "knowledge and distributed intelligence." Terms like these emerge from informal discussions between research program directors and members of the research communities whom they fund. Sometimes the terms have significant intellectual or institutional histories while sometime they are neologisms. It is common for the NSF to try to flesh out meaningful research agendas for such new fields by organizing workshops of scientists with relevant interests. The following article is a portion of a report that was part of these efforts.
The Committee on Computing, Information, and Communication of the National Science and Technology Council identified five components for a High Performance Computing Program, and referred to one of them as "Human-Centered Systems." HCI specialists, Prof. Jim Flanagan of Rutgers and Prof. Tom Huang of the University of Illinois - Urbana-Champaign were invited by program directors of NSF's Division on Information, Robotics and Intelligent Systems to organize a research workshop in February 1997. The label for the new field was called Human Centered Computing, Human Centered Systems, and Human Centered Intelligent Systems in the various stages of planning. A steering committee of 13 members (including Rob Kling and Leigh Star) met in November 1996 and developed some key themes and structures for the February workshop. There were to be a number of invited speakers and four thematic groups; each group would produce a section of the final report. One group, led by us, focused on the organizational and social analysis computerization (called organizational and social informatics and described in much more detail at http://www.slis.indiana.edu/SI). Its members included Sara Kiesler, Phil Agre, Geoffrey Bowker, Paul Attewell, and Celestine Ntuen. Phil Agre played an important role in moderating the groups' meetings.
The term "human centered automation," which is one of the intellectual roots of the term "Human Centered Systems," has been advanced within the field of human factors to refer to system that are (1) based on an analysis of the human tasks that the system is aiding (2) monitored for performance in terms of human benefits (3) built to take account of human skills and (4) adaptable easily to changing human needs. This conception emphasizes specialized technologies with human operators, including aircraft, advanced weapons systems, telemedical systems, and various kinds of control rooms. The organizational and social informatics group saw the value of a concept, such as human-centered systems in a broader perspective and ways to conceptualize the term were a major part of our deliberations and a key part of our report.
What follows is a portion of the report from this group, Chapter 5 of Human Centered Systems. The complete report, which includes descriptions of the participants, can be found at http://www.ifp.uiuc.edu/nsfhcs/.
2.0 When Should Computer Systems be Called Human Centered?
We began our group discussions by examining the term "human centered" and tried to characterize it clearly. We were specially concerned that the term "human centered" could easily become a trivialized buzzword that could casually be slapped as a label onto any computer application that seemed to help people. We did not believe that certain kinds of applications, such as medical diagnostic aids, should be automatically be called human-centered because improved medical diagnosis can help people. For example, a medical diagnostic system whose logic is difficult for a doctor to comprehend or interrogate would not be very human-centered.
Thus, we spent considerable time answering these questions:
What are the meanings of human-centered that justify a new label? What research questions would there be? What do we know about the organizational and social aspects of computer systems that sheds light on human centered systems developments? The following paragraphs summarize our deliberations.
There is no simple recipe for the design or use of human-centered computing. Our group agreed, however, that the analysis of any aspect of systems should take into account at least four dimensions of human-centeredness:
1. There must be analysis which encompasses the complexity of social organization and the technical state of the art. The analysis cannot be based upon a vague idea of what a generic individual would like, sitting at a keyboard in social isolation or in a stereotypic situation that effectively ignores the varieties of concrete social locations.
The computing world has developed a number of such generic scenarios, such as 4A -- in which any one can get any document anytime and anywhere. There are instantiations of 4A -- such as providing any researcher all of the documentary materials that they want for their research, even if they are traveling for a month; or providing any doctor with a complete medical record for any patient, anytime, anywhere. We can appreciate the practical value and symbolic power of these crisply stated goals. But they too easily trivialize the concept of human-centered system by homogenizing people and places into "everyman" and "everywhere." The various roles that people play in work groups are ignored and stereotyped. The ways that organizations structure information is also treated only as a barrier, unless materials are accessible 4A. The different kinds of resources (and skill sets) of organizations and groups are also all homogenized in 4 A scenarios.
In contrast, a human centered analysis must take account of varied social units that structure work and information -- organizations and teams, communities and their distinctive social processes and practices.
2. Human-centered is not a "one-off" or timeless attribute of a system at a given point in time. Rather, it is a process, one which would take into account how criteria of evaluation are generated and applied, and for whose benefit. It would include the participation of stakeholder groups -- such as involving patient groups in the development of specialist medical technologies, or teachers in the development of instructional technology.
