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Steering the Reverberations of Technology Change on Fields of Practice:
Laws that Govern Cognitive Work
David D. Woods (woods.2@osu.edu)
Institute for Ergonomics
The Ohio State University
1971 Neil Ave
Columbus, OH 43210 USA
Plenary Address
Annual Meeting of the Cognitive Science Society
August 10, 2002
“Now all scientific prediction consists in
discovering in the data of the distant past and of
the immediate past (which we incorrectly call the
present), laws or formulae which apply also to
the future, so that if we act in accordance with
those laws our behavior will be appropriate to
the future when it becomes the present.”
Craik, 1947, p. 59
Abstract
Research on cognitive work in context has abstracted a
set of common patterns about cognitive work and
about the relationship of people and computers. I offer
four families of Laws that Govern Cognitive Work plus
Norbert’s Contrast as a synthesis of these findings to
guide future development of human-computer
cooperation. These Laws are one prong of a general
strategy to avoid repeats of past "automation
surprises".
1. Patterns of Reverberations
Observational studies of cognitive work in context
have built a body of work that describes how
technology and organizational change transforms
work in systems. Points of technology change push
cycles of transformation and adaptation (e.g., Carroll’s
task-artifact cycle; Carroll and Rosson, 1992;
Winograd and Flores, 1987; Flores, Graves, Hartfield,
and Winograd, 1988). The review of the impact of new
technology in one operational world effectively
summarizes the general pattern (Cordesman and
Wagner, 1996, p.25):
Much of the equipment deployed ... was designed to
ease the burden on the operator, reduce fatigue, and
simplify the tasks involved in operations. Instead, these
advances were used to demand more from the
operator. Almost without exception, technology did not
meet the goal of unencumbering the personnel
operating the equipment
... systems often required exceptional human expertise,
commitment, and endurance.
… there is a natural synergy between tactics,
technology, and human factors ... effective leaders will
exploit every new advance to the limit. As a result,
virtually every advance in ergonomics was exploited to
ask personnel to do more, do it faster and do it in more
complex ways.
... one very real lesson is that new tactics and
technology simply result in altering the pattern of
human stress to achieve a new intensity and tempo of
operations. [edited to rephrase domain referents
generically]
This statement could have come from studies of the
impact of technological and organizational change in
health care or air traffic management or many other
areas undergoing change today (see Billings, 1997,
and Sarter and Amalberti, 2000, for the case of
cockpit automation). Overall, the studies show that
when “black box” new technology (and
accompanying organizational change) hits an ongoing
field of practice the pattern of reverberation includes
(Woods and Dekker, 2000):
• New capabilities, which increase demands and
create new complexities such as increased
coupling across parts of the system and higher
tempo of operations,
• New complexities when technological possibilities
are used clumsily,
• Adaptations by practitioners to exploit capabilities
or workaround complexities because they are
responsible to meet operational goals,
• The complexities and adaptations are surprising,
unintended side effects of the design intent,
• Failures occasionally break through these
adaptations because of the inherent demands or
because the adaptations are incomplete, poor, or
brittle,
• The adaptations by practitioners hide the
complexities from designers and reviewers after-
the-fact who judge failures to be due to human
error.
The pattern illustrates a more general law of
adaptive systems that has been noted by many
researchers (e.g., Rasmussen, 1986; Hirschhorn,
1997)—
The law of stretched systems:
every system is stretched to operate at its capacity;
as soon as there is some improvement, for example
in the form of new technology, it will be exploited to
achieve a new intensity and tempo of activity.
Under pressure from performance and efficiency
demands, advances are consumed to ask operational
personnel “to do more, do it faster or do it in more
complex ways” (see NASA’s Mars Climate Orbiter
Mishap Investigation Board report, 2000, for a
example).
2. Watching People Engineer Cognitive
Work: Claims and Myths
People as advocates for investment in and adoption
of new technology make claims about how these
changes will affect cognitive work and the processes
and products of practice. Claims about the future of
practice if objects-to-be-realized are deployed
represent hypotheses about the dynamics of people,
technology and work (Woods, 1998). Observations at
points of technology change find that these
hypotheses can be and are often quite wrong—a kind
of second order automation surprise (Sarter, Woods,
and Billings, 1997). Envisioning the future of
operations, given the dynamic and adaptive nature of
the process, is quite fragile.
What patterns emerge from observations of people
engineering cognitive work or of people’s claims
about how various advances-in-process will enable
the re-engineering of cognitive work? Remarkably
consistently, we observe over-simplifications
(Feltovich et al., 1997) that claim the introduction of
new technology and systems into a field of practice
substitutes one agent for another, essentially,
computer capabilities as substitute for erratic human
performance. Yes, the claims of opposition of human
and machine come cloaked in different and often
quite sophisticated forms, yet underneath inter-
substitutability or Fitts’ List remains the core—people
and machines are or can be equivalent so that new
technology (with the right capabilities) can be
introduced as a simple substitution of machines for
people—preserving the system though improving the
results. This oversimplification fallacy is so persistent
it is best understood as a cultural myth—the
Substitution Myth (Woods and Tinapple, 1999).
