I’ve been feeling for some time now an inkling of discomfort with the standard motivation for some of the work we do on the StepGreen project (and as members of the sustainable CHI research area in general). I’ve seen the same concern in various forms crop up in reviews and on thesis committees I’ve been privy to — the question of how much impact a project really has, what the costs of the project are, and so on. Sort of like privacy in the oldest Ubicomp work, the issue is often avoided or handled in a cursory fashion. But I want to investigate this issue in more depth today.
The standard motivation for much of the work in sustainability in the HCI community (and I’ve used this myself) goes something like this: “Using too much energy is bad (list of reasons). But look, energy is used by people for everyday activities (percentage given), and daily activities are a big percentage of this (more percentages). These things are within our control, and because they involve human choice, they are an area that human computer interaction has something to say about. Not only that, but technology has advanced and … ” I’ll stop here because of course there’s some divergence (are we looking and individuals? businesses? campuses? what technology has advanced in what way? what study did we do? these things vary from project to project).
On the positive side, this motivation is exciting, encouraging, and easy to connect to human computer interaction work such as technologies for behavior change. On the negative side, as others before me have argued (e.g., Dourish, 2010) it is utopian, ungrounded, and difficult to measure.
As an alternate, let us require that we work from raw facts down to specific potential impact number. Such a motivation might go something like this [starting from the same place]: “Using too much energy is bad (list of reasons). Globally, we used 16 Terawatts (TW) of energy in 2005, 90% non-renewable (gas, coal, oil, nuclear) (Griffith, 2008). About 7.8 GtCO2 emissions can be removed by information technology advances (Climate Group). This is about 2.7 TW by my calculations1, assuming that the source is coal (about 17% of of 2005 emissions). Of the categories of IT work proposed in Smart2020, the largest impact category is the smart grid category (2.03 GtCO2). More than half of the energy generated each year is wasted in the grid (“directly”) or is wasted because it is unnecessary to spend (“indirectly”). The indirect component adds up to about .28 GtCO2 (Climate Group). This is a vanishingly small portion of global energy emissions (.6%), as shown in the graph at right. Human behavior change to reduce energy use (such as home heating and cooling) falls into this category. By this reasoning, the maximum impact we can have is .6% of global energy emissions, assuming that we had a systemic impact on all energy wasted post grid (not just home heating and cooling in a few U.S. households).
On the positive side, this motivation is measurable, can be used to set real goals, and is based on real data. On the negative side, it is discouraging. Worse, it highlights how much we don’t know. Over what time period is Smart2020 technology expected to have its effect? What are the current global emissions, and how much are they likely to rise? The 7.8 GtCO2 saved by Smart2020 projects pales in comparison to possible projections of global increases, as shown at right. Would such work actually replace or reduce coal plant emissions, or just enable increased energy use globally? As a side note, projecting impact requires projecting future trends, something I would argue requires more formal methods, as humans are notoriously bad at doing this intuitively in the face of exponentially increasing change (Mankoff, et al., In Submission). What percentage, really, would even global adoption of any of our projects create? Is any of the work we do appropriately designed for a global context? And on and on…
In other words, neither of the two most obvious motivations for doing sustainable HCI work seems to justify the time we are putting in. Is there an alternative? I would argue that yes, there is. But it requires putting our work in a new context, viewing it in a new way, and that may affect how we must proceed. Before describing that motivation, we need to explore a broader theory of how we might reduce global emissions. If we combine the recommendations of Pacala & Socolow (2004) and Gore (1992), we can see that the list of ways to reduce carbon emissions is both broader than either of the previous motivations can conceive, and amenable to research at the intersection of technology and people.
Here is a partial list. At left are direct ways of reducing carbon emissions, at right are indirect ways of reducing carbon emissions.
The category “alternate sources of energy” requires special attention as most people underestimate exactly what is involved in making a significant change in how we produce energy. According to Griffith, to replace 14 (of 16) TW of global energy use with alternative sources (which be sufficient to reduce CO2 emissions to a manageable level), we would need, for the next 25 years, to build: 1 1250 m^2 pool of algae per second; 1 100 m^2 solar cell per second; 1 50 m^2 thermal mirror per second; 12 wind turbines per hour; 3 geothermal turbines per day; and 1 nuclear plant per week. This paints a daunting picture of how big the effort required is to truly solve the problems we face.
Projects about individual behavior also fit within the list above (under efficiency), but I would argue that the list of indirect ways of reducing emissions are potentially much more impactful. In fact, we must engage with this broader list, or we risk, as Dourish states (2010) that “framing sustainability solely in terms of personal moral choice in a marketplace of consumption options may obscure the broader political and regulatory questions that attend significant change.”
So where do we go from here? What is the “right” motivation for sustainable human computer interaction work? I would like to argue for a new checklist for impact. Projects must be explicit about the potential for both direct and indirect impact, measurable, and (ideally) scalable. They should consider major growth trends, multiple cultural contexts, and address energy production as well as use. Here is a partial checklist of issues to consider.
- Production of energy (how much, if any, is produced)
- Direct reductions of energy (which type is supported by the project, and how much is reduced?)
- Indirect reductions of energy
- How will it be implemented within or across nations?
- How will it influence national trend (e.g., growth)
- How will it integrate with national trends/cultural context?
- Scale (and scalability) of impact
- At what scale must this be deployed to have impact?
- One person at a time?
- Cultural/National? (social movements; governments; science)
- How could that be achieved?
- Metrics & Measures
- How much energy could one unit save?
- How much energy does one unit use?
- How much impact / cost does it have at scale?
- What are the uncertainties here?
This is just a partial list of things that we might consider when choosing a project. When we accept the importance of things like scale, internationalization, and indirect options for reducing energy use, then a new focus for sustainable CHI emerges. I wil nickname it Local-e, because it requires locally grounded, socially focused solutions. Local-e attempts to decentralize power production, increase sharing of resources, and encourage environmentality (Agarwal, 2004). We must measure waste (of all sorts) so that it can be regulated and taxed, monitor resource use, model it, and inform governments as well as individuals about what we discover. And all of this must be made relevant across sectors and scale up to cities, nations, or more.
Feel-good motivations are no longer enough. The crisis we face is too big for that. Luckily, it turns out that indirect influences on energy use are as important as direct. If we think about IT for sustainability more broadly, perhaps we can begin to have the impact that is needed. IT has changed so much in the world. It’s worth believing (and trying) to do this as well.
Agarwal, A. (2004). Environmentality: Community, intimate government, and the making of environmental subjects. Current Anthropology, 46(2).
Dourish, P. (2010). HCI and Environmental Sustainability: The Politics of Design and the Design of Politics. Proc. DIS 2010, pp. 1-10.
Gore, A. (1992). Earth in the Balance: Ecology and the Human Spirit, Houghton Mifflin
Griffith, S. (2008). GamePlan 1.0. Available at: http://www.slideshare.net/skeen/game-plan-v10-1
The Climate Group (2008). Smart2020: Enabling the low carbon economy in the information age.
Pacala, S. & Socolow, R. (2004). Stabilization wedges: Solving the climate problem for the next 50 years with current technologies. Science 305(5686):968-972.
Mankoff, J., Rode, J. & Kinnaird, P. (In submission). Looking past yesterday’s tomorrow: Using Future Studies methods to extend the research horizon. CHI 2011, In Submission.
1I will not repeat the entire calculation here, but calculated a conversion factor of .036 I using the following data sources to help http://www.nezhadpmd.com/worldenergyscenarios.pdf; http://en.wikipedia.org/wiki/World_energy_consumption; http://22.214.171.124/forecasts/ieo/more_highlights.cfm#world