Beth Karlin Ph.D. Thesis Defense

suggestions then the committee will huddle again okay awesome okay well thank you so much everyone for coming it's so exciting for me um to see so many familiar faces from so many different parts of my trajectory um of my time here and even in my preparation to come here some folks who I knew beforehand have come out so I really appreciate it means a lot to me because this is definitely a collaborative effort I feel like both professionally a lot of my colleagues and collaborators are here as well as personally and a lot of you have offered me maybe not collaboration but personal support so I appreciate it thank you so much so I'm going to talk about my dissertation work which is on residential energy feedback so this is kind of just to prepare you we're going to go over a lot of material in a very short amount of time so and I'm not going to go into a lot excruciating detail on every single study because there is so much of it we're talking about a couple hundred pages with four empirical studies so I'll welcome questions at the end but I might not answer ever address every little thing so I'm going to kind of introduce the topic and theory then I'm going to talk about four specific empirical studies that are included in the dissertation and then conclude with kind of the directions that I'm going in right now but I wanted to start with just kind of the ideas that brought me to this research as well as to coming here to pursue a PhD at UC Irvine and I had kind of three underlying ideas things that were really drawing me to quit my job as a high school activities director my former principal is here um and and get a PhD and study big these big picture questions and they were this the first one was that technology and new media were significantly changing how we interact with our natural built in social worlds so from cell phones and Central Africa to multi person chat rooms in Ames Iowa the way that we're interacting with each other and with the natural world is changing in significant ways we're all aware of that and it seemed that there was a lot of research in psychology and a lot actually being conducted here at UCI on some of the serious implications of that and the problems and concerns about that and while I don't disagree with them I also thought there was another story to be told and that was that there are a lot of potential opportunities to leverage these changes for pro environmental and pro social benefit so while it is true that technology can serve to disassociate and disconnect us from one another and from the natural environment I thought it could also be used to connect us and finally there is a lot of work doing that in the private sector right now but there wasn't as much being addressed empirically when the Social Sciences and I thought a social scientific and specifically a psychological or social ecological approach is really important for two reasons it provides a theoretical base with which to study this potential so we can apply things we know from other behavioral domains to this new media landscape as well as sets of empirical methodology with which to study this potential and so coming into those based on those three ideas I started to approach my work and ended up forming a research lab here at UC Irvine I'm in the Center for unconventional security affairs with Richard Matthew called the transformational Media Lab and the idea of the lab in general is to study how technology and new media are changing and can be leveraged to affect how we interact with one another and with the built and natural environment and there's two broad areas that I that we conduct this work in the lab and my dissertation focuses on the first home energy management and this actually represents the very first thing I started studying when I got to UC Irvine so it was only fitting that it encompassed my entire dissertation rather than just become a part thereof so when we look at home energy management I'm really looking at the role of home energy management in addressing a big problem so there's this big problem out there that some of us have heard about called climate change I'm not going to talk about it in much detail if you're not familiar with it feel free to talk to me afterwards but we know 97% of scientists currently agree upwards of that the amount of greenhouse gases and carbon being emitted into the atmosphere is rising and it's largely due to our behavior and that Rai using to see that rising that rising uh carbon emissions are largely due to energy electricity power generation as well as our use in buildings in a recent study by McKinsey identified energy efficiency as a significant vast low-cost energy resource while we are hard at work we being not me but scientists developing alternative energy sources energy efficiency is also a source and it's the cheapest source of new energy and they've identified a trillion dollars in savings a Giga ton of greenhouse gas year and there are two other kind of quotes I thought were really great one by former Energy Secretary Steven Chu who says energy efficiency is not the low-hanging fruit it's the fruit laying on the ground waiting to be picked up it's right there and this actually as I was preparing my slides yesterday I got an email from climate resolve I think this might be my favorite definition ever of energy efficiency and they said that it is the Swiss Army knife of public policy it is indeed veg-o-matic no matter that question it just might be the answer and I just couldn't help but include that in my in my slides today and they did this McKinsey study said the residential sector accounts for over a third of this potential so in our homes we can be addressing we can be reducing our emissions twice the size we could reduce twice the annual emissions of Scandinavia is basically what the potential reductions according to according to this McKinsey study on energy efficiency and they've identified a number of different behaviors and a number of different actions that can be done to reach that potential that potential a third of a Giga ton of greenhouse gas a year but they did identify some significant barriers to meeting this potential those significant barriers largely are people they found and we know that energy from other studies that energy use in identical homes with identical things in the homes vary by up to two hundred and sixty percent so two people living in the same house can have very different ecological footprints and so it's important that we not only address the technologic but also the psychological and the cool thing is psychology really does study people so social science and we think of psychology is largely clinical sometimes in the popular sphere but we are studying mental processes and behavior in the subfield environmental psychology and specifically looks at the study of human well-being human behavior in relation to our socio physical environment so not just studying behavior within the lab but how we're living within our local environments and I thought this was great when the National Academies of science defined the emerging field of sustainability science they specifically said it was the emerging field dealing with interactions between natural and social systems so we're seeing even within the broader sustainability sphere that social solutions are being seen as a necessary corollary with the physical sciences and so when I thought about kind of the role of a psychological or social scientific approach as I mentioned integrating theory is really important understanding behavior and then identifying and testing interventions and while my dissertation will address all three I'm going to start at the bottom and talk about the intervention that we're focused on today which is feedback so feedback a basic definition is information about the result of a process or action that can be used in modification or control so when you step on a scale you might receive feedback about the number of calories you