3. There are important architectural relationships, such as the question of whether the basic architecture of the system reflect a realistic relationship between people and machines. As with the architecture of buildings, the architecture of machines embody questions of livability, usability and sustainability.
4. The question of whose purposes are served in the development of a system would be an explicit part of design, evaluation and use. Thus the question of whose ideas get put into the design process is an important one for human centered systems. As well, the question of whose problems are being solved is important -- systems which seek only to answer a very narrow technical or economic agenda or a set of theoretical technical points do not belong under the "human centered" rubric.
2.1 What is and isn't HCS
There is no single recipe for human centered design. Given that humans are so diverse, by nature human centered designing tends to be tailored, rather than mass produced. "One size fits all" seems distinctively non human-centered. On the other hand, we don't believe that complete tailorability results in human centered systems, because few people have the time or interest to effectively learn how to tailor thousands of features in complex computer systems.
The question of what is and isn't HCS may be divided into four parts:
1. What do we mean by human?
2. What is a system?
3. What are the goals of a human-centered system or process?
4. What are the processes associated with HCS?'
2.2 What do we mean by human?
We use the word human to mean a person with activities who participates in some work worlds, communities outside of workplaces, and a life world. We don't use the term human to refer to a disembodied task, or to a set of cognitive processes. Humans are not divisible up into component parts such as tasks. Thus, a design which optimizes for performance of a data-entry task but which does not take into account ergonomics, organizational reward structures, and the other tasks, activities and feelings a person brings to the job is not effectively taking the human into account.
People are not stand-alone organisms -- we are quintessentially social and collective, not just individuals -- or individuals in a diffuse social world. We do not use the term "human" to refer to individuals working alone or to a set of cognitive activities. For use, the term human includes and goes beyond individuals and their cognitions to include the activity and interactions of people with various groups, organizations, and segments of larger communities. Thus, for example, we would view the appropriate communication systems to support distance education to be those which students to communicate with instructors and with each other, and not simply to download files and upload from an instructional site. Further these systems should be organized in ways that fit students' life worlds (ie., not require forms of connectivity that students could not sustain at home) and also enable communicants to develop some knowledge of and trust in each other.
People adapt and learn, and from the point of view of systems design, development and use, it is important to take account of the adaptational capabilities of humans (Dervin, 1992). Something that freezes at one development stage, or one stereotyped user behavior, will not fit a human centered definition.
Finally, it is worth noting that human systems are just as complex as technical systems (if not more so!). That is, although there is often a "it's common sense" approach to defining what is human and what human problems and challenges should be, the answers are no less complex than building a highly complex technical system.
2.3 What is a (more) Human Centered System?
Having characterized the meaning of "human," we can then better characterize human-centered systems?
First, design predicated on merely replacing human activity or automating is not human centered. That is, systems which do this may be interesting, but are not per se human centered -- in fact they may act to the detriment of humans in particular situations.
Human-centered systems are designed to complement humans skills. The impetus to build such systems are based on human needs, for information, assistance, or knowledge. We recognize that the conditions under which people use such systems vary considerably. An aircraft navigational system might remove significant control from a pilot and use a logic that is difficult to explore when a plane is flying at 200 mph near ground and other planes. In contrast, a medical diagnostic system might have to be designed so that a doctor can examine how it weighed evidence and a rule-base to make a specific diagnosis.
HCS designers recognizes that computer systems structure social relationships, not just information. (For example, email systems that order messages for a person to read based on criteria such as recency or length also influence the recipients' social relationships by encouraging attention to some messages and their senders rather than others). So the analysis which informs design is not just about optimizing the technical capacities of the machines, but also recognizes and respects the organizations or other forms of human social organization (such as the family or the classroom) into which they are being inserted.
HCS design should take into account the various ways that actors and organizations are "connected together" with social relationships, as well as information flows and decisional authority. For example, changes in a classroom may produce changes in the students' families if children encounter new opportunities to explore ideas freely. While we can't predict all such outcomes, human-centered systems designers should be cognizant of the possibility via analysis of systems' use in some very realistic contexts.
2.4 What goals best describe a human-centered system or process?
The holistic attitude of Human-Centered systems designers toward a person and their life world is important. Since people are not reducible to a set of component tasks taken out of context, the strategies of Human Centered Systems design -- and technologies to support them -- should reflect this complexity.
