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 computers.

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 sciences.

 

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
computing is
a domain of science
does not conflict
with computing’s
status as a field
of engineering or
even mathematics.

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?

 

conclusion

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 other domains.

 

References

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), 1373–1374.

8. Rosenbloom, P.s. A new framework for computer science and engineering. IEEE Computer (nov. 2004), 31–36.

9. Rosenbloom, P.s. Computing as a Great Scientific Domain: A Multidisciplinary Perspective. To be published (2009).

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 ( [e-mail]) 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 ( [e-mail]) 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.