are consuming and/or burning if you clap at the end of my talk you might provide me with some feedback about the quality of my presentation you could also just be conveying social norms so I have to be careful in my interpretation of that so if we and if we look at a system if we look at the system's definition of feedback so anytime we do something every action has some sort of response or reaction in the world and feedback is taking some sort of measurement collecting some sort of information about the results of an action and providing it back to that controlling source for the case of us this can happen in technical systems like a home thermostat this also happens in a natural environment but we're talking about people so I wanted to look at psychological theory in house feedback has been looked at in this field and research on feedback goes back back to the early 20th century looking at knowledge of results studies and early work and law of effect and behaviorism that says the knowledge of a result can affect our future behavior so when we do something we get some sort of information some positive or negative reinforcement and that positive or negative reinforcement can be used to modify future behavior subsequent research expanded on that and said it doesn't necessarily have to be physical we might get information that also we might see feedback being given social social identification theory not here says that we might see information being given back to a relevant peer and that can inform our behavior as well in addition when we set goals when we get information that has a fit that where that feedback is given in reference to a standard which can be a goal or the use of our neighbors or past use that that makes it more relevant so when you weigh yourself that tells you how much you weigh but if you don't know how much you want to weigh if you don't have a goal or you have a pair of pants that you want to fit into or you know what standard for your height that that might not be meaningful so linking all of this past theory Kluger Indonesia 1996 wrote meta-analysis that they published in Psychological bulletin and they they kind of incorporated a lot of past research that related to feedback and developed the feedback intervention theory and they said that for feedback to be effective there was a series of things that needed to be considered knowledge of results there had to be some feedback standard gap and they also pulled into action identification theory that says that there are different levels of motivation that we might seek so while when you take a test you might think I want to get a hundred on the test but if you already get a hundred or I want to get an a on the test but if you already have a 95 why do you want a hundred you might have some higher self relevant goals I want to be the smartest person in the class so once we meet kind of a basic task I have not failed that we can set higher goals more self relevant goals so that feedback is not always just reducing a discrepancy but can be used to stimulate us towards higher goals and feedback also serves to pull the locus of attention on to some specific thing and Kluger and jenissi also noted that while so much of this theory applies across behavioral domains feedback researchers have largely ignored the theoretical importance of task characteristics so most of this research has been on feedback or in classrooms on taking tests or health behavior very self relevant behavior and very little of this work none that we could see in this psychological theory had incorporated pro-environmental behavior which we know is psychologically distinct for a number of reasons so it seemed that it was important to think about the task characteristics of energy use and integrate those task characteristics with a broader understanding of feedback in general and so we identified four primary task characteristics of feedback which are the first that it's non sensory while yes you could technically sense electricity and see and touch electricity we typically don't experience it like this electricity is bound up in a cord so we're not seeing touching or feeling it and let's be honest we're not paying that much attention to the cord we're watching television which leads into the second that the energy uses abstract it's kind of invisible we use things that use energy nobody goes home and thinks I'm going to kick my feet up and use some electricity tonight right we think I'm going to make dinner I'm going to watch TV I'm going to turn on the lights and all of those things use electricity so they're psychologically removed that outcome without being brought back to our attention in addition when we talk about watching the TV it's not just watching TV there are hundreds of behaviors that use energy in a given household in a given day so and even within one specific area like lighting we can look at potential different conservation behaviors like turning off light when you leave the room replacing a light bulb with a CFL or LED or setting light timers so this is very complicated it's not just a single behavior that is addressing this energy use and it's often thought of as low personal relevance here in the state of California electricity is very inexpensive compared to other regions and also other sources of energy and know that over the past several years at least climate changes fairly low on the list of things that Americans worry about and this is just this year that and it stayed kind of on that bottom of the list for quite some time so we so I took these ideas and took that feedback intervention theory and wanted to integrate it with what we know about the task characteristics of environmental behavior and so kind of expand and developed an eco feedback intervention theory or eafit theory which builds on fit and says that for feedback to be effective for environmental behavior it needs to address four primary mechanisms the first the information needs to be perceived right as we say electricity is largely abstract invisible untouchable unknowable so it needs to be presented to people that feedback you're not naturally getting feedback and so you need to direct attention to an energy relevant behavior the second is the ability to interpret or process a lot of people don't necessarily know what a kilowatt is what that means how to relate it to anything that they understand so that interpretation is really important that's being presented in a way that people can interpret it additionally it needs to be motivational either so we know from fit that the feedback standard gap is really important there can be a pre-existing goal or motivation so if you already know that you're trying to conserve in a certain area just getting data might be motivational on its own or it can be provided with the feedback itself and then it needs to connect to specific actions that the user can engage in like we talked about that multiplicity of behaviors make feedback when it comes to environmental behavior and energy use a little more complicated so just to put that all in perspective let's look at a place where there's great feedback great artifacts so when we look at a grocery store we don't think of it but there's amazing information in here this is a great information ecosystem there are prices on everything you have nutritional information that's been mandated by the government this is all kind of feed-forward and in addition when you leave the grocery store every time you leave you get this amazing piece of feedback called a receipt that tell you in excruciating detail how much money everything cost if you saved on a sale item and so you know if you spent too much how to spend less the next time what if instead of getting this you just went grocery shopping whenever you wanted and got a bill like this at the end of the month it would be really hard to make actionable decisions and that's exactly what energy feedback has looked like in the home for a little over a century so when we look