bringing back “wild” problems suitable
for algorithmic study is not adequately
awarded. Hence, the computing problems driven by scientific domains are
often developed by the domain scientists, not the computer scientists. This
gives rise to an obvious question: Are we
sure these are the best algorithms for the
tasks at hand? If our answer is yes, then
we have a problem: either all domain-driven problems are trivial (very unlikely)
or expert algorithms can be developed by
nearly anyone without formal computer
science training, and our discipline is
extraneous. Clearly, there is a big opportunity for domain-driven algorithmic
thinking and a need for the broader computer science community to embrace
scientific problems and engineering opportunities. Should we fail to do so, we
contribute to a balkanization of computing, in which computing is reimagined
within each scientific community by
non-experts in computing sciences.
A great example of algorithmic innovation comes from DARPA’s MAKE-IT,d
a program that is reimagining the process of synthesizing chemical reaction
pathways into a search algorithm. The
key insight of MAKE-IT is that chemical reactions can be viewed as nodes in
a directed graph: given certain precursor compounds, a reaction produces
certain chemical products. New kinds
of search algorithms will enable chemists to find new and better methods of
producing important compounds.
˲ The human-machine symbiosis:5
Computing over the decades has been
focused on understanding computing
machinery, building it, controlling it
and understanding the consequences. A computer, or piece of software,
is principally a device that enables a
person to do a job, usually an existing
job, perhaps in a better manner than
before. As electronic spreadsheets
have largely replaced accountants’
physical ones, the human-centric task
has evolved but not fundamentally
changed. Computing machinery is
now poised to go beyond just assisting
with human problems—it enables us
to fundamentally rethink them. This
is seen across science and engineering
domains in a particularly pointed way:
progress has become intimately tied to
computation and data.
What other disciplines
can we disrupt
tools that augment
As this scientific revolution unfolds
we are witnessing a shift from merely
computational methods (for example,
computer as calculator) to those in
which humans and machines are partners. Over a decade ago, the Sloan Digital Sky Survey enabled astronomers to
pose questions that were previously impossible to answer. Currently, DARPA is
working to advance machine reading
under our Big Mechanisme program
with the goal of having computers that
can help scientists harvest vast collections of experimental results and produce a shared human-machine understanding of certain cancer pathways. An
emerging challenge is to consider how
problems can be broken up and distributed across human-machine teams
in order to exploit the power of silicon-based machines while optimizing the
insight and creativity of the carbon-based ones. What other disciplines can
we disrupt with computational tools
that augment our intelligence?
The computer scientist is the toolsmith that enables domain scientists
and engineers to reinvent and reimagine their disciplines as algorithmic or
information-centric. However, if computing really is going to be the new
framework for scientific discovery and
engineering innovation, we—the computer scientists—need to support this
kind of interdisciplinary study among
students as well as evangelize the unconverted. Sometimes we might find
those outside computing with a “not
invented here” bias—we need to meet
them halfway or more than halfway.
Sometimes we may find disciplines are
not as much converted to computing,
as they are becoming assimilated under
the assault of ideas from computing.
Scientific disciplines are refactoring
key problems around systems for vast
data and computation, and computer
scientists should be working deeply
with these domain scientists and engineers to bring about revolutions.
Many of the most important problems facing the U.S. and the world today represent a call to service similar
to that which began during the Second
World War, when many of the best and
brightest minds (mostly physicists) in
the country put commercial or academic interests on hold and dedicated
themselves to innovations in service
of national need. Students—pulled
by the lure of the Apollo program or
the needs of the Cold War—pursued
careers of national service in science
and engineering in order to solve big
I would love our best and brightest
computer science students to feel that
pull now, and have the opportunity
to be captivated by these major interdisciplinary challenges. But with the
current din of opportunities, we must
work harder to instill the passion for
such service. Computing is no longer
a new discipline and is well into adolescence—it needs to make some decisions about what it really wants to
be when it grows up. Rather than just
disrupting industries and creating the
next great mobile app, I long for an expanded view of what constitutes legitimate computer science inquiry and for
increased scientific citizenship.
1. Aho, A.V., Hopcroft, J.E.,and Ullman, J.D. The Design
and Analysis of Computer Algorithms.
Addison-Wesley, Reading, MA, 1976.
2. Brooks, F. P., Jr. The computer scientist as toolsmith
II. Commun. ACM 39, 3 (Mar. 1996), 61–68.
3. Grand Challenges For Engineering, The National
Academy of Engineering, 2008.
4. Vonavar, V., Hill, M., and Yelick. K. Accelerating science:
A computing research agenda: A white paper prepared
for the computing community consortium committee
of the computing research association. Technical
report, CRA/CCC, 2016.
5. Licklider, J.C. R. Man-computer symbiosis. Institute
for Radio Engineers, Transactions on Human Factors in
Electronics, HFE-1:4–11 (Mar. 1960).
6. Shneiderman B. The New ABCs of Research:
Achieving Breakthrough Collaborations. Oxford
University Press, 2016.
7. Steering the future of computing. Nature 440, 7083,
8. Stokes, D.E. Pasteur’s Quadrant: Basic Science
and Technological Innovation. Brookings Institution
William Regli (firstname.lastname@example.org) is Acting Director,
Defense Sciences Office, Defense Advanced Research
d http:// www.darpa.mil/program/make-it
e http://www.darpa.mil/program/big-mechanism Copyright held by author.