In an effort to make generalizations across a wide range of
problem-solving situations, Herbert Simon and his colleagues created a
kind of graph that depicts a problem-solver's path toward a goal. While
the problem-solver is working, he or she is asked to talk aloud, and this
protocol is used as the basis for each person's graph. This methodology
was developed using simple laboratory tasks like the 'Tower of Hanoi'
problem, where it provides the researcher with a fine-grained record of the
problem-solving process.
But can such a mapping scheme be adapted to the staggering
complexity of scientific discovery and technological invention?
Interestingly, instead of protocoling actual scientists working on their
discoveries, Simon and his colleagues have preferred to compare novices and
experts working on complicated textbook problems.
Shrager and Langley point out that such programs lack 'embodiment': they fail to capture the visual and tactual aspects of scientific problem-solving. For example, Krebs relied heavily on a tissue-slicing technique learned in Otto Warburg's laboratory. A program cannot, of course, simulate this extremely important aspect of science.
But Gooding has shown how problem-behavior graphs can represent
the hands-on as well as intellectual aspects of Michael Faraday's
discovery processes. Gooding & Addis (this volume) combine
computational and graphing approaches to mapping by developing a kind of
'expert assistant' program which will help the mapper clarify concepts like
'construe'. Every time the mapper thinks a construal has occurred, the
program asks for all the inputs and outputs, and uses this information to
identify additional instances of construal. If the program's predictions
are at variance with the mappers, then the concept needs to be clarified.
Gooding and Addis show how the rigor of the computational approach can be
combined with fine-grained details of the discovery process. What is less
clear is whether and how the expert assistant will facilitate our
understanding of the hands on' and visual aspects of discovery and
invention.
From a sociological perspective, Bruno Latour is developing a
graphing methodology that depicts the way in which a budding discoverer or
inventor recruits allies into a social network. Latour emphasizes
creating graphs from different perspectives, to represent the network as
viewed by competing actors (or 'actants', as he makes no distinction
between animate and inanimate actors). Here again, we see the need for
some kind of visual summary and re-organization of a complex process.
In Latour's case, the map or graph is always based on a narrative;
therefore, it is primarily a useful way of highlighting and summarizing a
path that is already outlined in a narrative. A sharp, visual summary can
facilitate comparisons among the network-building activities of different
actants.
Unlike some of the new sociologists of scientific knowledge, we believe that one cannot understand the innovation process without understanding the content of the inventions and discoveries. Like the sociologists, we believe traditional studies of creativity have underestimated the extent to which social negotiations and 'hands on' practices have shaped innovation. We are still experimenting with ways of incorporating social networks into our maps, which focus far more on cognitive processes. The point to keep in mind now is that 'social' and 'cognitive' are not mutually exclusive categories. Inventors and scientists take knowledge from others, transform it, and re-introduce it into a network of negotiations. Eventually, this whole process will need to be mapped if we are to understand discovery and invention.
To review and summarize earlier efforts:
Our mapping methodology attempts to address these shortcomings
while retaining as many advantages of preceding mapping schemes as
possible. To force us to keep generalizability in mind at the outset, we
decided to map the competition between three telephone inventors
However, we wanted to conduct this comparison at a fine-grained level of
detail. We include primary sources in our maps--through extensive quotes
in notecards as well as reproducing original sketches, to capture the
visual aspects of the invention process. Therefore, the reader need not
accept our interpretation of the invention process but can work to
reconstruct the event for him- or herself. By including so much original
material in our maps, we provide a buffer against distortion of the facts
in ways an account that merely selects the "relevant" data cannot.
To show all this detail on one level would make our maps hopelessly
complex. Therefore, another innovative feature of our mapping system is
that it is hierarchical, with lower level maps representing increasing
amounts of detail until at the lowest levels we have all the data we have
been able to uncover.
To explain our approach, we are going to resort to a series of
analogies, no one of which accurately captures our approach but each of
which captures important elements. One analogy is to the archaeological
reconstruction of the history of a city like Pompeii or Troy. Dozens of
stages in its development have to be reconstructed from partial foundations
overlaid by later buildings, from pottery shards and incomplete written
records. Similarily, we have to reconstruct stages in an invention's
development from surviving artifacts, scattered records and later
reconstructions that have 'overlaid' earlier events.
Our primary focus in the current study is on the inventors. We
are conducting a kind of archaeology of the mind--not of the Freudian sort,
where one probles the depths of the psyche, but of a cognitive sort, where
one tries to reconstruct the mental processes of a discoverer or inventor.
This is perilous work, because one can never be sure that one has
reconstructed the actual mental processes; instead, what we settle for is a
plausible reconstruction that fits the availiable. data Other
archaeologists can unearth new data, or show that we have lumped sketches
together that really belong to different stages or communities.
Some scholars (mostly sociologists) will even argue that our focus
is wrong: what we ought to reconstruct is the development of the social
networks and alliances that produce the invention. Our answer is that one
needs both the cognitive and the social.
What is required, then, is a method that will allow us to trace the
inventor's intellectual and social trajectories, blending them into a
single story. Furthermore, we need a way of making the data and
assumptions on which this story is based accessible to others, so that they
can challenge us and make alterations. If we can do all of this, we will
have developed a method by which a wide range of discoveries and inventions
can be compared, including those produced by teams.
Virtually every upper-level box has a sub-map associated with it,
and many of these sub-maps in turn have even lower and more detailed maps
associated with them. The use of sublevels allows us to incorporate all
of the visual and many textual materials into the map while retaining the
ability to generalize and summarize. The map stores textual material in
notecards linked to each sketch box, allowing the information to be
organized by visual cues and also within the hierarchy. In this way, one
may uncover only as much information as one currently wishes to explore
while preserving additional detail for later viewings of the map.
To pursue another analogy, let us compare our kind of map to a
geographical one--say, one of the new ones on CD-ROM. A person looking at
a map of North America could click on Chicago and 'zoom-in' for a close-up
view. Associated with this view might be all kinds of information about
the city. Similarily, someone looking at one of our upper level maps can
click on boxes with sketches in them to obtain increasingly detailed views
of the developments that lead to this upper-level sketch.
Geographical maps can also use different shapes and colors to
highlight different information, e.g., geographical contours, population
centers, bodies of water, etc. Similarily, we use different shaped boxes
on our maps to denote goals, conclusions, thought experiments and other
features (see
Mapping Symbols). A mapreader may choose to scan the map for
only a particular color, symbol or kind of line. For example, one can
search for national parks. Within a level on a cognitive map, the
different box shapes or symbols allow the reader to scan the map and select
only the thought experiments or only the conclusions. Thus, the map can
contain more information than a reader may be interested in at any one
viewing. In the same way, our cognitive map contains more information than
the reader may wish to confront at a particular time.
Another analogy is to a flowchart, or one of Simon's problem-behavior graphs. Unlike geographical maps, but like problem-behavior graphs, our "Master Map" shows the development of ideas over timewhich flows downward, though it might just as easily flow across.
