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- RISKS-LIST: RISKS-FORUM Digest Monday 11 January 1993 Volume 14 : Issue 24
-
- FORUM ON RISKS TO THE PUBLIC IN COMPUTERS AND RELATED SYSTEMS
- ACM Committee on Computers and Public Policy, Peter G. Neumann, moderator
-
- Contents:
- Organizational Analysis in Computer Science -- PART ONE (Rob Kling)
- [PART TWO is in RISKS-14.25.]
-
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-
- Organizational Analysis in Computer Science
-
- Rob Kling
- Department of Information & Computer Science
- University of California at Irvine,
- Irvine, CA 92717, USA
- kling@ics.uci.edu (714-856-5955)
-
- January 10, 1993 [Working Draft 11b]
-
- Note: To appear: The Information Society, 9(2) (Mar-Jun, 1993). A
- much shorter version of this paper will appear as "Computing
- for Our Future in a Social World" in Communications of the
- ACM, February 1993, in a Forum that discusses Computing the
- Future: A Broader Agenda for Computer Science and
- Engineering. Hartmanis, Juris and Herbert Lin (Eds).
- Washington, DC: National Academy Press, 1992.
-
-
- ABSTRACT
-
- Computer Science is hard pressed in the US to show broad utility to help
- justify billion dollar research programs and the value of educating well over
- 40,000 Bachelor of Science and Master of Science specialists annually in the
- U.S. The Computer Science and Telecommunications Board of the U.S. National
- Research Council has recently issued a report, "Computing the Future
- (Hartmanis and Lin, 1992)" which sets a new agenda for Computer Science. The
- report recommends that Computer Scientists broaden their conceptions of the
- discipline to include computing applications and domains to help understand
- them. This short paper argues that many Computer Science graduates need some
- skills in analyzing human organizations to help develop appropriate systems
- requirements since they are trying to develop high performance computing
- applications that effectively support higher performance human organizations.
- It is time for academic Computer Science to embrace organizational analysis
- (the field of Organizational Informatics) as a key area of research and
- instruction.
-
- INTRODUCTION
-
- Computer Science is being pressed on two sides to show broad utility for
- substantial research and educational support. For example, the High
- Performance Computing Act will provide almost two billion dollars for research
- and advanced development. Its advocates justified it with arguments that
- specific technologies, such as parallel computing and wideband nets, are
- necessary for social and economic development. In the US, Computer Science
- academic programs award well over 30,000 Bachelor of Science (BS) and almost
- 10,000 Master of Science (MS) degrees annually. Some of these students enter
- PhD programs and many work on projects which emphasize mathematical Computer
- Science. But many of these graduates also take computing jobs for which they
- are inadequately educated, such as helping to develop high performance
- computing applications to improve the performance of human organizations.
-
- These dual pressures challenge leading Computer Scientists to broaden their
- conceptions of the discipline to include an understanding of key application
- domains, including computational science and commercial information systems.
- An important report that develops this line of analysis, "Computing the
- Future" (CTF) (Hartmanis and Lin, 1992), was recently issued by the National
- Computing and Telecommunications Board of the U.S. National Research Council.
-
- CTF is a welcome report that argues that academic Computer Scientists must
- acknowledge the driving forces behind the substantial Federal research support
- for the discipline. The explosive growth of computing and demand for CS in the
- last decade has been driven by a diverse array of applications and new modes
- of computing in diverse social settings. CTF takes a strong and useful
- position in encouraging all Computer Scientists to broaden our conceptions of
- the discipline and to examine computing in the context of interesting
- applications.
