Society | DOI: 10.1145/1941487.1941495
Leah Hoffmann
Data optimization in
Developing nations
Artificial intelligence and machine learning could expand
access to health care, improve the quality of education, and respond
effectively to natural disasters in the developing world.
By noW, Many scientists and CEOshavebeguntoseizethe opportunities that lie within the exabytes of data being enerated each day. Banks
trawl data to detect criminal fraud,
marketers to spot emerging trends, researchers to uncover new patterns, and
governments to reduce crime and provide better services.
Most data analyses thus far have
focused on developed societies. Yet, a
growing community of computer scientists is calling for new applications
that would harness these data-analysis
methods to improve the lives of people
in developing nations. Machine learning and artificial intelligence, they say,
are perfectly poised to promote socioeconomic development, respond more
effectively to natural disasters, expand
access to health care, and improve the
quality of education. Now, thanks to the
efforts of Eric Horvitz, a distinguished
scientist at Microsoft Research, and Nathan Eagle, a researcher who lives in Kenya and holds faculty appointments at
the Massachusetts Institute of Technology (MIT) Media Lab and Northeastern
University, a small but diverse group of
computer scientists is banding together to share ideas and information, and
to define itself as a community.
Interest about the developing world
has been growing in the field of Information and Communication Technology for Development (ICT-D), which
encompasses projects that range from
managing the delivery of basic services
like health care and education to developing network infrastructure, but ICT-D has rarely focused on opportunities
to apply artificial intelligence or mine
data from developing nations. Last
year, ICT-D experts set out to rectify
that situation with the formation of the
ACM Special Interest Group on Global
nathan eagle (above), eric horvitz, and others are creating an artificial Intelligence for Development community to address problems in economically developing countries.
Development (SIGDEV), which held
its first conference at the University of
London in December. What Horvitz,
Eagle, and others aim to do is foster the
creation of a subfield within ICT-D to
address these deficiencies. The name
they’ve proposed for it: Artificial Intelligence for Development, or AI-D.
It began two years ago at a Princ-
eton University conference called
Studying Society in a Digital World,
which was organized by Edward W.
Felton, director of the university’s
Center for Information Technology
Policy. Eagle presented a paper about
using large data sets—in this case,
phone calls in Britain—to test Ameri-
can sociologist Mark Granovetter’s
“The Strength of Weak Ties” theory,
which argues that innovation often
travels most effectively via weak so-
cial connections. Did factors like the
geographical distance between call-
ers correlate with socioeconomic in-
dicators like income and education?
As it turns out, they did: Regions with
a higher volume of geographically di-
verse calls scored lower on the Index
of Multiple Deprivation, a statistical
study that covers factors like employ-
ment, crime, and health care. Horvitz
was intrigued. “I’m passionate about
machine intelligence and its applica-
tions,” he explains. “And I realized
there’s a lot we can do to stimulate
thought.” Horvitz was president for
the Association for the Advancement
of Artificial Intelligence (AAAI); with
Eagle’s help, he set up an AAAI sympo-
sium titled Artificial Intelligence for
Development at Stanford University,
which took place last March.
