cisely because they are so technologically, socially, and culturally
mediated. So these might be most
effectively addressed in conjunction
with policy initiatives and broader
public support. But HCI should
anticipate and lead these future
trends, look for opportunities to
raise awareness in meaningful ways,
and open up debate. For example,
the ethnographic expertise of HCI
can offer valuable insight into where
practices, and their associated
expectations of resource-reliant services, are headed. Devices such as
smartphones, e-readers, tablets, and
laptops are increasingly interwoven
into everyday life. How do these
devices enable, encourage, or constrain things like shopping for food,
making purchases, and organizing
travel? What implication does this
have for emissions and energy?
Such deeper understandings
enable us to better conceive of technologies and infrastructures that
are more subversive, perhaps working to slowly change expectations
over time, or constrain interactions
resulting in lower-impact services
[ 13]. For example, it is increasingly
common for modern washing
machines to default to a lower temperature setting. Imagine a PreHeat
system that is not only occupancy-predictive but that also sneakily lowers its temperature setting at selected occupied times, learning the
occupants’ tolerance (and even preference) for reduced temperatures.
In our observations of energy-reliant practices of university students, we frequently saw practices
that entailed concurrent and adjacent use of services [ 8]. The lower-resource activities of watching TV or
playing video games would overlap
with higher-impact activities such as
cooking and showering. Many everyday practices were organized around
sometimes conflicting university,
3. Strengers, Y. A. Designing eco-feedback systems
for everyday life. Proc. of CHI 2011. ACM, New York,
4. Brynjarsdóttir, H., Håkansson, M., Pierce,
J., Baumer, E.P., DiSalvo, C., and Sengers, P.
Sustainably unpersuaded: How persuasion narrows
our vision of sustainability. Proc. of CHI 2012. ACM,
New York, 2012.
5. Shove, E. Beyond the ABC: Climate change
policy and theories of social change. Environment
and Planning A 42, 6 (2010), 1273-1285.
6. U.S. EIA. Annual Energy Review. Table 2.5:
Household Energy Consumption and Expenditures
by End Use and Energy Source, Selected Years
7. Scott, J., Brush, A. J., Krumm, J., Meyers, B.,
Hazas, M., Hodges, S., and Villar, N. PreHeat:
Controlling home heating using occupancy prediction. Proc. of UbiComp 2011.
8. Bates, O., Clear, A.K., Friday, A., Hazas, M., and
Morley, J. Accounting for energy-reliant services
within everyday life at home. Proc. of Pervasive 2012.
9. This is based MacKay’s 2009 analysis which
puts indoor heating’s share at 24 out of the
total 195k Wh per person per day [ 10]. The total
includes the embodied energy of the stuff we buy.
Conversion of energy (both embodied and direct)
to carbon equivalents is complex and varies highly
with locale. So we’ll stick with these energy-equiva-lent numbers, as an illustrative example.
10. MacKay, D.J.C. Sustainable Energy—Without the
Hot Air. UI T Cambridge Ltd., 2009.
11. This uses MacKay’s (2009) total of 9k Wh per
person per day for “gadgets” and “light.”
12. Mankoff, J. HCI and sustainability: A tale of two motivations. interactions 19, 3 (May + June 2012), 16-19.
13. Pierce, J., Schiano, D. J., and Paulos, E. Home,
habits, and energy: Examining domestic interactions and energy consumption. Proc. of CHI 2010.
employment, social, and family
schedules. For busy lives like those
of our participants, quickness, convenience, and spontaneity dictated
the options for things like food,
transportation, and even entertainment. This motivates redesigning
technologies to achieve finer-grained
energy savings. For example, turn
off a video screen, leaving the sound
on and media still playing if nobody
is looking at it (as they multitask on
something else). Or make default
appliance behaviors the most ener-gy-efficient in the face of spontaneous and convenience-oriented use.
Looking at the growing amount of
sustainability research not only in
the HCI community but also across
many disciplines, we are excited
about the potential for impact reduction. We think the biggest opportunities emerge when people work
together across these areas, rather
than in silos. Researchers working in
HCI are well suited to help address
the tricky interaction problems that
arise when systems (like heating)
are reenvisioned, and also have a
deep understanding about the construction of needs and contexts of
people. More bluntly, we want to see
the creativity and expertise of the
sustainable HCI community rethinking, reimagining, and creating new
approaches to tackle challenges
of resource and carbon reduction,
rather than the community confining its interventions to visualization
and persuasion based around the
1. Darby, S. The effectiveness of feedback on energy consumption. Technical report, Environmental
Change Institute, University of Oxford, 2006. A
review for DEFRA.
2. Chetty, M., Brush, A.B., Meyers, B. R., and Johns,
P. It’s not easy being green: Understanding home
computer power management. Proc. of CHI 2009.
ACM, New York, 2009, 1033-1042.
ABOUT THE AUTHORS
Mike Hazas is a lecturer in the
School of Computing and
Communications at Lancaster
University, U.K. Using observational approaches combining
quantitative and qualitative data,
A. J. Bernheim Brush is a senior
researcher at Microsoft Research
in Redmond, WA. Her research
area is in HCI with a focus on
ubiquitous computing in the home
and continuous sensing on
James Scott is a researcher in the
Sensors and Devices group at
Microsoft Research Cambridge,
U.K. His research interests span a
wide range of topics in ubiquitous
and pervasive computing, includ-
ing novel sensors and devices,
September + October 2012
© 2012 ACM 1072-5520/12/09 $15.00