-
- CTF's authors encourage Computer Scientists to envision new technologies in
- the social contexts in which they will be used. They identify numerous
- examples of computer applications in earth science, computational biology,
- medical care, electronic libraries and commercial computing that can provide
- significant value to people and their organizations. These assessments rest on
- concise and tacit analyses of the likely design, implementation within
- organizations, and uses of these technologies. For example, CTF's stories of
- improved computational support for modelling are based on rational models of
- organizational behavior. They assume that professionals, scientists, and
- policy-makers use models to help improve their decisions. But what if
- organizations behave differently when they use models? For example suppose
- policy makers use models to help rationalize and legitimize decisions which
- are made without actual reference to the models?
-
- One cannot discriminate between these divergent roles of modelling in human
- organizations based upon the intentions of researchers and system designers.
- The report tacitly requires that the CS community develop reliable knowledge,
- based on systematic research, to support effective analysis of the likely
- designs and uses of computerized systems. CTF tacitly requires an ability to
- teach such skills to CS practitioners and students. Without a disciplined
- skill in analyzing human organizations, Computer Scientists' claims about the
- usability and social value of specific technologies is mere opinion, and bears
- a significant risk of being misleading. Further, Computer Scientists who do
- not have refined social analytical skills sometimes conceive and promote
- technologies that are far less useful or more costly than they claim.
- Effective CS practitioners who "compute for the future" in organizations need
- some refined skills in organizational analysis to understand appropriate
- systems requirements and the conditions that transform high performance
- computing into high performance human organizations. Since CTF does not spell
- out these tacit implications, I'd like to explain them here.
-
- BROADENING COMPUTER SCIENCE:
- FROM COMPUTABILITY TO USABILITY
-
- The usability of systems and software is a key theme in the history of CS. We
- must develop theoretical foundations for the discipline that give the deepest
- insights in to what makes systems usable for various people, groups and
- organizations. Traditional computer scientists commonly refer to mathematics
- as the theoretical foundations of CS. However, mathematical formulations give
- us limited insights into understanding why and when some computer systems are
- more usable than others.
-
- Certain applications, such as supercomputing and computational science are
- evolutionary extensions of traditional scientific computation, despite their
- new direction with rich graphical front ends for visualizing enormous mounds
- of data. But other, newer modes of computing, such as networking and
- microcomputing, change the distribution of applications. While they support
- traditional numerical computation, albeit in newer formats such as
- spreadsheets, they have also expanded the diversity of non-numerical
- computations. They make digitally represented text and graphics accessible to
- tens of millions of people.
-
- These technological advances are not inconsistent with mathematical
- foundations in CS, such as Turing machine formulations. But the value of these
- formats for computation is not well conceptualized by the foundational
- mathematical models of computation. For example, text editing could be
- conceptualized as a mathematical function that transforms an initial text and
- a vector of incremental alterations into a revised text. Text formatting can
- be conceptualized as a complex function mapping text strings into spatial
- arrays. These kinds of formulations don't help us grasp why many people find
- "what you see is what you get" editors as much more intuitively appealing than
- a system that links line editors, command-driven formatting languages, and
- text compilers in series.
-
- Nor do our foundational mathematical models provide useful ways of
- conceptualizing some key advances in even more traditional elements of
- computer systems such as operating systems and database systems. For example,
- certain mathematical models underlie the major families of database systems.
- But one can't rely on mathematics alone to assess how well networks,
- relations, or object-entities serve as representations for the data stored in
- an airline reservation system. While mathematical analysis can help optimize
- the efficiency of disk space in storing the data, they can't do much to help
- airlines understand the kinds of services that will make such systems most
- useful for reservationists, travel agents and even individual travellers. An
- airline reservation system in use is not simply a closed technical system. It
- is an open socio-technical system (Hewitt, 1986; Kling, 1992). Mathematical
- analysis can play a central role in some areas of CS, and an important role in
- many areas. But we cannot understand important aspects of usability if we
- limit ourselves to mathematical theories.
