From: kling@ics.uci.edu (Rob Kling)
Subject: BROADENING  CS and GRADUATE'S CAPABILITIES FOR EFFECTIVE IS WORK
Newsgroups: misc.jobs.misc
Date: 18 Dec 92 06:05:15 GMT



               Computing for Our Future in a Social World

                               Rob Kling
              Department of Information & Computer Science
                  University of California at Irvine,
                         Irvine, CA 92717, USA
                    kling@ics.uci.edu (714-856-5955)

                        December 17, 1992 [v.8E]


Note: A shorter form of this paper will appear in Communications of the
   ACM, February 1993, in a Forum which discusses Computing the Future:
   A Broader Agenda for Computer Science and Engineering. Hartmanis,
   Juris and Herbert Lin (Eds). National Academy Press, 1992.

Abstract

Computer Science is being pressed on two sides in the US to demonstrate
broad utility to help justify billion dollar research programs and the
value of educating almost 50,000 BS and MS specialists annually. The
Computer Science and Telecommunications Board of the 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 social analysis to help develop appropriate systems
requirements since they are trying to develop high performance computing
applications which effectively support higher performance organizations. It
is time for the academic Computer Science to embrace Organizational
Informatics as a key area of research and instruction.

Introduction

Computer Science is being pressed on two sides to demonstrate 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. It was justified by 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 about 40,000 BS and almost 10,000 MS degrees
annually. Many of these students enter PhD programs or work on projects
which emphasize mathematical Computer Science. Many of these graduates take
computing jobs for which they are inadequately educated, such as helping to
develop high performance computing applications to improve the performance
of organizations.

These dual pressures are pressing leading Computer Scientists to broaden
their conceptions of the discipline to include an understanding of
applications. An important report which 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  National
Research Council.

CTF is a welcome report which argues that academic Computer Scientists must
acknowledge the driving forces behind the generally good Federal 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 contexts.  CTF takes a strong and useful
position in encouraging all computer scientists to broaden our conceptions
of the discipline.

The authors encourage Computer Scientists to envision new technologies in
the social contexts in which they will be used. The numerous examples of
computer applications that the authors identify as having significant social
value rest on social analyses of these technologies. Further, the report
tacitly requires that the CS community develop reliable knowledge, based in
systematic research, to support effective social analysis. And it requires
an ability to teach such skills to practitioners and students. Without a
disciplined skill in social analysis, 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 have sometimes conceived
and promoted technologies which were far less useful or far more costly than
they claimed. Effective CS practitioners who "compute for the future" in
many organizations need some skills in social analysis to help understand
appropriate systems requirements and the conditions which transform high
performance computing into high performance organizations. Since CTF does
not spell out these tacit implications, I'd like to explain them here.

Broadening Computer Science: From Computability to Usability

Since the usability of systems and software is a key theme in the history of
CS, we must expand beyond mathematics for our  conceptions of "theory" for
the discipline. Some applications, such as as supercomputing and
computational science are evolutionary extensions of traditional scientific
computation, even though they have taken a new direction with rich graphical
front ends for visualizing enormous mounds of data. But some other, newer
modes of computing, such as networking and microcomputing, changed 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 have made
digitally represented text and graphics accessible to tens of millions of
people.

None of these advances are inconsistent with "mathematical foundations," in
CS, such as Turing machine formulations. But they are not well
conceptualized by the foundational mathematical models of computation. Nor
do our foundational mathematical models provide useful ways of
conceptualizing advances in even more traditional elements of computers
systems such as operating systems and database systems. 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.

Of the diverse trends in computing, the growing emphasis of usability is one
of the most dominant. The usability tradition has deep roots in CS, and
extends back into the design of programming languages, and operating
systems. But each of these topics also rested on mathematical analysis which
Computer Scientists could point to as "the foundations" of the respective
subdisciplines. However, the growth of non-numerical  applications for
diverse professionals, including text processing, electronic mail, graphics,
and multimedia has placed 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 are others. The theoretical
foundations about effective computer interfaces must rest on sound theories
of human behavior and their empirical manifestations (cf. Ehn, 1991, Grudin,
1989). Further, interfaces involve capabilities beyond the primary
information processing capabilities of a technology. They entail ways that
people can learn about the system 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, which 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 make many computer
systems truly useful must rest, in part, on theories of work and
organization.

Broadening Computer Science: From High Performance Computing to High
   Performance Organizations

The arguments of CTF go beyond interface design 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, for which critics can ask for systematic evidence. For example, one
can ask about the evidence 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 have
provided value to people and organizations. The tough question is whether
the overall productive value of these investments has been worth the
overall acquisition and operation costs. 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 it (Dunlop
and Kling, 1991a). But it there is no automatic link between
computerization and improved productivity. While it is easy to show that
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 technological support to improve organizational performance.
Some technologies require extensive technical support which provides hidden
costs (Kling, 1992). Some technologies are superb for well-trained experts,
but are difficult for less experienced people or "casual users."