at the current bills they're based on an analog meter which requires somebody to come out and read go back to the utility write down a number and you get one number with one dollar amount for an entire month the patent was filed on that in 1888 Thomas Edison did not invent the analog meter but he might have had a beer with the person that did this is about how old it is and we have this window of opportunity because we are right now transitioning in the United States and really globally to a new information architecture a smart grid where these look very similar but this smart meter is digital wireless and real-time so it enables provision of data immediately and larger amounts of it and that's been that's not been ignored that's been picked up by the United States White House launched the green button initiative which says when it was announced in September 2011 consumers should have access to energy usage information should be downloadable easy to read provided by their utility and large companies like Google and Microsoft and the largest tech companies in the world got involved and said we're going to partner with energy utilities to provide this and both of those two largest companies in the world products have been discontinued in less than five years which leads us to think what are we missing and so I started looking at the literature early on right when Google power meter launched I was actually in my first year of my PhD taking a meta analysis course with Joanne Frado Rolie now singer and was interested in this topic and what I found was maybe we're not asking the right questions and what I started to notice was that there's a lot of research looking into this question does residential energy feedback work but maybe we should be asking what types of feedback are out there how are they different how are they similar which ones are more or less effective what's going on here what is this psychological process like what's this black box in here what's leading getting information to conserving and then what are the best ways to measure outcomes and are we being consistent in the way that we're measuring outcomes and so from that I did four studies conducted four studies and a few others that probably aren't in here but should be but didn't fit in a couple hundred pages over the past few years to really start looking into not just is feedback effective but how what types and explore so I'm going to talk about these the first is a meta-analysis where I wanted to develop and test theory inferential II looking at what had been studied all the studies conducted to date what can we learn from meta analytic procedures the second I wanted to look at those different types of feedback what are all these different products there's this new technological ecosystem out there but people are just calling everything feedback and there might be a little more nuance there third I wanted to look at early adopters people who are recruited to participate in a study might not be the same people as those that are actually going out and buying these products when I start out really excited about this topic and started telling everyone I knew about feedback and I was studying feedback I learned that this isn't common most people don't own these aren't going to Home Depot and buying kilowatts and putting them in their homes so who are these early adopters who's actually buying these and are they different from the people in our studies can we learn something from not just experimental work but actually looking at naturalistic users and then finally how are we assessing outcomes and is it as empirical and robust as it can be and what I noticed was a lot of this work in this area had been done in by in practice by practitioners in grey literature and there wasn't a lot of rigor that I was being trained in as a doctoral student in the fields of psychology and education the way we measure and and psychometrically valid a tar scales so can we start developing tools and instruments so first I conducted a meta-analysis that says for one and so as I said there have been tons of studies conducted and some literature reviews had already been had already come out that had found that feedback on average saves about 10% but they saw huge ranges from no effect at all to twenty plus percent and all of these reviews were qualitative and as I was taking in my first year that meta-analysis class I learned that there's a really big difference between a literature review eyeballing findings and comparing them to really statistically measuring effect sizes and comparing them using inferential statistics and when I looked at those lit reviews the findings on several of those key of key moderators several of those key variables that could affect feedback effectiveness conflicted between reviewers and so somebody said feedbacks better when it's when it last longer others said when it's shorter and so we saw these conflicts and finally there was very little theoretical integration they were just kind of presenting results so what I wanted to do was look at all this research in a little slightly different way a slightly more empirical way so collected a bunch of studies ended up with 174 total 69 were irrelevant or secondary analysis we reviewed 103 ran them through some inclusion criteria ended up with 52 papers and 42 empirical studies coated them on variables related to the report the setting methodology treatment and then collected statistical information and then tested a series of proposed moderators that I had identified from previous literature as well as integration with the e-fit theory so looking at perception how frequent was feedback given what medium was it was it a computer was it a bill how was how was feedback being presented what was the measurement was it dollars kilowatt hours were there comparison messages was there a feedback standard gap was it a control comparison historical a social comparison was feedback combined with other interventions with a goal with a financial incentive how long did the treatment last what was the energy granularity so was that feedback about your whole home or was it about a specific appliance or in the home and war information or tips given along with the feedback to help people identify specific behaviors so here's what we found overall feedback answering that same old question once again was effective average savings were 9% and the main effect size was significant and it was actually I think there were about 18 zeros before that one so it was highly significant but again significant variability in effects and actually the heterogeneity the differences in the effect sizes were more significant than the main effect size itself and those mean affects those effect sizes varied from negative point oh eight to positive point for eight so huge variability and effect sizes so maybe we should be saying feedback can be effective but it depends and so we ran those moderators and found that yes feedback was significantly moderated by several of the proposed theoretically and empirically proposed moderators including frequency medium comparison intervention and feedback duration we also tested for variant for study quality were there differences in methodology that led to some of these some of this variability and we didn't see steady quality affecting so things like how they were assigned was the control group of where they were in a study we didn't see that that introduced any statistically significant bias we also tested for publication type because as I said there's a lot of grey literature in this field we did see sample size was the only one of the non treatment variables that was significant so when we kind of pull this back in we saw that most of our hypothesized moderators were significant real-time feedback more frequent real-time feedback was most effective feedback effectiveness increased with technological sophistication so computerised feedback was more effective than paper-based feedback appliance specific that