Thursday, December 21, 2006

The Necessity of Engineering for Science

Last month the University of Chicago faculty received an email from new president Robert Zimmer and soon-to-be-provost Thomas Rosenbaum about discussions on creating a program in Molecular Engineering.
The boundary between science (as the study of natural phenomena) and engineering (as the development and study of man-made artifacts) has become much more porous and in certain areas has virtually vanished. Historically, the University of Chicago has had a major international presence in science, but with a few special exceptions, has not systematically developed programs in engineering. With this important and evolving paradigm shift in the relationship between science and engineering, there are important questions regarding how the University should respond. These questions arise both because of exciting and important new areas of investigation at the science/engineering interface and because a lack of an explicit investment in engineering may hamper the development of our science.
Does science need engineering because engineering problems lead to important intellectual scientific questions or because engineering provides the tools needed by the scientists to carry on their research? Perhaps a bit of both.


  1. Engineering has always provided tools that scientists use. What is a more recent phenomenon is that engineering has produced artifacts that are themselves worthy of scientific study. The internet (and the economy) are human artifacts, but are poorly understood, and thus worthy objects of scientific study.

  2. Hmmm. I guess it depends on how you define "recently". Herb Simon was talking about these sorts of issues back in the 1960s.

  3. The study of human artifacts is different in some ways than the study of natural phenomena. Human artifacts are often moving targets since there are so many variations that one can consider.

    For example, while analyzing the performance of some existing networking algorithms, one might come up with new algorithms. In computer science, human artifacts are nebulous and malleable. This makes it less likely that any particular artifact will be well studied.

    Moreover, it's not clear which human artifacts are worthy of study. There are so many, particularly in computing.

  4. Elaborating on the malleability of human artifacts and the difficulty this presents to computer science:;action=display;num=1164772533

  5. Does medicine count as science or engineering?

  6. To algorithmically compress the U of C President's message by 71% (from 1227 to 355 characters, thanks 'wc'!):

    "Funding in math, physical science, and biology is flat, with little prospect of renewed growth anytime soon. However, funding for engineering is growing. Furthermore, previous decades or research in math, science, and biology has created powerful new tools for engineers. Therefore, the U of C is going to invest strongly in engineering. So get busy, folks."

  7. ...previous decades or research in math, science, and biology has created powerful new tools for engineers.

    John Sidles has this completely backwards. It is the methods of engineers, computer scientists, statisticians, and mathematicians that have created the powerful new tools for biologists rather than vice versa. The automatic gene sequencer was a feat of engineering by Leroy Hood and his group that fundamentally changed biology. Shotgun sequencing as used by Celera Genomics as part of the human genome project was an algorithm and methodology developed by a computer scientist, Gene Meyers. The fundamental change in biology has come from the adoption of methods from other disciplines and has opened up biology both for fundamental science and for new applications.

    It also isn't about government funding, though potentially lucrative patents probably are a big sweetener. If there is something beyond the leverage that the engineering point of view can give the scientists, it is about the buzz, the good P.R. of getting the university on the top discovery lists that come out each year.

  8. Paul Beame says: "It is the methods of engineers, computer scientists, statisticians, and mathematicians that have created the powerful new tools for biologists rather than vice versa."

    Answering the question "who created what for whom" is a fascinating exercise in history, technology, cognitive science, and primatology.

    AFAICT, the best roadmaps for technology development are usually written by individuals who either trained as engineers and worked as scientists, or vice versa. Examples include the mid-1940s roadmaps of Linus Pauling, John von Neumann, or Werner von Braun (click here and here).

    As a holiday treat, here is 1954 voice of von Neumann himself, speaking at the dawn of the computing age:

    "Those of you present who have lived with this field, and who have lived with and suffered with computing machines of various sorts, and know what kind of regime it is to invest in one, I'm sure have appreciated the fact that it appears that this machine has been completely assembled less than two months ago, has been run on problems less than two weeks ago, and yesterday already ran for four hours without making a mistake!

    Those of you who have *not* been exposed to computing machines, and who do not have the desolate feeling which goes with living with their mistakes, will appreciate what it means that a computing machine, after about two weeks of breaking in, has really a faultless run of four hours.

    It is completely fantastic on an object of this size; I doubt it has ever been achieved before, and it is an enormous reassurance regarding the state of the art and regarding the complexities to which one will be able to go in the future, that this has been achieved."


    To learn what von Neumann (very presciently) foresaw regarding the physics, economics, and politics of global warming, click here.