-
- The growing emphasis of usability is one of the most dominant of the diverse
- trends in computing. The usability tradition has deep roots in CS, and has
- influenced the design of programming languages and operating systems for over
- 25 years. Specific topics in each of these areas also rest on mathematical
- analysis which Computer Scientists could point to as "the foundations" of the
- respective subdisciplines. But Computer Scientists envision many key advances
- as design conceptions rather than as mathematical theories. For example,
- integrated programming environments ease software development. But their
- conception and popularity is not been based on deeper formal foundations for
- programming languages. However, the growth of non-numerical applications for
- diverse professionals, including text processing, electronic mail, graphics,
- and multimedia should place a premium on making computer systems relatively
- simple to use. Human Computer Interaction (HCI) is now considered a core
- subdiscipline of CS.
-
- The integration of HCI into the core of CS requires us to expand our
- conception of the theoretical foundations of the discipline. While every
- computational interface is reducible to a Turing computation, the foundational
- mathematical models of CS do not (and could not) provide a sound theoretical
- basis for understanding why some interfaces are more effective for some groups
- of people than others. The theoretical foundations of effective computer
- interfaces must rest on sound theories of human behavior and their empirical
- manifestations (cf. Ehn, 1991, Grudin, 1989).
-
- Interfaces also involve capabilities beyond the primary information processing
- features of a technology. They entail ways in which people learn about systems
- and ways to manage the diverse data sets that routinely arise in using many
- computerized systems (Kling, 1992). Understanding the diversity and character
- of these interfaces, that are required to make many systems usable, rests in
- an understanding the way that people and groups organize their work and
- expertise with computing. Appropriate theories of the diverse interfaces that
- render many computer systems truly useful must rest, in part, on theories of
- work and organization. There is a growing realization, as networks tie users
- together at a rapidly rising rate, that usability cannot generally be
- determined without our considering how computer systems are shaped by and also
- alter interdependencies in groups and organizations. The newly-formed
- subdiscipline of Computer Supported Cooperative Work and newly-coined term
- "groupware" are responses to this realization (Greif, 1988; Galegher, Kraut
- and Egido, 1990).
-
- BROADENING COMPUTER SCIENCE:
- FROM HIGH PERFORMANCE COMPUTING
- TO HIGH PERFORMANCE ORGANIZATIONS
-
- The arguments of CTF go beyond a focus on usable interface designs to claims
- that computerized systems will improve the performance of organizations. The
- report argues that the US should invest close to a billion dollars a year in
- CS research because of the resulting economic and social gains. These are
- important claims, to which critics can seek systematic evidence. For example,
- one can investigate the claim that 20 years of major computing R&D and
- corporate investment in the US has helped provide proportionate economic and
- social value.
-
- CTF is filled with numerous examples where computer-based systems provided
- value to people and organizations. The tough question is whether the overall
- productive value of these investments is worth the overall acquisition and
- operation costs. While it is conventional wisdom that computerization must
- improve productivity, a few researchers began to see systemic possibilities of
- counter-productive computerization in the early 1980s (King and Kraemer,
- 1981). In the last few years economists have found it hard to give
- unambiguously affirmative answers to this question. The issue 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 (Dunlop and Kling, 1991a)."
-
- Economists are still studying the conditions under which computerization
- contributes to organizational productivity, and how to measure iteasy. But
- there is no automatic link between computerization and improved productivity.
- While many computer systems have been usable and useful, productivity gains
- require that their value exceed all of their costs.
-
- There are numerous potential slips in translating high performance computing
- into cost-effective improvements in organizational performance. Some
- technologies are superb for well-trained experts, but are difficult for less
- experienced people or "casual users." Many technologies, such as networks and
- mail systems, often require extensive technical support, thus adding hidden
- costs (Kling, 1992).
-
- Further, a significant body of empirical research shows that the social
- processes by which computer systems are introduced and organized makes a
- substantial difference in their value to people, groups and organizations
- (Lucas, 1981; Kraemer, et. al. 1985; Orlikowski, 1992). Most seriously, not
- all presumably appropriate computer applications fit a person or group's work
- practices. While they may make sense in a simplified world, they can actually
- complicate or misdirect real work.