kind of connected feedback to specific actions was more effective comparisons highlighting that feedback standard gap increased effectiveness combination with other interventions goals or incentives also our hypothesis that increased motivation we know that it increased effect size and then duration was really interesting because we found a curvilinear relationship for duration was such that shorter studies and long studies were the most effective with those in the middle being less effective which we hypothesized that short durations engage immediate loading and long term establishes habit and pattern and there might be a sweet spot in this short term and long term and I'll talk about that a little bit coming up so second I wanted to look at all these different types of feedback like I mentioned there are so many different kinds of technologies out there and I wanted to look at some of the differences so there had been again some previous work that had categorized different types of feedback but what I noticed was that there were some issues with the current categorization one was that they really focused on the information provided and we're neglecting like all these technological changes that were going on and they didn't have the sophistication for account for diversity in available products at this end so while we have a category for billing and one for billing with tips when we get to all the kind of technological products they were all kind of lumping into one or two groups and the these classifications weren't systematic they were not mutually exhaustive and mutually exclusive and then finally and I noticed this I was just trying to do a slide where I wanted to say how many of these products were out there and I wasn't sure if I should say there are literally dozens of these products on the market or if I should say there are literally hundreds of these products on the market and that seemed like something easy to find and I realize it didn't exist so you couldn't even find out what's out there so it's the equivalent I like to think of when we look at like cameras we have this huge category for like charcoal drawings and then when we come to almost every camera that exists today it's all lumped into like modern stuff and so how can if we're really trying to analyze camera effectiveness and how it increases people's connection to their children how could we compare it if we don't have enough cat you know and kind of robustness in the way that we understand the differences so what we wanted to know was how many products is this what are they how are they are like or different and can they be categorized systematically and this seemed really important when we realize that medium is is a predictor of effectiveness but we don't really understand the differences between these things is how that kind of if you're wondering why this sounds more engineering even psychologically I think it's important that we understand the technological differences and link that to our psychological theories about what's most effective but if we don't even have categories how can we do that so again we collected a bunch of data um so we ended up spending Kristi did you work on this one yeah so Kristen now is here and about I think six or eight students spent a good 10 to 20 weeks just looking for what's out there they said how do I said I want to know everything that exists is that how do I find it I'm like I don't know use the Internet so we spent some time just collecting data looking on retail websites asking everybody we know internet keyword searches and we find shoot we found 259 so it was literally hundreds of these products exist there's question one then we wanted to code and categorize them so we looked for products that receive information about building use provide that data back to the user and that we had enough information that we could describe them we ended up with 213 we coded them based on 117 identified device parameters that we grouped into 36 characteristics and then we broke those down into six typing characteristics which led us to this beautiful isn't it are a taxonomy of feedback technology which groups from just is feedback effective to does it have hardware is it a product or is it a service because not every feedback has a physical thing we have utility information so services include information platforms and management platforms like your utility company website or companies like Opower that actually just went public last month that work with utilities to pull information directly from your smart meter give it to you on your phone website home computer Facebook so it doesn't necessarily need hardware so that was an important categorization second does it communicate so something that doesn't communicate was just kind of a feedback device so the most common that we see in the market are what are called load monitors so a load monitor is just something that you plug into the wall you plug something into it and it tells you how much that thing uses that's just a device it's not a complex system and appliances can sometimes have this so an appliance can tell you exactly how much it uses versus things that are networked and communication is required for anything to be networked then we wanted to see can you control this was really important as well so we go from information only to management is the communication one way are you receiving information but not able to talk back so you check your iPhone at work and it says you left your lights on and can you turn them off or can you just feel real bad all day right so we have information platforms information networks and management platforms and management networks and in this amazing 21st century world we can communicate by directionally if the technology allows us to then we wanted to look at where is the display and this is really important for that perception piece that I was talking about can you actually see the feedback is it embedded so for example we've seen if you're if you use one of these load monitors to get information about your refrigerator well most likely that display is going to be might be behind the refrigerator so you might not be able to see it so is it embedded on the appliance or sensor is it autonomous is it some sort of like almost like a clock in-home display that can just sit out or is it distributed as in it can go anywhere so your computer something on the web or a web portal or your iPhone also where is the data being collected and this is important to understand what type of information when we're talking about that granularity an appliance monitor is giving you information about that appliance but nothing else same with a load monitor versus things that are coming information coming from the grid will give you information about your whole home that can be disambiguated if there's sufficient granularity and I know some of these things are words that some of you might not be familiar with hopefully my committee who's read the dissertation is familiar with the nuance of some of these things but basically when you're getting information from the grid from your smart meter it's just giving you information about your whole home but theoretically if you collect enough information you can pull out different uses and then finally what's the protocol is the communication proprietary or not so when we get down to these management networks where you can find out about information and turn find out something from your phone and turn it off is it an open protocol using that green that green button protocol that the White House was talking about that I mentioned before or is it a proprietary system where you can only use things from that company and that company only are you locked into some proprietary control which is really important we look about when we look at kind of a broader ecosystem of products so we were successful that looked maybe a little simple at the end it took us a long time to come up with categories that were mutually