The Bay Bridge in San Francisco was closed for nearly a week due to the collapse of a steel beam and two tie rods. During the closure, the ridership on the Bay Area Rapid Transit (BART) system increased dramatically to record levels. So, now BART is studying ridership data and feedback from new and infrequent riders, in hopes of attracting them to take public transit on a regular basis.
On Wednesday, the first full day of the emergency bridge closure, BART began an online survey aimed at finding out more about those reasons. The survey will close at the end of business Tuesday, Nov. 3, so if you used BART during the bridge closure, there’s still time to submit your feedback.
Around 1,500 people responded to the survey, which was posted on the homepage of BART’s website and promoted through social web channels including @SFBART on Twitter, the SFBART blog and Facebook fan page. Although anyone could take the survey, analysis will focus on the responses from first-time or infrequent riders.
Preliminary Results
Suggestions given in verbatim, open-ended comments for what would get people to ride BART more frequently included: expanding service, improving parking availability at stations, making machines easier to use, ensuring announcements and signage are clear, keeping trains clean and providing more police presence. BART will dig deeper into the statistical data from questions about trip origins, destinations and frequency.
Carbon Savings
Getting more people out of their cars and onto trains is good not only for BART, but also for reducing environmental impacts of highway congestion, he said. For example, during the first two full days of the bridge closure on Wednesday and Thursday, BART estimated that riders took 163,000 extra BART trips. If they had driven vehicles for those trips, the trips would have resulted in about 1.8 million pounds of CO2 emissions.
Technology has been cited as one possible solution for increasing ridership amongst choice riders (choice riders are those that have multiple alternatives to travel). Studies of the OneBusAway system, for example, have shown that real-time information about city bus arrivals/departures, can increase the number of rides that people take (though it’s yet unclear whether OneBusAway increases rides amongst choice riders). The BART webpage also links to a variety of iPhone and other mobile phone apps for the BART.
I met with University of Washington Assistant Professor Hendrik Wolff last week to discuss the economics of eco-feedback interfaces. Hendrick has done research on environmental economics and management but has focused largely at the macro scale rather than the micro scale, which is where most of the eco-feedback work fits. One of the focuses of our conversation was the amount of resources that are often necessary to run experiments out in the field rather than in the laboratory. Hendrik mentioned John List, who is a professor at the University of Chicago known for adapting methods that are well established in medical science to the social sciences, mainly, real-world experiments relying on randomized trials.
The New York Times has a really interesting article on John List, which includes a personal biography and some highlights from his more well-known research studies, one of which is on philanthropy–in particular, why do people give? From the article:
Philanthropy in America
For a long time, philanthropy was mostly ignored by social scientists. It’s not an especially large part of the economy, and most charities operate on a shoestring, without the resources to finance research projects. But this is starting to change. Americans gave $295 billion to charity in 2006, equal to 2.2 percent of the country’s gross domestic product, up from about 1.8 percent from the mid-’70s to the mid-’90s, according to the Center on Philanthropy at Indiana University. Most philanthropy still comes in the form of small gifts, but there is also a growing group of donors, like Bill and Melinda Gates, who are interested in bringing some of the quantitative rigor of big business to philanthropy
Charities as Laboratories to Study Human Behavior
Academics, for their part, have come to realize that charities provide an excellent laboratory for studying human behavior, in part because so many of them are desperate for the kind of free-of-charge consulting Karlan was offering. When charities are designing their donor appeals, they often go by nothing more than a few rules of thumb, some of which may be profoundly insightful and others a good deal less so. “I think some fund-raisers have developed terrific intuitions, passed on through the fraternity of fund-raisers,” says Paul Brest, president of the William and Flora Hewlett Foundation in Menlo Park, Calif., which often works with charities. “But a lot of the intuitions don’t work. Look at how much junk mail you get.” Matching gifts were another good example. People figured that they worked, because — well, how could they not? They seem so sensible.
So, John List and Dean Karlan, an economics professor at Yale, put together a field experiment to uncover how well “matching gifts” work in social programs. Matching gift programs work by asking for a donation and touting that some other organization (or person) will match that gift thereby making your original donation much more significant. Most matches are two-to-one (e.g., you donate $100, another organization donates $100–doubling the size of your contribution) but some go up to a four-to-one match.