There are two senses of the term "ecology" that illustrate this (Star, 1995b). The goals of a human centered system (or process) would be ecological in the sense of accounting for the larger picture of systems development and use. For example, displacing work does not make it go away. A system which is used to replace all the secretaries in a firm, while requiring extra hours of other employees to make up for the loss of services, has not accounted for the real organization of work. Fuller (1995) coined the term "cybermaterialism" to refer to the analytical approach in which the analyst is specially sensitive to the ways in which computerization reorganizes work and costs rather than simply reducing or eliminating them. As well, there are larger scale issues of infrastructure development, ethics and humaneness which are important; for example, the Computer Professionals for Social Responsibility guidelines for NII development suggest ethical as well as ecological approaches to infrastructure development that clearly have a place in discussions about human-centered computing (http://www.cpsr.org/cpsr/nii_policy).
Human Centered System designers would also ideally be ecological in terms of global concerns, and take into account issues of environmental sustainability. In this, by implication, we do not necessarily accept that only humans are important. A system which monitors acid rain or tree disease has wider natural implications as well.
The goals of a human centered system are not fixed once and for all, and then good for all contexts. People who user systems must be able to help define what they need systems to do (usually); it certainly means not just testing design when one is well down the design path, after it is too late for good user feedback. In this, we see a desirable shift from passive users of systems to more active participants in systems at all developmental phases.
Human Centered System designs must also scale up to become non-trivially human centered, and often here the values and implications for impacts change significantly. What works for a small group in a laboratory may entail larger scale issues which look different -- for example, privacy changes a great deal with larger groups, with lack of face to face accountability, and as systems move from the lab to the real world (Clement, 1994b). In this, the goals of human centered systems design should be congruent with social sustainability as well as environmental sustainability; analysis of policy and political implications especially with scale are important to defining a system's goals.
Finally, the system designers should use the best available social science knowledge in addressing all of these above points. Interdisciplinary teamwork is crucial to making this practice workable.
2.5 What are the processes associated with design, use and analysis of HCS?
How does one design, use and analyze human centered systems, according to the above precepts? Our group recommended several foci, including but not limited to the following:
a. One should take cognizance of multiple media (paper, computing, video, conversation, etc.) in the process of design. That is, information systems are always part of a large ecology of communicative devices and conventions, ranging from conversations to faxes and post-it notes. The interaction of these media is important for understanding the big picture of design in a human centered sense.
b. Human centered analysis would also extend to infrastructure and standards. That is, the usability of a system depends on infrastructural configurations of all sorts. Computers sent to a developing country without knowledge of the problems with its power grid and the dust-filled atmosphere may fail for reasons other than pure design; systems which work well for one group but violate existing standards in use for another will also not work.
c. Technology does and will not solve social justice problems. For example, putting more computers into inner city classrooms will not per se increase literacy. This is important to a human-centered approach, as is a certain modesty about systems capabilities. Sometimes "less is more", and the system which is helpful as a tool in solving a particular problem may not always be the most elegant technically. From a human centered perspective, 'pretty good systems' are sometimes the best systems.
d. Another part of human centered designing is articulating the values that are at stake in design processes themselves. This means examining the values of both designers and of the intended systems audiences and also being able to identify value-conflicts. This is only partly managed by user participation; it also requires ethics and values analysis for which it may be valuable to involve professionals who are very skilled in analyzing social values and social change.
e. Finally, in the design of human-centered systems, machinery should not be anthropomorphised. Machines should extending human capability as gracefully as possible. In line with the value of not simply replacing humans, human-centered system designers must know the limits of machines in a specific social order, and not impute certain human properties to them, such as fairness or objectivity.
3.0 State-of-the-art
We identified a body of research that is fundamental for anyone who wishes to understand how human centered systems can help or hinder organizations and social groups. In this brief review, we separate the research into five categories: evaluation and usability (including user centeredness); problems, paradoxes and overlooked social realities; organizational and group and community processes; co-design and design issues; and infrastructure, person power and training.
3.1 Evaluation and Usability (including user centeredness)
There is a large body of research on the evaluation of systems, interfaces, and usage at the individual level (see e.g. Bishop and Star, 1996; Hewins, 1990). Task analysis -- an individual system user and her tasks -- are also well understood. However, human centered systems have to be workable for groups. Some recent research has begun examine these issues at the group, organizational and community levels.