exclusive and mutually exhaustive so all 213 products fit into one of those categories and only one of those categories and that was really important to us because a real category categorization structure needs to be mutually exclusive and mutually exhaustive we know that even though they swim in the ocean dolphins are in fact mammals they are not mammals and fish and so it was important that we design something that was similarly similar next step so I'm working right now to try and partner with some other organization with some other researchers and organizations to create to go to the next step which is what everyone wants within these categories what's better what's worse what works and that's what kind of started this research because people were very interested in that but I felt like these categories were a necessary precursor because if you want to know what the best camera is which which one of these two cameras are better you need to know if you're looking for a camera that fits in your pocket or one that can shoot a low light high-quality action photography so when we see on things like CNET there are all these different types this was our first step was developing the types and our goal is to create an interactive database and then some sort of ratings and rankings based on psychological principles of effectiveness next and I wanted to look as I said and who's actually buying these things because it sounds really cool when you sit in a talk like this maybe it does um this is huge forty percent a trillion dollars in energy savings we can save Earth why aren't these things flying off the shelves who's out there purchasing what's going on in the real world so there's tons of empirical there's tons of research that suggests that if people get this it will work but who's using them and what's their experience so we wanted to look at naturalistic users people who are actively purchasing and using feedback and we wanted to look at their naturalistic experiences what commercial products they're buying the differences which ones they picked and the full spectrum of user experience from how did you find out about it too how did you get it - are you still using it why or why not and so we conducted a survey and we did some purposive sampling so I was looking for people that use feedback so we over sampled on listservs and emails and social media locations of people that we thought might be these strange early adopter minority people who are hacking into their homes and figuring out how much energy they use and we actually did really well we ended up with 10% we got collected data from 836 people 86% of them 10% reported using energy feedback and so we wanted to know who are these people and what is their user experience so first we asked them a series we asked all 836 a series of questions about who they were demographically and psychological variables and we wanted to see are there differences between feedback users and non-users and we did see several significant differences within this sample between those who hadn't had it so we saw most of our demographic variables they were more likely so feedback users were more likely to be male older married they were slightly more liberal higher income they lived in a detached home and they were much more likely to own their home and that was and that owning at the bivariate level owning a home and being male where the two strongest effects and then we also looked at some psychological variables environmental concerns financial concerns and social concerns and we did find significant differences on both environmental and financial what's interesting as we found feedback users were more environmentally concerned and motivated but less financially motivated and less price conscious so it wasn't necessarily saving money that was that was differentiating these folks so then what we did was we took all the variables that were significant at the bivariate level and ran them in a regression to look at what variables best explained the variance between these early adopter feedback users and non-users and we found that they were gender home ownership environmental motivation and financial motivation so they were less financially motivated more environmentally motivated male homeowners which could be useful and this is just kind of preliminary work but building off of this what is different about these things this could affect how we approach market segmentation and understanding what are the barriers for people that are not these folks as well so both it helps us identify who we can target to be those early adopters and also some people to look at that we might not be getting and then we want to look at what is their user experience so we asked those 86 who said yes I've used feedback what did you use how did you find out about it what do you like and dislike about it did anything change and do you still use it and so when we asked what they used we found across these categories we found the most frequent where these load monitors half of almost half of them 42 of and we saw 86 people but 99 reported devices because some people had reported using more than one and if they were used more than one we asked them to answer the questions about all of them so when I have numbers and percents they're pretty much the same so we found the most frequent where these load monitors in-home displays information platforms like utility websites and Bill's a couple had used these newer management networks and then although heating ventilation and air conditioning is not technically energy feedback we were interested in self perceptions so we included if they thought it was feedback we wanted to know their perception of their thinking that they were using feedback so people said I use my programmable thermostat and that's feedback although it's not really giving energy feedback it is giving temperature feedback so we included though folks we ask them how'd you get it and the most interesting train here was over 30 percent found out via friends and family and acquired via friends and family followed by utility acquisition I found out and got it for my utility and a significant number borrowed their devices so they didn't purchase them they borrowed them then we asked them what did you like and dislike about it and we saw people really said its apparel some of these they're easy to use effectiveness interactivity again this is just kind of high-level across these devices but then some people talked about display problems there's lots of hard tiny to read numbers it's hazardous to set up where I put it I can't see the information there's not enough storage for me to actually keep track of it and then we asked them about outcomes and we did see that over half of them reported some sort of energy saving behavior but a quarter said no changes and 15% actually said they found out that they used that certain things use less than they thought and potentially are using more I've round up using more energy on some devices a potential what's called a rebound effect in some cases I'm less diligent than I was before so while we see kind of what we want from some users others we see on I really care about that anymore I found out doesn't really matter and then when we ask them do you still use it about half a little over half said yes I like to check myself and make sure I'm on track it's just kind of become a habit but almost half said no it served its purpose I learned what I needed to learn and that leads to what I thought was the most interesting distinction to come out of this study which I have a very small separate paper I wrote just on this which was that these kind of dual functions of feedback that we see across from motivation to product use to outcomes that feedback can be used for tracking and learning and so and these are these are actual quotes so it wasn't that hard for me to identify they literally used the words track and learn multiple times right but what we identified was that when we think about