Earlier Research on Match Gifts
In addition to common sense, some of the earliest economic research on philanthropy supported the idea that matching gifts should make a big difference. In the 1970s, economists began studying the tax deduction for charitable giving, and they found that it clearly affected how much people gave. When tax rates were higher — and deductions were thus more valuable — people gave more. It seemed to follow that they would be equally rational about a match.
The Experiment
Late in 2004, List and Karlan started working on different solicitation letters for a political organization. The letters were similar except for the part that mentioned (or didn’t mention) a match. In one letter, sent to the control group, there was no match. Another letter said that a donor had agreed to match any gift, dollar for dollar. In a third, the match was increased to two to one, and in a fourth it was three to one.
The Results
When Karlan and List got their results, however, they realized that the conventional wisdom about matches was only partly right. The existence of a matching gift did very much matter. In their experiment, 2.2 percent of people who received the match offer made a donation, compared with only 1.8 percent of the control group. That may not seem like a big difference, but it is — more than a 20 percent gap between the two response rates, which is certainly large enough to justify making the effort to solicit a hefty matching gift.
But the size of the match in the experiment didn’t have any effect on giving. Donors who received the offer of a one-to-one match gave just as often, and just as much, as those responding to the three-to-one offer. That was surprising, because a larger match is effectively a deeper discount on a person’s gift. Yet in this case, the deeper discount didn’t make an impact. It was as if Starbucks had cut the price of a latte to $2 and sales didn’t increase.
Why Do People Give?
In the late 1980s, an economist named James Andreoni argued that the internal motives for giving were indeed more important than many people had acknowledged. He came up with a name for his idea — the “warm glow” theory — and it stuck. In the warm-glow view of philanthropy, people aren’t giving money merely to save the whales; they’re also giving money to feel the glow that comes with being the kind of person who’s helping to save the whales.
Andreoni’s argument was a merely theoretical one, but the experiment by List and Karlan suggested that it was correct. Donors did not, in fact, seem to do a rational analysis of how they could best help promote liberalism. And there was one more layer to their results that made the findings even more striking. In blue states — defined as those that voted for John Kerry — even the existence of a matching gift had only a minor effect. It lifted the response rate by about 5 percent. In red states, though, a matching gift increased donations by about 60 percent. For isolated liberals living in states that had just voted for Bush’s re-election, the glow that came from joining up with another liberal seemed to be much stronger. “Giving is not about a calculation of what you are buying,” Karlan said. “It is about participating in a fight.” It is about you as much as it about the effect of your gift. As much as fund-raisers say that they understand these mixed motivations, charities often continue to behave as if donors were automatons. Thus the existence of big matching gifts.
I found this study incredibly compelling for a number of reasons. First, their method allowed them to test a number of conditions at scale in the field. This is the primary principle behind A/B testing and will, no doubt, play a huge role in future eco-feedback systems (e.g., like Google’s PowerMeter and Microsoft’s Hohm) that will allow the designers to quantify the benefit/effectiveness of specific feedback features and interfaces. Second, their results further underline how very irrational humans can be and that we are not, for whatever reason, always motivated to maximize rational economic gain. If you’re interested in the theory of decision making, I recommend Tversky’s The Framing Of Decisions And The Psychology Of Choice, Tversky’s Judgment Under Uncertainty Heuristics And Biases, and Thaler’s Mental Accounting Matters (to name a few). Note that I believe each of these articles rely solely on laboratory experiments to make their arguments. Finally, I’d be interested in knowing whether visualizations of how gift matching works on the letters themselves would have an effect–that is to say, are some people simply not getting the fact that gift matching can make a huge difference?
Charles and his staff went to every state in the US and used the Freedom of Information Act to get information about companies that dump pollutants into the water. As part of the Clean Water Act, companies have to measure what they are actually dumping, as much as once a week. From each state, Charles received waterway permits and information on whether companies are breaking the law and whether they have actually been punished. They built a giant database with this information, which supposedly rivals the EPA’s own bookkeeping.
Some key issues that I picked up (paraphrased from the interview):
An estimated one in ten Americans have been exposed to drinking water that contains dangerous chemicals or fails to meet a federal health benchmark in other ways. This includes carcinogens in the tap water of major American cities and unsafe chemicals in drinking water wells
The Clean Water Act has been violated more than a half a million times in the last five years, but fewer than three percent of polluters have been fined or punished.
