Artificial intelligence implements aspects of human thought. A compiler
implements a high-level language with
machine code. In chemistry, hydrogen
and oxygen implement water. In molecular biology, complex combinations
of amino acids implement life.
Interaction occurs when two phenomena influence each other. In physics, atoms arise from interactions
among the forces generated by protons,
neutrons, and electrons. In astronomy,
galaxies interact via gravitational waves.
In computing, humans interact with
Interactions exist not only within
domains but across domains. Computing is implemented not only by physical processes, but by life processes (for
example, DNA computing) and social
processes (for example, games that
produce outputs1). Likewise, computing can implement, or at least simulate,
structures and processes in these other
domains. Computing interacts not only
with people and other living systems,
but with the physical world (for example,
through sensor networks and robots).
The accompanying table illustrates
a wide range of implementation and
interaction relationships between
computing and the four domains (
including itself). An entry in the table
identifies a way that computing interacts with a domain. For example, the
entry for “quantum computing” in the
“Physical” column and “implemented
by” row means that computation is
implemented by quantum processes
from the physical sciences domain.
The examples in the table are sufficient to demonstrate the amazing extent of interactions between computing and the other domains. Computing
is much more than infrastructure; it is
an equal partner that strongly influences thought, practice, and approach.
There is still more to the story. Many
other interactions involve more than
two fields or domains. For example, the
emerging field of “network science” is
built on multi-way interactions among
the computing, physical, and social
Down to the Basics
We’ve used the term “computation” as
if everyone agrees on its meaning. In
fact, this is not so. Typical definitions
include “activity of a computer,” “phe-
To say that
a domain of science
does not conflict
status as a field
of engineering or
nomena surrounding computers,” and
“transformation of content.” None of
these captures all the notions of computing we can see at work in the table.
For example, biologists believe DNA
encodes information about the living
body and that DNA transcription is
a natural information-transforming
process that creates the amino acids
that generate new life. They clearly do
not think of information as something
stored in a computer database or transcription as an activity of a computer.
One way to define computing in a
sense broad enough to cover everything
in the table is to base it on the evolution
of representations. 6 Except in artificial intelligence, representations are a
somewhat neglected aspect of computing. Computing scientists need to get
better answers to key questions. What
do we mean by a representation? What
does it mean to represent something in
a computationally amenable format?
Should representations be grounded in
the world, or projected from a mathematical definition? What is not a representation? In what way is computation
an evolution of representations?
In fact, representations are not the
only fundamental principle of computing in need of new answers. Many of the
oldest questions are being reopened. 11
What is computation? What is information? What is intelligence? How can we
build complex systems simply?
Computing is pervasive because it is a
fundamental way of approaching the
world that helps understand its own cru-
cial questions while also assisting other
domains advance their understandings
of the world. Understanding computing
as a great domain of science will help to
achieve better explanations of computing, increase the attraction of the field
to newcomers, and demonstrate parity
with other fields of science.
To say that computing is a domain
of science does not conflict with computing’s status as a field of engineering or even mathematics. Computing
has large slices that qualify as science,
engineering, and mathematics. No
one of those slices tells the whole story
of the field.
The exercise of examining computing as a domain of science reveals
that the extent of computing’s reach
and influence cannot be seen without a map that explicitly displays the
modes of implementation and interaction. It also reveals that we need to
revisit deep questions in computing
because our standard answers, developed for computer scientists, do not
apply to other fields of science. Finally,
it confirms that computing principles
are distinct from the principles of the
1. von Ahn, L. Games with a purpose. IEEE Computer
Magazine (june 2006), 96–98.
2. Denning, P. Great principles of computing. Commun.
ACM 46, 11 (nov. 2003), 15–20.
3. Denning, P. Is computer science science? Commun.
ACM 48, 4 (Apr. 2005), 27–31.
4. Denning, P. Computing is a natural science. Commun.
ACM 50, 7 (july 2007), 13–18.
5. Denning, P. Beyond computational thinking. Commun.
ACM 52, 6 (june 2009), 28–30.
6. Denning, P. and Martell, C. Great Principles of
Computing Project; http://cs.gmu.edu/cne/pjd/GP
7. newell, A., Perlis, A.j., and simon, H.A. “Computer
science,” letter in Science 157, 3795 (sept. 1967),
8. Rosenbloom, P.s. A new framework for computer
science and engineering. IEEE Computer (nov. 2004),
9. Rosenbloom, P.s. Computing as a Great Scientific
Domain: A Multidisciplinary Perspective. To be
10. simon, H.A. Sciences of the Artificial, Third Edition.
MIT Press, Boston, MA, 1996.
11. Wing, j. Five deep questions in computing. Commun.
ACM 51, 1 (jan. 2008), 58–60.
Peter J. Denning ( firstname.lastname@example.org) is the director of
the Cebrowski Institute for Information Innovation
and superiority at the naval Postgraduate school in
Monterey, CA, and is a past president of ACM.
Paul S. Rosenbloom ( email@example.com) is a
professor of computer science in the Viterbi school of
Engineering at the University of southern California,
a project leader at the UsC institute for Creative
Technologies, and the former deputy director of the UsC
Information sciences Institute.