3.2 Problems, Paradoxes and Overlooked Social Realities
Much of the research about the social and organizational aspects of systems has pointed out actual and potential problems with design and use. In broad brush strokes, these include the following topics:
1. Computerization is ongoing, along with other organizational processes, rather than one-shot.
The computerization of common organizational activities, such as accounting, inventory control, or sales tracking, is not a one-short venture. Computerized systems that are introduced at one time are often refined over a period of years (Kling & Iacono, 1984), and periodically replaced by newer systems. Some computerized accounting systems have histories of 30 or 40 years (McKenney and Mason, 1995), and 10-20 years is quite common in manufacturing.
The decade-long time frame for the life of many computerized systems makes their adaptability to changing working and operational conditions an important aspect of human-centeredness (Zmuidzinas, Kling, and George, 1990). However, adaptability alone is not a sufficient condition for an information systems to be human centered. Software AG's SAP R/3 Enterprise Integration system is an interesting case in point. SAP requires that standards be set across an organization, but also allows many parameters to be tailored. Many large firms, including Corning, Compaq, Chevron, Borden, Owens-Corning, Mentor Graphics, Fujitsu, Dell, Apple, IBM and Microsoft are using SAP to help integrate far flung operations. It is common to have 8,000 data tables in an SAP database (Xenakis, 1996), and it is easiest for firms that have high levels of administrative centralization to decide upon parameters for geographically decentralized operations.
Because the customization is very complicated, some firms restructure the way that their people work and even their business policies rather than completely tailor SAP's R/3 (White, Clark, and Ascarelli, 1997). SAP is not a "human-centered system;" it is a strong example of an "organization centered system" that makes exceptional demands upon people to use it effectively. SAP is an interesting contrast to the kinds of Human Centered Systems (and design principles) that this research program should promote.
This discussion breaks new ground because we know relatively little about the conditions under which computer systems that are very human-centered also provide strong organizational support, and vice versa. Some readers have been surprised by our treating organizational-centered and human-centered systems as potentially very different. In our view, we will make more research headway by not automatically identifying human-centered with organizationally-centered (any more that we would say that all organizational structures and practices are always good for an organizations' employees, clients, etc.)
2. Neither technical excellence or market share alone define system survival. "Network externalities," on the other hand, can play a substantial role in the sustainability of system.
Economists have demonstrated the "path dependencies" associated with technical standards (Antonelli 1992). The analysis of these effects was inspired partly by the economics of telecommunications systems, in which subscribers often have an economic incentive to connect with the largest network (Cristiano, 1992). Computer users, likewise, often have economic reasons to adopt the dominant standards in information technology, even in cases where another standard might be preferable on narrow technical grounds. This phenomenon has profound consequences for the dynamics of competition in IT markets (Farrell and Saloner 1987), and consequently for policy as well (Kahin and Abbate 1995). Standardization also has broader economic consequences; research on business information (Bud_Frierman 1994; Bowker, Timmermans and Star, 1995), for example, has pointed to the mutual reinforcement between communication technology (which allows information to be transferred from dispersed locations to centralized offices), information technology (which increases the incentive to centralize information by making it easier to process), and the standardization of products and practices (which makes the various elements of accumulated information commensurable). The resulting economies of information ought to have pervasive consequences, although the nature and magnitude of these consequences remain controversial (Babe 1994).
Operating systems, such as UNIX or Microsoft Windows, were not necessarily the technically best alternatives when they were widely adopted. However, each of them was part of a larger matrix of social/technical systems and resources. UNIX was distributed as an "open system" to academic computer science departments whose technically inclined students were able to enhance it, and who sought it in the engineering labs and product development firms that employed them after graduation.
Microsoft Windows was, in some ways, technically inferior to IBM's OS/2. But the set of software companies that were willing to support Windows vastly outnumbered the number of firms that were willing to support OS/2. Neither of these observations about UNIX or Windows means that they were "poor technologies." Rather, we are noting that technologies become popular for reasons that are sometimes quite different from their technical strengths and weaknesses. Conversely, technologies can fall in popularity because of declining network externalities. For example Windows 95 is not quite as refined as the Apple Mac operating system; but Microsoft has out-marketed Apple in ways that lead software developers (and then the market) to shift away from Apple.
In a similar way to UNIX and Windows, SAP /R3 (and its enhancements) may become a commonplace Enterprise Integration system because of externalities, such as the extent to which consulting firms recommend it (White, Clark and Ascarelli, 1997) and offer training to help firms adopt it and tailor it.