-
- Group calendars are but one example of systems that can sound useful, but are
- often useless because they impose burdensome record keeping demands (Grudin,
- 1989). In contrast, electronic mail is one of the most popular applications in
- office support systems, even when other capabilities, like group calendars,
- are ignored (Bullen and Bennett, 1991). However, senders are most likely to
- share information with others when the system helps provide social feedback
- about the value of their efforts or they have special incentives (Sproull and
- Kiesler, 1991; Orlikowski, 1992). Careful attention to the social arrangements
- or work can help Computer Scientists improve some systems designs, or also
- appreciate which applications may not be effective unless work arrangements
- are changed when the system is introduced.
-
- The uses and social value of most computerized systems can not be effectively
- ascertained from precise statements of their basic design principles and
- social purposes. They must be analyzed within the social contexts in which
- they will be used. Effective social analyses go beyond accounting for formal
- tasks and purposes to include informal social behavior, available resources,
- and the interdependencies between key groups (Cotterman and Senn, 1992).
-
- Many of the BS and MS graduates of CS departments find employment on projects
- where improved computing should enhance the performance of specific
- organizations or industries. Unfortunately, few of these CS graduates have
- developed an adequate conceptual basis for understanding when information
- systems will actually improve organizational performance. Consequently, many
- of them are prone to recommend systems-based solutions whose structure or
- implementation within organizations would be problematic.
-
- ORGANIZATIONAL INFORMATICS
-
- Organizational Informatics denotes a field which studies the development and
- use of computerized information systems and communication systems in
- organizations. It includes studies of their conception, design, effective
- implementation within organizations, maintenance, use, organizational value,
- conditions that foster risks of failures, and their effects for people and an
- organization's clients. It is an intellectually rich and practical research
- area.
-
- Organizational Informatics is a relatively new label. In Europe, the term
- Informatics is the name of many academic departments which combine both CS and
- Information Systems. In North America, Business Schools are the primary
- institutional home of Information Systems research and teaching. But this
- location is a mixed blessing. It brings IS research closer to organizational
- studies. But the institutional imperatives of business schools lead IS
- researchers to emphasize the development and use of systems in a narrow range
- of organizations -- businesses generally, and often service industry firms. It
- excludes information systems in important social sectors such as health care,
- military operations, air-traffic control, libraries, home uses, and so on. And
- Information Systems research tries to avoid messy issues which many practicing
- Computer Scientists encounter: developing requirements for effective systems
- and mitigating the major risks to people and organizations who depend upon
- them.
-
- The emerging field of Organizational Informatics builds upon research
- conducted under rubrics like Information Systems and Information Engineering.
- But it is more wide ranging than either of these fields are in practice.
-
- Organizational Informatics Research
-
- In the last 20 years a loosely organized community of some dozens
- of researchers have produced a notable body of systematic
- scientific research in Organizational Informatics. These studies
- examine a variety of topics, including:
- * how system designers translate people's preferences
- into requirements;
- * the functioning of software development teams in
- practice;
- * the conditions that foster and impede the
- implementation of computerized systems within
- organizations;
- * how people and organizations use systems in practice;
- * the roles of computerized systems in altering work,
- group communication, power relationships, and
- organizational practices.
-
- Researchers have extensively studied some of these topics, such as
- computerization and changing work, appear in synoptic review articles (Kling
- and Dunlop, in press). In contrast, researchers have recently begun to examine
- other topics, such software design (Winograd and Flores, 1986; Kyng and
- Greenbaum, 1991), and have recently begun to use careful empirical methods
- (e.g. Suchman, 1983; Bentley, et. al, 1992; Fish, et. al., 1993). I cannot
- summarize the key theories and rich findings of these diverse topics in a few
- paragraphs. But I would like to comment upon a few key aspects of this body of
- research.