Further, a significant body of empirical research has shown 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). Most seriously, some computer
applications do not fit a person or groups'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 which can sound
useful, but which often are useless because they impose burdensome record
keeping demands (Grudin, 1989). On the other hand, email is one of the most
popular applications in office support systems, even when other
capabilities, like group calendars, are ignored (Bullen and Bennett, 1991).

The social consequences 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 graduate 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 have been prone to recommend systems-based
solutions whose structure or implementation would be problematic.

Organizational Informatics

CTF places dual responsibilities on Computer Scientists. One responsibility
is to produce a significant body of applicable research. The other
responsibility is to educate a significant fraction of CS students to be
more effective in conceiving and implementing systems that will actually
enhance organizational performance. Today, most of the tens of thousands
people who obtain BS and MS degrees in CS have no opportunities for
systematic exposure to reliable knowledge about the value of computing in a
social world (Lewis, 1989). Yet a substantial fraction of these students go
on to work for organizations attempting to produce or maintain systems which
improve organizational performance without a good conceptual basis for their
work. Consequently, many of them develop systems which underperform, and are
sometimes even counterproductive, in organizational terms.

Organizational Informatics includes studies of the usability of computerized
information systems and communication systems in organizations. It also
includes studies of their effective implementation, use, organizational
value, conditions that facilitate risks of failures, and their consequences
for people and an organization's clients. It is an intellectually rich and
also practical research area.

In the last 20 years a substantial body of scientific research in
Organizational Informatics has developed. The best of the research in North
America is conducted by faculty in the Information Systems departments in
Business schools and by scattered social scientists (cf. Boland and
Hirschheim, 1987; Galegher, Kraut and Egido, 1990; Cotterman and Senn,
1992). But Computer Scientists cannot effectively delegate the research and
teaching of Organizational Informatics to Business Schools or social science
departments.

Like CS, faculty in these other disciplines prefer to focus on their own
self-defined issues.  And they rarely ask questions with attention to fine
grained technological variations which are important for CS. For example,
the professional discussions of computer risks have been best developed by
ACM sponsored activities related to SIGSOFT. They are outside the purview of
Business School faculty and sociologists seem disinterested. Further,
faculty in these other disciplines are not organized to effectively teach
numerous CS students about systems development and use in organizations. In
North America there is currently no well developed institutional arrangement
for educating students who can effectively take leadership roles in
conceptualizing and developing complex organizational computing projects
(Lewis, 1989).

CTF is permeated with interesting claims about the social value of recent
and emerging computer-based technologies. While many of these observations
are of a kind that should rest on an empirically grounded scientific
footing, Computer Scientists have deprived themselves of access to such
research. For example, the discussion of systems risks in the ACM rests on a
large and varied collection of examples and anecdotes. But there is no
significant research program to help better understand the conditions under
which organizations are more likely to develop systems using the best
risk-reducing practices. There is an interesting body of professional lore,
but little scholarship to ground it.

More broadly, Computer Scientists have virtually no scholarship to draw upon
to understand when high performance networks, like NREN, will catalyze
social value proportional to their costs. Consequently, many of the
"obvious" claims about the value of various computing technologies that we
Computer Scientists make are more akin to the lore of home remedies for
curing illness. Some are valid, others are unfounded speculation. More
seriously, the theoretical bases for recommending home medical remedies and
new computer technologies are not advanced without having sound research
programs.

What is needed

CTF sets the stage for a broader appreciation of value of Organizational
Informatics within Computer Science. It bases the expansion of the
discipline on a rich array of applications in which many of the effective
technologies must be conceived in relationship to plausible uses in order
provide attractive social value for multi-billion dollar public
investments.

The CS community needs an institutionalized research capability to produce
a reliable body of knowledge about the usability and value of computerized
systems and the conditions under which computer systems improve
organizational performance. In Western Europe there are some research
projects about Organizational informatics in a few Computer Science
departments and some research funding through the EEC's Espirit program
(Bubenko, 1992; Iivari, 1991; Kyng and Greenbaum, 1991). These new research
and instructional programs in Western Europe give Organizational
Informatics a significantly more effective place in CS education and
research than it now has in North America.

The CS community has had many years of experience in institutionalizing
research programs, especially through DARPA and NSF. There are many
approaches, including national centers and individual investigator research
grants. All such programs aim to develop and sustain research fields with a
combination of direct research funds, the education of future researchers,
and the development of research infrastructure. They are all multimillion
dollar efforts. Today, NSF devotes about $100K annually to Organizational
Informatics as part of the Information Technology in Organizations program.
This start is far short of the level of funding required to develop this
field within CS.