Much of the water pollution in the 1970s was more obvious–you could see it, and you could taste it, and you could feel it. In addition, it took a lot of pollution to affect your life. Now, many chemicals have no scent, have no taste, making them more difficult to detect. Some are dangerous when they’re measured in parts per billion. This is the equivalent of a thimble full of chemical in a swimming pool’s worth of water, and that can actually be enormously dangerous; can be linked to cancers, can be linked to birth defects and other problems
The reason why the Clean Water Act isn’t being enforced is that states simply don’t have the resources to control and monitor polluters. The average Department of Environmental Protection’s budget has remained essentially flat over the last decade while the number of facilities that they have to police has doubled. So as a result, they just don’t have the manpower to go out there and actually enforce the law.
It’s great to see major technology companies like Microsoft, Google and IBM place an emphasis on finding solutions to mitigate climate change. These companies have some very talented engineering staff that could likely make a big difference. Recently, IBM has poured a lot of money into marketing their “smarter cities” program. The website, unfortunately, reads like a giant heap of cleantech-utopia used-car salesman babble. “Safe neighborhoods. Quality schools. Affordable housing. Traffic that flows. It’s all possible…” with IBM! Case in point, this lovely vacuous pitch about IBM’s vision for “Smarter Cities.”
However, the New York Times recently detailed an IBM Smarter Cities program that is, apparently, more than just hype: they are starting a project in Dubuque, Iowa that, “over the next several years will use sensors, software and Internet computing to give the city’s government and citizens the digital tools to measure, monitor and alter the way they use water, electricity and transportation.”
I.B.M. already has a number of computer-services projects with cities around the world, from traffic management systems in Stockholm and London to a smart-grid electricity system in Amsterdam, to water management in Shenyang, China. A goal in each is to conserve resources and reduce energy consumption and carbon emissions.
The Dubuque effort stands out not only because it is in the United States, but also because it marks I.B.M.’s most comprehensive approach to these digitally enhanced public services — water, electricity and transportation. “We’re trying to make Dubuque into the first integrated, smart city,” said Robert Morris, vice president of services research at I.B.M.
The benefits, Mr. Morris added, could well extend beyond water, electricity and transportation. For example, housing development and traffic management could be modeled and policies adopted for other goals like “making sure you have a walkable city.”
The first phase will involve installing digital water and electricity meters in 250 homes and businesses. The smart water meters include special low-flow sensing technology from a local manufacturer, A.Y. McDonald, that will help the public works department and residences reduce water use and detect leaks. An estimated 30 percent of households use water unnecessarily because of undetected leakage in faucets and toilets.
The smart electric meters will help households track their energy use and conserve. They will be able to tap into a Web site and, for example, set household temperatures a few degrees cooler in the winter or warmer in the summer — and model the savings in energy use and monthly bills.
Sounds very technocentric but worth keeping an eye on. In particular, the water sensing stuff seems very relevant to our recent work with HydroSense–a water sensing system that can identify water usage down to the source (e.g., dishwasher, kitchen sink). We have also begun looking at leak detection and identification.
“Smart cities” have recently also emerged as a topic of academic inquiry–the key idea being that traffic sensors, cameras, and even mobile phones all potentially provide data that can be used to understand and model the city. We did a bit of this work on shared bicycling–i.e., what does shared bicycling data reveal about a city? Marcus Foth has a book called Handbook of Research on Urban Informatics: The Practice and Promise of the Real-Time City, which is a collection of essays on “smart cities” research. The senseable city lab directed by Carlo Ratti is also a great place to check out for work in this area.
A set of semi-viral videos about using “fun to change people’s behavior” have hit the web by a group called Rolighetsteorin.se. So far, the group has posted two videos: the first is on redesigning a garbage can to play back a sound file when depositing garbage and the second is on redesigning a subway staircase to promote walking vs. escalator use by turning the stairs into a giant piano ala Big. Both are examples of Persuasive Technology: technology that changes the way people think and act. It is an area I have been studying in graduate school at the University of Washington for the past few years.