-
- Computer Systems Use in Social Worlds
-
- Many studies contrast actual patterns of systems design, implementation, use
- or impacts with predictions made by Computer Scientists and professional
- commentators. A remarkable fraction of these accounts are infused with a
- hyper-rational and under-socialized view of people, computer systems,
- organizations and social life in general. Computer Scientists found that rule
- driven conceptions to be powerful ways to abstract domains like compilers. But
- many Computer Scientists extend them to be a tacit organizing frame for
- understanding whole computer systems, their developers, their users and others
- who live and work with them. Organizations are portrayed as generally
- cooperative systems with relatively simple and clear goals. Computer systems
- are portrayed as generally coherent and adequate for the tasks for which
- people use them. People are portrayed as generally obedient and cooperative
- participants in a highly structured system with numerous tacit rules to be
- obeyed, such as doing their jobs as they are formally described. Using data
- that is contained in computer systems, and treating it as information or
- knowledge, is a key element of these accounts. Further, computer systems are
- portrayed as powerful, and often central, agents of organizational change.
-
- This Systems Rationalist perspective infuses many accounts of computer systems
- design, development, and use in diverse application domains, including CASE
- tools, instructional computing, models in support of public policy
- assessments, expert systems, groupware, supercomputing, and network
- communications (Kling, 1980; Kling, Scherson and Allen, 1992).
-
- All conceptual perspectives are limited and distort "reality." When
- Organizational Informatics researchers systematically examine the design
- practices in particular organizations, how specific groups develop computer
- systems, or how various people and groups use computerized systems, they find
- an enormous range of fascinating and important human behavior which lies
- outside the predictive frame of Systems Rationalism. Sometimes these behaviors
- are relatively minor in overall importance. But in many cases they are so
- significant as to lead Organizational Informatics researchers to radically
- reconceptualize the processes which shape and are shaped by computerization.
-
- There are several alternative frames for reconceptualizing computerization as
- alternatives to Systems Rationalism. The alternatives reflect, in part, the
- paradigmatic diversity of the social sciences. But all of these reconceptions
- situate computer systems and organizations in richer social contexts and with
- more complex and multivalent social relations than does systems rationalism.
- Two different kinds of observations help anchor these abstractions.
-
- Those who wish to understand the dynamics of model usage in public agencies
- must appreciate the institutional relationships which influence the
- organization's behavior. For example, to understand economic forecasting by
- the US Congress and the Executive branch's Office of Management and Budget,
- one must appreciate the institutional relations between Congress and the
- Executive branch. They are not well described by Systems Rationalist
- conceptions because they were designed to continually differ with each other
- in their perspectives and preferred policies. That is one meaning of "checks
- and balances" in the fundamental design of the US Federal Government. My
- colleagues, Ken Kraemer and John King, titled their book about Federal
- economic modelling, DataWars (Kraemer, et. al., 1985). Even this title
- doesn't make much sense within a Systems Rationalist framework.
-
- Modelling can be a form of intellectual exploration. It can also be a medium
- of communication, negotiation, and persuasion. The social relationships
- between modelers, people who use them and diverse actors in Federal
- policymaking made these socially mediated roles of models sometimes most
- important. In these situations, an alternative view of organizations as
- coalitions of interest groups was a more appropriate conceptualization. And
- within this coalitional view of organizations, a conception of econometric
- models as persuasion support systems rather than as decision support systems
- sometimes is most appropriate. Organizational Informatics researchers found
- that political views of organizations and systems developments within them
- apply to many private organizations as well as to explicitly political public
- agencies.
-
- Another major idea to emerge from the broad body of Organizational Informatics
- research is that the social patterns which characterize the design,
- development, uses and consequences of computerized systems are dependent on
- the particular ecology of social relationships between participants. This idea
- may be summarized by saying that the processes and consequences of
- computerization are "context dependent." In practice, this means that the
- analyst must be careful in generalizing from one organizational setting to
- another. While data wars might characterize econometric modelling on Capitol
- Hill, we do not conclude that all computer modelling should be interpreted as
- persuasion support systems. In some settings, models are used to explore the
- effects of policy alternatives without immediate regard for their support as
- media for communication, negotiation or persuasion. At other times, the same
- model might be used (or abused with cooked data) as a medium of persuasion.