The North American CS curricula must also include opportunities for
students to learn the most reliable knowledge about the social dimensions
of systems development and use (Denning, 1992). While the study of
Organizational Informatics builds upon both the traditional technological
foundations of CS and the social sciences, the social sciences at most
universities will not develop it as an effective foundational topic for CS.
On specific campuses, CS faculty may be able to develop good instructional
programs along with colleagues in social sciences or schools of management.
But relying upon any specific discipline doesn't provide a national scale
solution for CS. Other disciplines will not do our important work for us.
Mathematics departments may be willing to teach graph theory for CS
students, but the analysis of algorithms would be a much weaker field if it
could only be carried out within Mathematics Departments. For similar
reasons, it is time for academic Computer Science to embrace Organizational
Informatics as a key area of research and instruction.

References:

    Boland, Richard and Rudy Hirschhiem (Ed). 1987.  Critical Issues in
       Information Systems, New York: John-Wiley.
    Bullen, Christine and John Bennett. 1991.  Groupware in Practice: An
       Interpretation of Work Experience" in Dunlop and Kling 1991b.
    Bubenko, Janis. 1992. "On the Evolution of Information Systems
       Modeling: A Scandinavian Perspective." in Lyytinen and Puuronen,
       1992.
    Cotterman, William and James Senn (Eds). 1992. Challenges and
       Strategies for Research in Systems Development. New York: John
       Wiley.
    Denning, Peter. 1992. "Educating a New Engineer" Communications of the
       ACM. (December) 35(12):83-97
    Dunlop, Charles  and and Rob Kling, 1991a. "Introduction to the
       Economic and Organizational Dimensions of Computerization." in
       Dunlop and Kling, 1991b.
    Dunlop, Charles and and Rob Kling (Ed). 1991b. Computerization and
       Controversy: Value Conflicts and Social Choices. Boston: Academic
       Press.
    Ehn, Pelle. 1991. "The Art and Science of Designing Computer Artifacts."
       in Dunlop and Kling, 1991.
    Galegher, Jolene, Robert Kraut, and Carmen Egido (Ed.) 1990.
       Intellectual Teamwork: Social and Intellectual Foundations of
       Cooperative Work.  Hillsdale, NJ: Lawrence Erlbaum.
    Grudin, Jonathan. 1989. "Why Groupware Applications Fail: Problems in
       Design and Evaluation." Office: Technology and People.
       4(3):245-264.
    Hartmanis, Juris and Herbert Lin (Eds). 1992. Computing the Future: A
       Broader Agenda for Computer Science and Engineering.  Washington,
       DC. National Academy Press. [Briefly summarized in Communications
       of the ACM, November 1992]
    Iivari, J. 1991."A Paradigmatic Analysis of Contemporary Schools of IS
       Development." European J. Information Systems 1(4)(Dec): 249-272.
    Jarvinen, Pertti. 1992. "On Research into the Individual and Computing
       Systems," in Lyytinen and Puuronen, 1992.
    Kling, Rob. 1992. "Behind the Terminal: The Critical Role of Computing
       Infrastructure In Effective Information Systems' Development and
       Use." Chapter 10 in Challenges and Strategies for Research in
       Systems Development. edited by William Cotterman and James Senn.
       Pp. 153-201. New York: John Wiley.
    Kraemer, Kenneth .L., Dickhoven, Siegfried, Fallows-Tierney, Susan, and
       King, John L. 1985.  Datawars: The Politics of Modeling in Federal
       Policymaking.  New York:  Columbia University Press.
    Kyng, Morton and Joan Greenbaum. 1991. Design at Work: Cooperative Work
       of Computer Systems. Hillsdale, NJ.: Lawrence Erlbaum.
    Lewis, Philip M. 1989. "Information Systems as an Engineering
       Discipline."  Communications of the ACM 32(9)(Sept):1045-1047.
    Lucas, Henry C. 1981. Implementation : the Key to Successful
       Information Systems. New York: Columbia University Press.
    Lyytinen, Kalle and Seppo Puuronen (Ed.) 1992. Computing in the Past,
       Present and Future: Issues and approaches in honor of the 25th
       anniversary of the Department of Computer Science and Information
       Systems. Jyvaskyla Finland, Dept. of CS and IS, University of
       Jyvaskyla.
    Sarmanto, Auvo.  1992. "Can Research and Education in the Field of
       Information Sciences Foresee the Future of Development?" in
       Lyytinen and Puuronen, 1992.

Acknowledgements:

I appreciate efforts by several colleagues to strengthen this paper through
their comments and critical assistance: Jonathan P. Allen, Lisa Covi, Sy
Goodman, Beki Grinter, Jonathan Grudin, John King, Heinz Klein, Kenneth
Kraemer, Sharyn Ladner, Larry Rosenberg, Tim Standish, John Tillquist, and
Carson Woo.
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