The World’s Deepest Bin
This video starts off with the question “Can we get more people to throw their rubbish in the bin by making it fun to do?” The video then skips through a variety of small vignettes showing people throwing away trash at the bin and being amused by the result. The video discloses that on one day 72kg of rubbish was collected in the redesigned bin, 41kg more than a traditional bin just a small distance away. The video ends with: “Fun can obviously change behavior for the better.”
The academic in me asks, “can it really?” I don’t think anyone would debate that fun can change behavior–indeed, “fun” tends to inspire many activities in our lives. However, to truly evaluate the redesigned bin’s effectiveness, one would need to collect data for weeks if not months and, ideally, in more than one setting and in more than one redesigned bin. Although a 31kg difference in rubbish weight between the traditional bin and modified bin certainly points to a positive effect, we can’t be sure if this is just standard garbage variance (i.e., this was just a busy garbage day at that side of the park) or whether the redesigned bin area always gets more garbage (i.e., that particular bin always gets more garbage whether it has sound feedback or not).
Secondly, a problem that plagues much of Persuasive Technology is whether or not the technological intervention induces long-term change (the so called novelty effect). That is, once the person is habituated to the persuasive tech, it no longer impacts their behavior. In this case, given that the bin is in a public space where usage is predominantly by random passerbys, this may not be so relevant.
Finally, there is actually a slight paradox in their design–they are trying to decrease littering by increasing the usage of a trash bin; however, the only way to interact with the system is to deposit trash in the bin. That is, it is only reinforcing people’s proper trash behaviors not necessarily changing the behavior of litterers (although an argument could be made that a litterer could observe or overhear the bin and decide, then, not to litter).
For those that are interested in persuasive technology for garbage/recycling behaviors, I point you to two other relevant sources. At UbiComp2006, Eric Paulos and Tom Jenkins from Intel Research demo’d JetSam, a trash bin that had a camera and projector installed within it to actually project the bin’s contents on the ground (left and middle in Figure below). At DIS2005, David Holstius and colleagues from Carnegie Mellon University wrote a paper on their Infotropism display, which used sensors and living plants to provide ambient feedback about recycling and waste disposal practices in a cafeteria (right in Figure below).
Of course, technology need not be used at all to increase positive garbage disposal behaviors, we can, instead, rely on good industrial design. In a study by Sean Duffy and colleagues at Rutgers, they found that a redesigned trash bin with specific holes for recycling cans, bottles, and newspapers increased recycling by 34%.
Piano Stairs
This is a really fun digital art installation. It is clearly engaging and promoted curiosity and exploration by subway riders. Given that large amounts of people tend to exit a subway at the same time, sound was a great way of attracting others to take the staircase who may have taken the escalator.
That said, a few questions come to mind. (1) This may improve stair walking in the short term, but a more interesting and useful study would be to investigate whether these changes were maintained for long periods (e.g., weeks or months) and, particularly, whether the commuters of this station were compelled to repeatedly opt for the stairs over the escalator. Of course, the non-regular users may indeed be stimulated to try the stairs over the escalator leading to more stair usage at this station than on average. (2) How could we use this design at multiple stations? There is likely a novelty effect at play here–if all subway staircases had piano stairs–would it still be effective? (3) Finally, given that the escalator appears to be moving whether or not people are on it (i.e., it does not have a motion sensor to start and stop), there is no energy savings for stair use (although there are health benefits).
Finally, I should mention that the stated intentions of Rolighetsteorin.se are “to use fun to change people’s behavior for the better”. However, Rolighetsteroin.se appears to either be sponsored by or affiliated with VW. It’s unclear what constitutes this relationship nor what effect it has on the project undertakings or the videos themselves. Rolighetsteroin.se may simply be part of a VW viral advertising campaign and not actually interested in “changing people’s behavior through fun.”
On Friday, October 9th, I was part of an invited panel at the Walk21 conference on Using Powerful Web Apps to Build a Livable Streets Movement hosted by Nick Grossman from The Open Planning Project (TOPP) Labs. Other panelists included Ben Berkowitz from SeeClickFix, a tool to report and monitor community issues; Aaron Ogle from WalkShed.org, a visualization tool to explore very precise and personal walkability calculations; and Seth Priebatsch from SCVNGR, a website to host geo-based scavenger hunt games. It ended up being a tremendously successful panel with a very fruitful discussion which included questions about privacy, the pros/cons of transparency, motivating adoption, and government engagement. Discussions will continue on the mailing list: streets-advocacy-tech@googlegroups.com.
