Exponential Laws of
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Bias in
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Artificial
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Cell-Graphs
Deploying SDN
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Use of Mankind
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Practice
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Review Articles
74 Cell-Graphs: Image-Driven Modeling
of Structure-Function Relationship
Cell-graph construction
methods are best served when
physics-driven and data-driven
paradigms are joined.
By Bülent Yener
Watch the author discuss
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Communications video.
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cell-graphs
42
66
Research Highlights
54 Exponential Laws
86 Technical Perspective
of Computing Growth
Moore’s Law is one small component
in an exponentially growing
planetary computing ecosystem.
By Peter J. Denning and Ted G. Lewis
Watch the authors discuss
their work in this exclusive
Communications video.
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videos/exponential-laws-of-
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66 Bottom-Up Enterprise Information
Systems: Rethinking the Roles
of Central IT Departments
Central IT needs to guide
functional areas and departments
toward effective operational
and procurement practices.
By Cecil Eng Huang Chua
and Veda C. Storey
Magnifying Motions the Right Way
By Richard Szeliski
87 Eulerian Video
Magnification and Analysis
By Neal Wadhwa, Hao-Yu Wu,
Abe Davis, Michael Rubinstein,
Eugene Shih, Gautham J. Mysore,
Justin G. Chen, Oral Buyukozturk,
John V. Guttag, William T. Freeman,
and Frédo Durand
96 Technical Perspective
Mapping the Universe
By Valentina Salapura
97 HACC: Extreme Scaling
and Performance Across
Diverse Architectures
By Salman Habib, Vitali Morozov,
Nicholas Frontiere, Hal Finkel,
Adrian Pope, Katrin Heitmann,
Kalyan Kumaran,
Venkatram Vishwanath,
Tom Peterka, Joe Insley, David Daniel,
Patricia Fasel, and Zarija Lukic´
42 Resolving Conflict
Don’t “win.” Resolve.
By Kate Matsudaira
45 Faucet: Deploying SDN
in the Enterprise
Using OpenFlow and DevOps
for rapid development.
By Josh Bailey and Stephen Stuart
50 Research for Practice:
Web Security and
Mobile Web Computing
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editor’s letter
DOI:10.1145/3020075
Moshe Y. Vardi
Technology for the Most
Effective Use of Mankind
one online”—is either hopelessly naïve
or utterly self-serving.
Over the past decade alone we have
witnessed the demise of two prominent
techno-optimist “solutions.” The One
Laptop per Child (OLPC) project was
launched in 2005 with the goal of trans-
forming education for the world’s dis-
advantaged schoolchildren. But within
a few years “the vision was overwhelmed
by the reality of business, politics, logis-
tics, and competing interests worldwide”
(see https://goo.gl/xWj8OK). The MOOC
(massive open online courses) movement
was launched in 2011 with the rhetoric of
dramatically reducing the cost of higher
education while “reaching the quality of
individual tutoring.” But by 2014, Sebas-
tian Thrun, a MOOC pioneer, concluded
that “The basic MOOC is a great thing for
the top 5% of the student body, but not a
great thing for the bottom 95%.”
The central thesis of Toyama’s talk
was that “Technology has positive im-
pact only when amplifying social trends
or institutions that are already positively
inclined.” As much as I sympathize with
Toyama’s skeptical approach toward
techno-optimism, I find this thesis hard
to swallow. Consider, for example, Polio-
myelitis, often called polio, as an exam-
ple. Polio used to be a dreaded infectious
childhood disease, as in a small fraction
of cases the disease results in permanent
severe muscle weakness. In 1952, Jonas
Salk developed the first effective polio
vaccine, which led to drastic reduction
in polio infections (100 known cases
worldwide in 2015). Surely this counts
as technology with positive impact. Of
course one could argue the worldwide
adoption of polio vaccination required
“social trends or institutions that are al-
ready positively inclined,” but that would
make the thesis a tautology. Some social
problems do have technical solutions!
But Toyama is right that using tech-
nology to solve societal challenges re-
quires a deep understanding of the so-
cietal context, an understanding that
was not demonstrated by the OLPC
and MOOC movements. Furthermore,
deploying technology without under-
standing its societal context may have
adverse societal consequences. Consid-
er “frictionless sharing” as an example.
The concept first arose in the context of
scholarly work, where the goal was to en-
able scholars to easily share resources
with other scholars. In 2011, Zuckerberg
announced developments to Facebook
that would allow “real-time serendipity
in a frictionless experience.” By 2016,
however, frictionless sharing has given
rise to the fake-news phenomenon, with
the proliferation of websites that pub-
lish fraudulent misinformation, quickly
spread via social media, intended to
mislead readers. While it is difficult to
gauge the impact of this phenomenon
on the outcome of the 2016 U.S. presi-
dential election, the explosion of mis-
information surely counts as a negative
consequence of technology. Frictionless
sharing is technology, but to what end?
We, as computing professionals, are
engaged in the development of infor-
mation technology. This technology is
changing the world, but not always for
the better. It is time for computing to
emerge from its technological cocoon
and engage vigorously with social sci-
ence. If we wish our technology to be
developed “for the most effective use of
mankind” (quoting from Ada Lovelace’s
1843 letter to Charles Babbage), then we
need to understand mankind better!
Follow me on Facebook, Google+,
and Twitter.
Moshe Y. Vardi, EDITOR-IN-CHIEF
Copyright held by author.
JANUARY 2017 | VOL. 60 | NO. 1 | COMMUNICATIONS OF THE ACM 5
T ECHNO-OPTIMISM IS DEFINED as
the belief that technology can
improve the lives of people.
It was famously satired in
the U.S. television comedy
series “Silicon Valley,” with a startup-
company’s founders pledging to “make
the world a better place through Paxos
algorithms for consensus protocols.”
But some people take techno-optimism
very seriously. Ray Kurzweil, an accom-
plished tech innovator, described his
techno-optimistic vision in his books:
The Age of Spiritual Machines, How to Cre-
ate a Mind: The Secret of Human Thought
Revealed, and The Singularity Is Near.
In a keynote address (see https://goo.
gl/RwkwK1) at the 2016 meeting of the
Computing Research Association, Ken-
taro Toyama argued that “In spite of the
do-gooder rhetoric of Silicon Valley, it
is no secret that computing technology
in and of itself cannot solve systemic
social problems.” Toyama’s argument,
detailed at length in his 2015 book
Geek Heresy: Rescuing Social Change
from the Cult of Technology, is that per-
sistent societal challenges, such as
socio-economic inequality, do not have
technology-centric solutions. Indeed,
over the past 50 years we have witnessed
the development of the Internet, the
personal computer, the cellphone, the
Web, search engines, social media, and
smartphones—a development often
summarized as the “Information Revo-
lution.” During this period, the U.S.
poverty rate oscillated in the 13%–15%
range, completely impervious to devel-
opments in information technology. In
view of the data on poverty, the quote
attributed to Mark Zuckerberg, Face-
book’s founder and CEO—“The rich-
est 500 million [people] have way more
money than the next six billion com-
bined. You solve that by getting every-
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