3. There is a significant gap between the productivity that should result from the nation's investment in computer systems and the actual productivity gains in the economy.
The discrepancy between the expected economic benefits of computerization and measured effects has been termed "The Productivity Paradox," based on a comment attributed to Nobel laureate Robert Solow who remarked that "computers are showing up everywhere except in the [productivity] statistics."
Many analysts have argued that organizations could effectively increase the productivity of white collar workers through careful "office automation". There is a routine litany about the benefits of computerization: decreasing costs or increasing productivity are often taken for granted. In the last few years economists have found it hard to identify systematic improvements in United States national productivity which they can attribute to computerization. Although banks, airlines and other United States service companies spent over $750 billion during the 1980s on computer and communications hardware __ and unknown billions more on software __ standard measures have shown only a tiny 0.7 percent average yearly growth in productivity for the country's service sector during that time. (Productivity growth in many sectors of the United States economy was much lower since 1973 than between the end of World War II and 1973.)
In the mid-1990's, US National productivity has been closer to 2-3%/year. Macro economists see this as a workable growth rate, but it has also lead to income stagnation for many middle class families. It is also tiny relative to the 25%/year improvements in the cost/performance of computer hardware.
Research identifies many common social processes which reduce the productivity gains from computerization. Many changes in products and ways of work that come from computerization, such as improving the appearance of reports and visual presentations or managers being able to rapidly produce fine grained reports about their domains of action, often do not result in direct improvements in overall organizational productivity. Numerous accounting reports may give managers an enhanced sense of control. But managers may seek more reports than they truly need, as a way to help reduce their anxieties about managing. (SAP /R3, for example, can provide rapid access to transaction level detail about operational activities in diverse divisions of a multinational firm; a manager in San Jose California can readily track daily inventories in Munich and Melbourne).
Similarly, some professionals may be specially pleased by working with advanced technologies. But much of the investment may result in improving job satisfaction rather than being the most effective means for improving organizational productivity.
There are good diagnoses of the productivity process (and paradox) with respect to linkages between individual and organizational scale behavior (but not yet a clear solution)(See Harris et al., 1994; Landauer, 1995; Attewell, 1996).
4. Workable computer systems are usually supported by a strong socio-technical infrastructure.
The "surface features" of computerization are the most visible and the primary subject of debates and systems analysis. But they are only one part of computerization projects. Many key parts of information systems are neither immediately visible or interesting in their novelty. They include technical infrastructure, such as reliable electricity (which may be a given in urban America, but problematic in many Third World countries, in wilderness areas, or in urban areas after a major devastation.) They also involve a range of skilled-support -- from people to document systems features and train people to use them to rapid-response consultants who can diagnose and repair system failures. System infrastructure is a socio-technical system insofar as technical capabilities depend upon skilled people, administrative procedures, etc.; and social capabilities are enabled by supporting technologies (i.e., word processors for creating technical documents, telephones and pagers for contacting rapid-response consultants).
Much of the research about appropriate infrastructure comes from studies of systems that underperformed or failed (Star and Ruhleder, 1994; Kling and Scacchi 1982). The social infrastructure for a given computer system is not homogeneous across social sites. For example, the Worm Community System was a collaboratory for molecular biologists who worked in hundreds of university laboratories; key social infrastructure for network connectivity and (UNIX) skills depended upon the laboratory's work organization (and local university resources) (Star and Ruhleder, 1996). Star and Ruhleder found that the Worm Community System was technically well conceived; but it was rather weak as an effective collaboratory because of the uneven and often limited support for its technical requirements in various university labs. In short, lack of attention to local infrastructure can undermine the workability of larger scale projects.
There is a small body of research that amplifies these ideas. Web models of computing (which are not related to WWW) treat the infrastructure required to support a computerized systems as an integral part of it (Kling & Scacchi, 1982; Kling, 1992).~Star and Ruhleder (1996) have also shown that there are subtle individual and organizational learning processes underlying the development of local computing infrastructure (including the ability of professionals with different specialties to communicate about computerization issues) (see also Star, 1995b; Ruhleder, 1995 ).
3.3 Organizational, group and community processes
There is a solid body of empirical and theoretical work which identifies a variety of processes at scales above the individual. Among the points made in this research are the following:
1. Information sharing in groups can be supported by computerized systems, but organizational incentive systems play a major role in influencing the extent of information sharing.