- The brief accounts of models for global warming in CTF fit a Systems
- Rationalist account. Their uses might appear much less "scientific" if they
- were studied within the actual policy processes within which they are
- typically used.
-
- Repercussions for Systems Design
-
- Even when computerized systems are used as media of intellectual exploration,
- Organizational Informatics researchers find that social relationships
- influence the ways that people use computerized systems. Christine Bullen and
- John Bennett (1991) studied 25 organizations that used groupware with diverse
- modules such as databases, group calendars, text annotating facilities and
- electronic mail. They found that the electronic mail modules were almost
- universally valued, while other system facilities were often unused.
-
- In a recent study, Sharyn Ladner and Hope Tillman examined the use of the
- Internet by university and corporate librarians. While many of them found data
- access through databases and file transfer to be important services, they also
- reported that electronic mail was perhaps the most critical Internet feature
- for them.
- The participants in our study tell us something that we
- may have forgotten in our infatuation with the new
- forms of information made available through the
- Internet. And that is their need for community. To be
- sure, our respondents use the Internet to obtain
- information not available in any other format, to
- access databases ... that provide new efficiencies in
- their work, new ways of working. But their primary use
- is for communication. Special librarians tend to be
- isolated in the workplace -- the only one in their
- subject specialty (in the case of academe), or the only
- librarian in their organization (in the case of a
- corporate library). Time and time again our
- respondents expressed this need to talk to someone --
- to learn what is going on in their profession, to
- bounce ideas off others, to obtain information from
- people, not machines.
- There are tremendous implications from the Internet
- technology in community formation -- the Internet may
- indeed provide a way to increase community among
- scholars, including librarians. The danger we face at
- this juncture in time, as we attach library resources
- to the Internet, is to focus all of our energies on the
- machine-based resources at the expense of our human-
- based resources, i.e., ourselves (Ladner and Tillman,
- 1992).
- In these studies, Organizational Informatics researchers have developed a
- socially rich view of work with and around computing, of computing within a
- social world.
-
- These studies have strong repercussions for the design of software. A good
- designer cannot assume that the majority of effort should go into the
- "computational centerpiece" of a system, while devoting minor efforts to
- supporting communication facilities. One of my colleagues designed a modelling
- system for managers in a major telephone company, after completing an
- extensive requirements analysis. However, as an afterthought, he added a
- simple mail system in a few days work. He was surprised to find that the
- people who used these systems regularly used his crude electronic mail system,
- while they often ignored interesting modelling capabilities. Such balances of
- attention also have significant repercussions. Many people need good mail
- systems, not just crude ones: systems which include facile editors, ease in
- exporting and importing files, and effective mail management (Kling and Covi,
- 1993).
-
- Assessing people's preferences for systems' designs is an exercise in social
- inquiry. While rapid prototyping may help improve designs for some systems, it
- is less readily applicable to systems which are used by diverse groups at
- numerous locations. Computer scientists are beginning to develop more reliable
- methods of social inquiry to better understand which systems designs will be
- most useful (Bentley, et. al. 1992; Kyng and Greenbaum, 1991). Root and his
- colleagues (1993) recently reported the way that the explicit use of social
- theory helped them design more effective group meeting systems. Unfortunately,
- these newer methods are rarely taught to CS students. When computer
- specialists build an imbalanced system, it should not be a surprise when the
- resulting organizational value of their efforts is very suboptimal.
-
- [CONTINUED in RISKS-14.25.]
-
- ------------------------------
-
- End of RISKS-FORUM Digest 14.24
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-