Science and complexity – Weaver, 1948 (classic paper introduction 2004)

Science and complexity.Warren WeaverPublished in American scientist 1948


Source for reference: Science and complexity. – Semantic Scholar

Classic paper (pdf)

The above includes this 2004 introduction:


Science and complexity
Warren Weaver
Originally published as Weaver, W. (1948). “Science and complexity,” in American Scientist, 36: 536-544. Reproduced with permission. The Editors would also like to express their sincere thanks to Mia Smith of American
Scientist for providing a high quality digital scan of the original publication.
t is easy to get caught up in the excitement surrounding the study of complexity and how our
new learning might be applied to the problems we
face today. We often feel like pioneers in a new land,
making new discoveries. For those involved in charting such a course, it is easy to lose historical perspective and the path already taken by others. It is to these
earlier pioneers that the Classical Papers Section is
dedicated. Such a side trip to the archives can quickly
bring the reader a dose of reality, that some “new” ideas
are really only “rediscovered.” Similarly, our view of
the future can gain some perspective when reading
about earlier predictions of the future, what we now
call the present.
Reaching back almost 60 years, E:CO readers
are invited to read a classic article by Warren Weaver
(1894-1978). For historical setting, this article was pubOLVKHGVKRUWO\DIWHU:RUOG:DU,,DQGLVLQíXHQFHGE\
for the war effort. During the war, Weaver headed the
Applied Mathematics Panel (AAAS, 2004), a position
that led to familiarity with many of the top scientists of
the era. It was a time of great advances in science and
optimism for more growth in the future. This article
was also written at the time Weaver was formulating
ideas that would later be published with Claude Shannon in The mathematical theory of communication,
which laid the foundation for information theory.
Weaver’s thoughts during this time on how computers
might be employed in machine translation were later
collected in his famous memorandum on the topic that
“formulated goals and methods before most people
had any idea of what computers might be capable of”
The optimistic attitude of the power of science
tion that separates simple, few-variable problems from
the “disorganized complexity” of numerous-variable
problems suitable for probability analysis. The problems in the middle are “organized complexity” with a
moderate number of variables and interrelationships
that cannot be fully captured in probability statistics
The second part of the article addresses
how the study of organized complexity might be
approached. The answer is through harnessing the
power of computers and cross-discipline collaboration.
Weaver predicts:
“Some scientists will seek and develop for themselves
new kinds of collaborative arrangements; that these
groups will have members drawn from essentially all
contribute greatly to the advance which the next half
sciences.” (Weaver, 1948)
When reading this, there is a bit of déjà vu in
what we sometimes hear today of our study of complexity. So too in the statement that “science has, to
date, succeeded in solving a bewildering number of
relatively easy problems, whereas the hard problems,
and the ones which perhaps promise most for man’s
future, lie ahead” (Weaver, 1948). In the end the reader
not further along in our understanding of complexity
given Weaver’s ideas nearly 60 years ago, while also
still being optimistic in our success for the same reasons
Weaver was optimistic.
Ross Wirth