The myth creates difficulties because it is wrong,
empirically—adding or expanding the machine’s role
changes the cooperative architecture and changes
human roles, introduces capabilities and complexities
that are part of multiple adaptive cycles as human
actors and stakeholders jostle in the pursuit of their
goals. But moreover, the myth is unproductive as it
locks us into cumbersome trial and error processes of
development, blocks understanding the demands of
cognitive work in context and how people in various
roles and groups adapt to those demands, and
channels energy away from processes of innovating
use from the continually expanding power of machine
information processing.
How can we better calibrate and ground claims
about the future of cognitive work to avoid past cycles
where change exacerbated clumsy use of technology
and limited adaptations from people responsible to
meet system goals? One possible tactic is to develop
generalizations or ‘laws’ that govern cognitive work by
any cognitive agent or any set of cognitive agents
from the empirical base. Such Laws could serve as a
guide to enhance the use information processing
technology in a practice–centered R&D process
(Woods and Christofferesen, in press).
3. Predicting and Steering Change in
Cognitive Work
Based on patterns about cognitive work and about
the relationship of people and computers abstracted
from research on cognitive work in context, I offer four
families of Laws that Govern Cognitive Work as a
synthesis to guide future development of human-
computer cooperation (the approach is a deliberate
play off Conant’s 1976 laws of information that govern
systems). I also offer Norbert’s Contrast (Wiener,
1950) as an alternative conception of the relationship
between people and computers. The current draft set
of Laws is available from the author.
These laws are built on a foundation of agent-
environment mutuality. Agents' activities are
understandable only in relationship to the properties
of the environment within which they function and an
environment is understood in terms of what it
demands and affords to potential actors in that world.
Each is mutually adapted to the other.
The Laws fall into four families plus Norbert's
Contrast. First, Laws of Adaptation build on original
insights of cybernetics and control (Ashby, 1957;
Conant, 1976). The driving force here is how cognitive
systems adapt to the potential for surprise in the
worlds of work, i.e., the foundational slogan for
Cognitive Systems Engineering from Jens Rasmussen
adaptations directed at coping with complexity and
surprise (Rasmussen and Lind, 1981; Woods, 1988;
Woods and Christoffersen, in press).
Laws of Models are concerned with how we
understand and represent the processes we control
and the agents we interact with. The driving force here
is the mystery of how expertise is tuned to the future,
while, paradoxically, the data available is about the
past.
Laws of Collaboration address how cognitive work
is distributed over multiple agents and artifacts. The
driving force here is the fact that cognitive work
always occurs in the context of multiple parties and
interests as moments of private cognition punctuate
flows of interaction and coordination. The idea that
cognition is fundamentally social and interactive, not
private, radically shifts the basis for analyzing and
designing cognitive work and reconsidering the
relationship between people and computers.
Quite surprisingly, Laws of Responsibility are the
fourth family, driving home the point that in cognition
at work, whatever the artifacts and however
autonomous that are under some conditions, people
create, operate, and modify these artifacts in human
systems for human purposes.
Fifth, based on these Laws, Norbert's Contrast goes
behind our fascination with increasing the power of
the computer to remind us of the limits of literal
minded agents and the unique competences of
human cognition to handle the tradeoffs and
dilemmas of a changing, finite resource, uncertain
world (Wiener, 1950).
Norbert’s Contrast
Artificial agents are literal minded and
disconnected from the world, while human
agents are context sensitive and have a stake
in outcomes.
The key is people and computers start from
different opposite points and tend to fall back or
default to those points without the continued
investment of effort and energy from outside the
system.
Each of these families of Laws and Norbert's
Contrast is quite surprising even shocking given
conventional beliefs about cognition, organizations,
and computers. The Laws allow us to see past these
conventional beliefs to re-consider relationships
across people, computers, the goals of various
stakeholders and the complexities and variations in
the worlds of human activity as we envision and
create the future of operations.
Laws that Govern Cognitive Work have an odd
quality–-they appear optional. Designers of systems
that perform cognitive work do not have to follow
them. In fact, we notice these laws through the
consequences that have followed repeatedly when
design breaks them in varying episodes of technology
change. The statements are law-like in that they
capture regularities of control and adaptation of
cognitive work, and they determine the dynamic
response, resilience, stability or instability of the
distributed cognitive system in question. While
developers may find following the laws optional, what
is not optional is the consequences that accrue
predictably from breaking these laws, consequences
that block achieving the performance goals
developers and practitioners, technologists and
stakeholders set.
Respect for the Laws is essential, for in the final
analysis:
in design, we either hobble or support
people’s natural ability to express forms of
expertise.
Acknowledgments
This piece is a companion and follow up to a previous
address to the Cognitive Science Society in 1994,
Observations from Studying Cognitive Systems in Context.
Many thanks to the various colleagues who in one way or
another helped identify how generalizations like these
operate in cognitive work.
Prepared in part through participation in the Advanced
Decision Architectures Collaborative Technology Alliance
sponsored by the Army Research Laboratory under
Cooperative Agreement DAAD 19-01-2-0009.
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