One of the capabilities enabled by shared databases is the possibility of groups sharing data/information that was previously inaccessible in a timely manner, if at all. It is easy to identify examples, such as airline reservation systems where shared databases of seats on flights enhance the quality of service to passengers and the operational efficiencies of the airlines. Information sharing is technologically enabled by most computerized information systems; and some systems attract managers and professionals because of new kinds of information sharing that they enable. (For example, SAP /R3, as discussed above, can provide rapid access to transaction level detail about operational activities in diverse divisions of a multinational firm. Intranets seem to becoming popular for enhancing the flow of certain information across the boundaries of organizational subunits).
Much of the value of groupware applications, such as Lotus Notes, hinges on the promise of professionals' sharing narrative materials -- such as client studies in multi-office consulting firms, country-specific market-intelligence in multi-national firms, and software bug fixes in a vendor's technical support office. Careful research finds mixed support for the value of these applications (Orlikowski, 1993; Orlikowski, 1996, Ciborra and Suetens, 1996). Each of the studies just cited found some examples of Lotus Notes' use, but only staff in the technical support office made extensive use of Notes for routinely sharing information. In many consulting firms there is a negative incentive for consultants to share reports; they are rewarded for the time that they can bill to their clients and -- to some extent -- for demonstrating unique expertise (Orlikowski, 1993). Managers at a French (national) public utility company had hoped that their staff would use Lotus Notes to share information about market conditions, but they did not alter their organization's reward system to compensate for the time involved in creating online reports. While a pilot group was highly enthusiastic to share information via Notes, the project "lost momentum" as other groups were asked to participate (Ciborra and Suetens, 1996). In contrast, a small technical support workgroups in which technicians helped each other with problem call before they used Notes, found Notes to be a helpful extension of their preexisting cooperative practices (Orlikowski, 1996).
2. People who use computerized systems are often using multiple media.
Much of the writing about computerized systems tends to focus on the digital media that is part of the official systems design. But we know that people also other media, such as paper and telephone, as part of their work. In the case of digital libraries, some analysts take notes on paper about materials that they find on-line (Levy and Marshall, 1995). Scholars who read electronic journals often print out long articles onto paper for sustained reading and markup (Kling and Covi, 1995).
In an intriguing kind of example, air traffic controllers use paper "strips" for key information about flights in their sectors; and to share it when they pass control over an aircraft to a colleague (Stix, 1994). Stix (1994) article reports that recent efforts to develop a completely electronic flight control system lead to efforts to replace paper strips with unwieldy databases with dozens of fields.
3. The routine use of computer systems often requires articulation work
The concept of "articulation work" characterizes the efforts required to bring together diverse materials or to resolve breakdowns in work (such as clearing a paper jam when printing a long electronic document to read). In a provocative study, Gasser (1986) found that anomalies were common in many use of computer systems, and that professionals often developed informal (and sometimes strange) workarounds to compensate for recurrent difficulties. Suchman (1996) observes how articulation work is often invisible to people who are not close to the place and moment of working. She also notes that articulation work can require notable ingenuity, but that higher status professionals (and managers) who are buffered from the details of computer work, tend to trivialize the nature of the work to be done. To the extent that high status professionals and managers who can delegate most of their work to others are male, and that many of the clerical and technical staff who do the work are female, there is also a gender politics to articulation work. But Schmidt and Bannon (1992) argued that articulation work is so pervasive that (humanly) effective system designers have to routinely examine how new systems reduce, increase, or reorganize articulation work.
4. It is critical to comprehend the use of many computerized systems in terms of specific social units, such as workgroups, teams, local communities and communities of practice.
It is common for systems designers to conceptualize computerized systems in terms of organizations and individuals ("users"). But there are important intermediate levels of social organization between individuals and the larger collectivity. In practice, workgroups and teams (Galegher, Kraut and Egido, 1990; Ciborra, 1996; Tyre and Orlikowski, 1994) have proven to be critical social groupings which shape the use of computerized systems. (See below for some examples).
Brown and Duguid (1991) coined the term "communities of practice" to refer to people who are concerned with a common set of work practices. They are not a team, a task force, and not even necessarily an authorized or identified group. People in CoPs can perform the same job (but work in different places much of the time, such as field service engineers), collaborate on a shared task or work together on a product. They are peers in the execution of "real work." What holds them together is a common sense of purpose and a real need to know what each other knows. There are many communities of practice within a single organization and most people belong to more than one of them. Some research shows that communities of practice are the appropriate groups for learning how to best integrate new computer systems into real working practice (George, Iacono & Kling, 1995; Jones, 1995).