The title of my talk was The Feetback Cycle: Leveraging Everyday Technologies to Change the Way We Move. I focused on the emerging area of Persuasive Technology and the ways in which technology may be used to encourage particular behaviors. I began the talk with a brief overview of popular behavior motivation techniques, highlighted past studies by Sunny Consolvo and colleagues at Intel Research exploring the use of mobile phones to promote fitness activity and then transitioned into a lengthier overview of the UbiGreen Transportation Display. Unfortunately, due to time constraints, I was not able to go over commercial offerings of persuasive technology like the Nike+iPod, the newly released iPod Nano Pedometer or the long-awaited FitBit but you can see the slides here (pptx file, 33.9 MB).
Below are some pictures from the talk itself:
The Toyota Prius is perhaps the quintessential eco-feedback system, it provides real-time information about a driver’s fuel efficiency as well a historical graph to track progress over time.
Back in 2005-2006, Sunny Consolvo and colleagues from Intel Research, Seattle used a pedometer and mobile phone to show that rewards mediated by a technology could be effective in motivating fit behavior even if that reward was simple. In this case, study participants were rewarded with an asterisks when they achieved their step goals.
The UbiGreen Transportation Display semi-automatically senses transportation modes such as bicycling, running, and walking and feeds this information back to the user with the goal of motivating green transportation decisions.
The UbiGreen Transportation Display uses the background of the mobile phone (sometimes called the wallpaper) to display evocative imagery that changes based on sensed transit activity (sort of like a real-life Choose Your Own Adventure where the choices are sensed in the physical world rather than in a book).
The United States Geological Survey (USGS) found that the thermoelectric generating industry is the largest user of the nation’s water resources, accounting for nearly half (48%) of total water use in the US (this includes both fresh and saline water) [1]. Agriculture (including livestock) is second at 35%, the public water supply is third at 11%, followed by the industrial sector at 5% (four other categories consume around ~1% each).
Agriculture is the largest user of fresh water, accounting for 41% of all freshwater withdrawals in the US (thermoelectric is second accounting for 39%). Salinated water (salt water) cannot be used in agriculture because crops do not tolerate high salinity content and livestock that consume water with high salt content can become sick (e.g., develop digestive disorders) [2].
In terms of the public water supply (which is treated water), the residential sector is the largest user at (56%), followed by commercial (17%), and industrial (15%) [3]. Officially, public water supply is, “water withdrawn by public and private water suppliers that furnish water to at least 25 people or have a minimum of 15 connections.” So, note that this does not include private wells (e.g., homes in rural areas).
The first USENIX Workshop on Sustainable Information Technology (SustainIT ‘10), February 22, 2010. San Jose, CA. Co-located with the 8th USENIX Conference on File and Storage Technologies (FAST ‘10). The workshop program committee is heavily skewed towards Systems researchers (which isn’t too surprising given the fact that (1) it’s USENIX and (2) it’s co-located with FAST). The CFP (below) seems to emphasize engineering trade-offs between performance, cost, reliability and the environment. However, it is more broad than I expected it to be (e.g., lifecycle analysis, including “applications”–although I don’t know what their definition of applications is).
Increasingly, designers of computer systems ranging from small mobile devices to massive datacenters are concerned with sustainable design, including both power and life-cycle costs; these costs should include manufacturing, operation, and disposal of IT systems. Energy costs are growing rapidly, as are the costs of producing, managing, and disposing of the material from which computing systems are built; worse, the long-term environmental impacts of this entire IT life-cycle are poorly understood. Whereas understanding the power that runs computer systems is important, it is not the only factor: the resources needed to manufacture a computer system can be comparable to and even exceed what it consumes in its useful lifetime. The research community and industry do not understand these issues sufficiently well, much less the trade-offs between energy used in various stages of a computer system’s life and its interactions with performance, cost, reliability, usability, security, and more.
This workshop brings together researchers as well as industry practitioners in a forum that presents the latest research and practices. We seek papers that evaluate energy-related issues and their aforementioned trade-offs, present novel new ideas, challenge and/or debunk past and present practices, and more. We especially encourage papers that discuss not just energy issues but also how they interact with other dimensions in a sustainable manner. The scope of this workshop is broad, covering research, theory, hardware, software, applications, techniques, etc.—all related to making computing systems greener.