learning learning is acquiring a byte of information in a moment I learned that my television uses energy when it's off I know that now versus track which is keeping track of how much energy my home is using over time so tracking requires many bits of information over time how is my energy use changing how is it different or similar to my neighbors learning doesn't need comparable information I just learned something we're tracking does require that feedback standard gap so rather than just looking at feedback as one thing we're starting to see this nuance and when I talked about that short and long term duration that weird curvilinear effect in the meta analysis it could be that short term feedback helps people learn but really long term feedback is required for that tracking that habitual used to come into play and additional things that we thought were interesting which I kind of mentioned from those differences we that there's a lot of information that we can kind of drill into for market segmentation this was one of the first studies on looking at actual users and who is this potential market and who's not social diffusion so looking at leveraging social networks because over thirty percent are engaging socially this idea of diminished utility some people almost half of them aren't using it served its purpose so we can look at lending programs from utilities or libraries or even lending these as well as what to do about that rebound effect that uh found out electricity is cheap right didn't use that much and then last ah like I said we wanted to look at what I noticed was that every study was collecting similar data in slightly different ways so when asking about behavior some would say what have you done to save energy others would say are you saving energy now some would say on a scale of one to ten how much less energy are you using some would say here's a list of ten behaviors which ones have you engaged in others here's a list of twelve behaviors which ones have you engaged in and as a psychologist I knew that that's not ideal but nobody there were no real scales or validated instruments so this is the first one that we developed and I'm working with some colleagues on building from this but we wanted to look at usability at like how easy is it user experience about users right so what is the user experience is it easy to use engaging effective efficient easy to learn how what is the people's experience of using this and the most widely when I started looking at the usability the most widely used scale by a factor of I don't know what is called the system usability scales developed in 1986 and it's used for systems I think I would like to use the system frequently I found the system complex I found the various functions in this system were well integrated so the question seemed a little clunky for what I was going after so I thought this could be tweaked a bit and so I looked at what else was out there and I found some similar issues and these were those issues they were designed primarily to evaluate products or systems rather than information so we could kind of address the unique needs of eco feedback and these metrics were primarily associated with ease of use and there was less focus in the past scales on use of an engagement so I wanted to validate subscales for both ease of use and engagement so we designed a short a quick and dirty eight question scale which with for for ease of use for for engagement the ease of use questions were designed to get at complexity interpretability and learnability which are identified in past literature's components of ease of use and the engagement relevance relevance usefulness and intention to use and so we tested it online with a little over a thousand people this was part of a larger study there are a couple other this was the outcome variable that we used in a study where we were asking about framing messaging and info visualization we got a fairly representative sample they are a little bit younger than this then than the census with slightly more education but somewhat representative and we tested for for psychometric properties which are called which are factor structure reliability criterion validity and sensitivity so factor structure is did the ease of use questions kind of cluster together as ease of use and did the engagement questions kind of cluster together as engagement and they did we had a real clean break and I'm presenting the 8th that worked we tested like 12 or 13 of them but we did see that for real clean ones came out on ease of use and four on engagement and then we looked at reliability which is as a whole do these do these all kind of test something a thing and we found both the overall scale to be reliable with an alpha of 0.85 as well as these sub scales where both were both reliable then we looked at criterion validity which is is it correlated with what we want it to predict so we're hoping that people will see a different see different images and that based on these questions it will predict behavioral intention this was an online study so we couldn't test actual behavior but it did significantly predict behavioral intention the overall scale as well as both the sub-skills and then finally sensitivity is it sensitive to differences so people in these studies saw four different images and are there significant differences in this usability scale across these images versus everyone's just saying everyone's just saying whatever they look at is cool like it pretty cool like it pretty so we'd see high reliability because everybody's answering positively but low sensitivity and we did see that the scale was sensitive so we put these preliminary tests suggest that this scale is valid and reliable we do need to test it in naturalistic settings so to really fully validate this a few more studies this was the first one testing the scale and then I also want to I'm working right now to build a full model of instruments and and scales to test this so upscale is just the first piece and what we're hoping is a larger model of assessment of behavior based energy so when we look at a broader general discussion we've looked at the taxonomy really getting it what is this intervention and teasing a little bit into what are the differences in the variability and feedback we looked a little bit at user experience the meta-analysis was really looking at some of the the intervention based mediators so what's our moderators what's moderating this effectiveness that feedback user paper the naturalistic chapter is looking at that for whom who are these people that are using it what is their user experience and then and then with this experience piece we're looking at like how can we learn more about not just is feedback effective but how and for whom is it effective so while there are benefits to simplicity I think that we need to be designing interventions and designing feedback that when people receive it is very simple and easy to understand and respond to like that on the back end in our analysis it might not be that simple so I think while we want to present simple information to end-users we need to not be thinking a little bit more complex ly about how we design them so thinking not just about is feedback effective but again how who what when where and why is feedback effective so things like what's on future and current research is looking at differences among what type of feedback what amount how much when we go from 12 data points a year to 31 and a half million or up to six point three trillion if we pull those electricity signatures we tested we did some analysis looking at seven verses 31 data points and found that when you go from here to here you see significant changes so when you go from seven to thirty one and you see differences what happens when you get to 31 billion if you're not careful and also what message as we said there's lots of different ways to present information about how much in for me how much your your washer is using I can tell