Local communities, as well, can be important units of analysis and frames of reference for human centered computing. "Community information systems" may mean organized information provision to special constituencies (e.g. cancer patients, small business owners, hobbyists), or it may be geographically local provision of services, including freenets and other public computing facilities. For more information on this, Prof. Ann Bishop has offered to share her syllabus from the University of Illinois for a graduate class, Community Information Systems (http://alexia.lis.uiuc.edu/gslis/courses/syllabi/450CI.html).
5. Communication is a key value for many users of computer system (even where that has not been an explicit or high priority goal).
For example, email was the "killer application" that drove up the use and demand for the Internet (in contrast with file transfer). Bullen and Bennett (1996) found that email was the most frequently used application within workgroups that used office suites that included group support functions (such as calendars).
6. There is an understanding of emergent social psychological processes when individuals work together in groups with computer networks
Social processes in groups that use electronic mail have been the subject of substantial research. We understand that email can reduce the contextual cues in messages (Sproull and Kiesler, 1991), and that flaming can result as a byproduct of people misunderstanding other's intentions. We also understand that people's who have on-going work relations can be very cognizant of social norms beyond those of the electronic workspace, and that these norms can reduce the frequency of phenomena such as flaming (Lea, O'Shea, Fung, and Spears, 1992). In some workplaces, people use email quite strategically (such as to convey bad news (Markus, 1994). There have been some systematic studies of the dynamics of groups online (see Sproull and Kiesler, 1991 for an introduction). One important finding is that email can gives greater visibility to "peripheral workers" -- those who are lower in social status, who work in distant location or in different time schedules that the more mainstream workforce (Sproull and Kiesler, 1991;, Hesse, Sproull, Kiesler, and Walsh, 1993). There is as well a related important body of work on scholarly communication which represents similar processes (Doty, Bishop, and McClure, 1991).
7. Information technologies may become a means of constructing and exploring individual, group, organizational and community identity.
Communication is not simply a matter of exchanging information. Studies of on-line communication show that people use them to construct certain identities (i.e., local technical expert), and in some cases, to explore new social identities (Mantovani, 1996).
3.4 Co-design and design issues
A more recent development in this research area is the partnership of social and computer scientists, particularly the participatory design or co-design thrust. Some findings from this area:
1. Designers design both system and shape the setting
The separation between system and setting can seem simple -- the system is the computer system (and telecommunications) and the setting is the arrangement of furniture, lighting, walls, and other facilities. In some cases, such as the design of cockpits and control rooms, teams explicitly design both system and setting. In other case, people reorganize their offices to more comfortably use computer systems -- pulling down Venetian blinds to reduce glare on computer screens, shuffling desktop materials to make room for monitors and printers, and so on. In both cases, computerization reshapes the use of space and the ways that people inhabit it.
2. Three-way partnerships (social scientists, designers, users) have been powerful ways to organize systems development
Some of partnerships have been pioneered in Scandinavia (Kyng and Greenbaum 1991; Clement and Van den Besselaar, 1993; B?ker and Gr?baek, 1996), but they have also been developed within major North American firms, such as Xerox and NYNEX (Euchner and Sachs, 1993; Clement, 1994a). Dutton and Kraemer's early work on negotiations about computer modeling also points to complex de facto processes of implementation, modification and the politics of design (1984).
4.0 Conclusions
This excerpt from the chapter on "Human Centered Systems
in the Perspective of Organizational and Social Informatics" conceptualizes HCS in richly social terms. It also identifies some key ideas from over 20 years of systematic research about computerization that help us understand how to design and implement more humanly-centered systems.
This workshop was followed up by additional NSF workshops on HCS. In addition, the subject of Organizational and Social Informatics was the focus of a special NSF workshop that was help at Indiana University in November 1997 (see http://www.slis.indiana.edu/siwkshop/SocInfo1.html). This workshop included about 25 specialists in Organizational and Social Informatics drawn from the fields of computer science, information systems, information science, sociology, and communication. They discussed key ideas in the field as well as ways to develop the field through expanded research, teaching, and communication with people in related specialty areas, as well as practicing professionals. A report from this workshop will be completed in the Winter 1998 and be available through the Social Informatics Home page (http://www.slis.indiana.edu/SI).
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