This workshop is co-located with FAST ‘10 in order to encourage researchers from the two events to interact with each other.
In the July/August 2009 issue of Mother Jones magazine there is an article entitled Why Wasting Water Is So Damn Cheap. It walks through the East Bay’s struggle with drought and its attempts to reduce consumption by ordering most of its residential customers to slash their water use by nearly one-fifth—regardless of how much they were previously using. One problem with this, as the article points out, is it unfairly targets users who were already conservative. Some highlights from the article (my headings):
Tiered Pricing
Composed of dense coastal cities, such as Berkeley and Oakland, as well as sprawling inland suburbs, San Francisco’s East Bay is one of the state’s most balkanized water districts. Typically, 25 percent of the East Bay’s inhabitants suck down 60 percent of its residential water. For this, they are charged as much as 50 percent more per gallon than the most efficient users. During the recent drought they were asked to use 20 percent less and got a rate increase along with everyone else.
Breaking the addiction to cheap water can be tough. Less than half of California’s water districts use tiered pricing. During the last big drought, in 1991, when EBMUD hiked its rates for customers who used more than 250 gallons per day, irate homeowners refused to pay their bills and four inland suburbs sued. The utility relented. “One part of the district was subsidizing another, and fundamentally that’s not fair,” says John Coleman, vice president of the EBMUD board, sounding like a ticked-off conservationist—except that he’s defending the users who couldn’t bear to see their lawns die.
There is No Water Shortage
“There is no water shortage,” says David Zetland, a water policy researcher at the University of California-Berkeley. “We’re just doing the worst job in the world trying to allocate it. If you go down to a bar and Corona costs 12 cents a bottle, you’re gonna run out of Corona. And that’s the problem with water: It’s just too damn cheap to care about.” Even in Southern California’s Irvine Ranch Water District, which sells water to its most frugal customers at below cost but slaps an additional 840 percent charge on the biggest users, 200 gallons at the top rate still cost less than a Frappuccino.
As computing shifts from the desktop to the cloud, large-scale data centers are rapidly growing to meet capacity. And, as it turns out, these data centers are not just huge energy consumers but also huge water consumers. Data centers generate massive amounts of heat and they use water to help keep things cool. So much water, in fact, that it can exceed the capacity of local utilities. From Data Center Knowledge:
The enormous volume of water required to cool high-density cloud computing server farms is making water management a growing priority for data center operators. A 15-megawatt data center can use up to 360,000 gallons of water a day, according to James Hamilton, a data center designer and researcher at Amazon.com.
“Water is tomorrow’s big problem,†Hamilton said. “No one talks about water. The water consumption (in data centers) is super embarrassing. It just doesn’t feel responsible. We need designs that stop using water.â€
Move Towards Water Efficiency
So, what are the big cloud computing companies (Microsoft, Google, and Amazon) doing about this? Again, from Data Center Knowledge:
Microsoft and Google are trying new approaches that use recycled water and nearby rivers and canals to cool their massive data centers, which is influencing where these facilities are located.
Microsoft says it picked San Antonio for one of its new data centers because the local water company could provide large amounts of recycled water, meaning the project would have less impact on the city’s drinking water supply. “One of the unique features of the San Antonio area is their great recycled water systems,†said Debra Chrapaty, Microsoft’s corporate vice president for Global Foundation Services. “As part of our commitment to the environment, we’re using approximately 8 million gallons of water (per month) from this system for our data center cooling needs.â€
Google’s new data center in Belgium is located next to an industrial canal for cooling, while other providers are incorporating wells and captured rain water into their cooling systems.
Google’s Water Cooling System in Belgium
On April 1, 2009, Google hosted the “Efficient Data Centers Summit” in Mountain View, CA. At the summit, they debuted this video walking through the design of their own water treatment facility in Belgium.
The movie above was pulled from this talk at the summit:
sustain is a blog dedicated to the environment, human behavior, technology and the relationship between all three. subscribe to the rss or atom feed.
Author
jon froehlich is a phd candidate in
computer science at the university of washington.
his research focuses on building and studying technology that promotes healthier lifestyles and proenvironmental behaviors.