Innovation
in computing will be essential to finding real-world solutions to
sustainability challenges in such areas as electricity production and delivery,
global food production, and climate change. The immense scale, numerous
interconnected effects of actions over time, and diverse scope of these
challenges require the ability to collect, structure, and analyze vast amounts
of data. A report from the National
Research Council says that advances in computing—such as ones that allow us to
make trade-offs, understand complex systems and their connections, and account
for uncertainty—will be critical to meeting sustainability challenges.
“These
problems are as complex as they are important; we need to engage deeply across
disciplines to have any hope of meeting global sustainability challenges,”
said Deborah Estrin, professor of computer science at the University
of California, Los Angeles, and chair of the committee that
wrote the report. “The urgency of
these problems means that we must begin to deploy our ‘best-of-breed’
approaches immediately to put our critical societal infrastructures on a
digital plane. This will give us a chance to start creating opportunities for
transformative efficiency gains, deep scientific understanding, and informed
evolution of the associated political and economic systems.”
The report
uses smart energy grids, sustainable agriculture, and resilient infrastructure
as examples to illustrate the potential impact of advances in computing. In
each example, the report shows how information, data management, and
computational approaches can be used to weigh costs and benefits of alternative
approaches, minimize the risks of failures and disaster, and cut waste and
unnecessary redundancy. For instance, in the case of a smarter energy grid,
better data management will enhance understanding of the energy supply and
demand chain in ways that could foster substantial reductions in overall demand
and more use of renewable energy sources.
The
report recommends working toward these complex and challenging sustainability
goals from the bottom up. By solving particular pressing problems, researchers
can identify and improve approaches that can then be applied broadly. Past
efforts in computer science research, such as Internet protocols, machine
learning, and databases are successful examples of this problem-focused,
iterative approach that can stimulate dramatic change.
An
ultimate goal of applying computer science to sustainability is to inform,
support, facilitate, and even automate decision making, the report says. Four
broad research areas in computer science are crucial to attaining this goal:
measurement and instrumentation; information-intensive systems; modeling,
simulation, and optimization; and human-centered systems. Efforts in each will
be needed, often in tandem. Since these areas correspond to established
research areas in computer science, the research community is well-positioned
to make progress.
The
report stresses that computer science research in sustainability must be an
interdisciplinary effort, with experts in the various fields of sustainability
being equal partners in research. To further that end, undergraduate and
graduate education in computer sciences should provide experience across
disciplinary boundaries. Programs should include tracks that offer course work
in areas such as life-cycle analysis, agriculture, ecology, natural resource
management, economics, and urban planning.
The
committee was encouraged by the establishment of Science, Engineering, and
Education for Sustainability (SEES) as a National Science Foundation area of
investment. With an emphasis on interdisciplinary efforts, the program provides
an opportunity to put the recommended principles of this report into practice
at NSF and can be used as a model for computer scientists who wish to further
their research in a sustainability-oriented problem space.
Source: National Academy of Sciences