you how much how many kilowatts it uses a year that it's six percent of your home how much per load or we can even translate to other more interesting messages that might get people with different motivations I know that a double bacon I know what a double bacon cheeseburger is and that's about equivalent to a kilowatt hour and then again what outcome so thank you so much and I would welcome any questions at this time and I want to just acknowledge so many so many people in this room have contributed to this so thank you thank you thank you thank you so much thank you so we're going to start our discussion session now and I'm going to alright so I think you did a really great job this is a very impressive body of work I'm actually had a little bit of trouble trying to find too many critiques of it just from my you know experimental social psychological point of view but one thing that did but that I did notice I was reading this in your naturalistic feasibility or your user study where you do have that additional category of the HVAC use which you sort of indicates not really an energy feedback but you put it in there because looks like a little more than 10% of your sample has sort of said this was the energy feedback that they were considering when they were answering when they were doing their answers I'm just wondering if you were to take out that that chump that 10% or so that isn't really fitting into this idea of energy feedback that you have does it have any kind of effect on the results in terms of the picture of the people that are using this or what they think of that Exedra but I didn't see that as really fitting in to you know to the rest even though obviously 10% of the people were confused about what energy feedback meant I didn't know that we should you know let their confusion be part of you know make it look like we were confused um ya know that's a good question we talked as like I see nods because some my collaborators on that project er are in the room and we talked about that and I think what and this one's actually not published yet so this is something we can rerun those numbers and take a look at which I don't think we did but my thought was and I went back and forth on this a bunch was that I was interested in the subjective user experience and these people thought they were using something that they considered energy feedback and a lot of people in this bra field we'll talk about programmable thermostats as feedback because it's giving you feedback about the temperature in the room it's not giving you what my definition of energy feedback is in feedback about the energy consumption of that and so that was our rationale for keeping it possibly because it's a small sample but also because the thought was this was do they think it's feedback the subjective user experience of these people that think they are purchasing and so we kept him we thought the same thing we also thought about people who are just saying well I read my energy bill they weren't really actively adopting and everyone gets an energy bill so some of those non users but they were viewing it they were referring to themselves as a user of feedback and that's kind of where we went with that and it is messy because it's naturalistic and so I'll definitely rerun I think that's a good suggestion to rerun those numbers and see if it changes anything even be worth a footnote that you know when excluding these you know 10 participants who you know aren't really in the cleanest category you know there were no it didn't significantly affect the results or you know or if it does and maybe talking about those totally separately but yeah I would I would try to make sure I mean it it is only a handful of people but you only had 90 people who were you know who were reporting using this so even ten of those 90 you know could you know could throw things off so and gets worth running in both ways awesome thank you all right let me let me let me first of all start off by saying that that the whole thing straightening is showing a very very sophisticated use of statistical interpolation so it's very competent it's it makes a clear contribution to the to the whole sort of feedback psychology domain and and I think it's it's at that level where it is or could be or will be publishable in that domain because it's clearly a contribution and it does what I think is very important social to social ecology it also has obvious real world implications and value and utility so it's sort of a very good example of social ecology research that identifies that the you know identifies a problem that's a real-world problem and grapples with it in a way that is sophisticated intellectually but also useful so so as I guess that backer I want to suggest that there are some things that I would would want you to consider as ways that it might be low cost relatively low cost ways of enriching the value of this to a broader community so those I want I want to suggest a couple of things because I think this is a very well-thought-out will conceived and even exuberant endorsement of a position on the climate change solution set so that's so that's very so in that sense you know it's going to be it hasn't it has an audience but you know and I think this is what I think that maybe maybe you could consider for chapter one maybe you don't even have to consider for this project maybe it's something later on when you you know present or exam but but clearly that point on the solutions that that idea that efficiency is is a linchpin environmental rescuing dealing with climate change is a position that has also a large body of critique so there are lots of people who could disagree with that position could think that that that it is it is it is a sort of sending the wrong message about the severity of the problem so it's it's speaking to a certain demographic a sort of elite upper class type of person and and and and sort of suggesting that here is what we need to do to solve climate change and there are people who think that that's that when we send that message and so yeah that's the wrong message and so all I'm suggesting is that is a approaches to deal with climate change are much broader then efficiency the efficiency is is one of them but it's not by any means all of them and and the reason this is important is for example you state that energy is abstract is an abstract thing and I think the for a certain demographic it is is it abstract for everyone I think a lot of the people it's not very abstract I think for a lot of people is extremely concrete so when you demystify it for wealthy people because it is abstract if you're a homeowner in Newport Beach if you're collecting firewood in ensalada Park it's not that abstract is it maybe more concrete so it's so the process of demystified energy for certain segments of society I think is extremely valuable I think it's important I think it's not people it is a certain subsection of people and even when you look at your group number of people in the world who make 90 to $100,000 at the household level you're talking about a very very small group so they are now being put into a very large role in environmental rescue for being sort of a fraction of the planet and that comes with some implications and I don't think the study is the place to address them but rather just to acknowledge them the first one is when you when you talk about technologies of production and consumption and ways we might alter them adjust them refine them in the what the critics will say is that you're ignoring some important questions and the reason you're ignoring those important questions is because you wouldn't like the answers but and the important questions are that these have implications for technologies of meaning how we understand the problem technologies of sort of you know control how we decide to govern the problem and ultimately technologies of self what we think of as normal behavior as normative behavior for somebody's a psychologist it would be great to it to for me to see your reflections on the implications of something like this for identity for for how people understand what is normal behavior with decide what is good what is normative behavior because it's behavior that a lot of people are never going to be eligible to to to meet for example so is it the I because yeah as we know only only a small number of people have residences in which it's possible to reduce with to reduce energy use building on that a little bit I think that that the the other thing so I would be interesting for me to have your comments on what are some of the broader implications of aligning climate change response which efficiency and when that's only a very small group of people who are really talking to so that would be one thing just to reflect on okay is this in you know are the critics right that this group the last thing you want to be doing is telling this group it that it's role and environmental rescue is actually fairly painless is that the right message to be sending or are we reinforcing their face or in these things yeah because that's what the credible might might suggest about this research and I think that where you can where you can really add value is by anticipating that and responding to it and simply saying here's why this is an important thing to do acknowledging that it that that what I'm not okay looking people in a way that's fully generalizable to everybody on the planet I'm talking about people in a particular socio-economic and cultural context and they look very American and they look very upper class and that's what I'm talking about and this is why I think motivating them them in this way is valuable to the problematic of climate change and not sort of actually making it more complicated because the critique I think goes that that we do this and we're just going to pay the price of environmental collapse and later than we would now because this doesn't actually solve the deeper problem so the other thing that because you're psychologists it would be interesting is is you focus largely on on a certain set of feedback messages and and I would wonder in this all this research did you did you did did you ever think that there might be sort of radically different ways to provide feedback to people like just just you know ways in which people who aren't necessarily doing it but which might be much more effective in terms of this this broader problem of climate change because you know are there other associations or where does it have to be so linear to work good could you have could you have a little bit more complicated routing for feedback to still or would this be a way to to make it accessible to other types of people or to allow other people to participate in getting feedback messages from our energy economy and so on so this is this is a good way for somebody's getting a monthly bill and big under want to reduce it and that's the thing but other other ways that we can think of providing feedback about energy use which might be which might talk to other types of motivations and other types of aspirations that people have really know that one of the things that you have is this broader sense of aspirational and motivational types of issues and just seems that this is begging to be connected to that in a way which which ultimately deepens the personalization of your set of recommendations and conclusions so that these are not so that these are these are a little bit impersonal and I think that there's an opportunity to deepen the intellectual involvement of yourself in same let have we really learned from all this and how is it how it is ultimately this figure in to the larger issue that I'm concerned with the relationship between technology and messaging and climate change and so I don't know if you want to do it in this day but I think you want to do it ultimately is to weigh in and this bigger issue that you have about technology about communications about climate and ask is this you know is it the right way to be going is it the best way to be going are there other ways did this close other doors or probability's other things what are the problems this creates as well as well as what are the solutions it generates I think that you of all people should be able to to do that to think to put this in a broader universe of sort of you know prescription for us then then what the conclusion does I would say the conclusion ends but there's more that you could be writing about the potential value of this way of thinking and taking it to this point then you have done you've closed you've spoken very effectively to that feedback community I think that there's another two pages which would link it to a broader set of concerns about in this direction or not voting in this direction so I think there's a there's a lot of potential it was a little bit of effort when it would would allow you to add an element of creativity to the end of this that links it to the big issues that you described as your motivation for getting in here yeah no I love that I actually it's something I think about it isn't in there and I think I can work in is that what I often say when talking about it is that it's in and I appreciate your comment about the kind of ethnocentrism of the of the approach because in emerging markets people are still very physique physiologically connected to resource use and so I often say it's actually modernism that disconnected us from resource use and the information economy is what can reconnect us to the connections that which that have been lost and so we see that with food right that it's the microwaves and all of these things that have made food so easy that have disconnected us from the number of calories required to hunt and gather and prepare food which is why we have these problems it's the same thing with energy we're disconnected from the physical labor required to get this electricity because of the Industrial Revolution because we're using concentrated energy and so the information can reconnect us to that natural connection that's been lost so in some ways the in the information revolution corrects for the issues that were brought up by the Industrial Revolution so to me that speaks directly to the way in which a technology adjustment in the world of production consumption has implications for technologies of meaning and identity it speaks directly to that and that is a really interesting thing which would also sort of anticipate people who are saying you're just telling these people that all they need to do is make that they their lifestyle is not going to be shaken but all they have to do is put a little device in their home and they're playing their role but what you're really trying to say is I'm going to I'm going to connect them to a deep understand of their links to nature and that's a whole different thing I think it's worth I think it's worth exploring yeah thank you it's what's interesting to me and it's and what's interesting is that I didn't put it in it at all but I about it that way and I don't write about it that way so thank you so as I read across different research strategies that he's brought together I saw a lot of strengths a lots of life I think you mastered and integrated several different mixed methods from meta analysis to surveys archival data analysis and content analysis of feedback device characteristics you integrated subjective as well as objective data reflecting different aspects of feedback so there are a lot of sort of social psychological themes methodological theoretically you've tried to contextualize the meaning of feedback and when it's effective at the same time as I've mentioned to you looking across there there are issues that you haven't addressed Richard and Johanna pointed out some of those so I just want to suggest a few others to think about and as you go forward whether it's for this project later first in terms of energy policy effectiveness you know one could think about where should we put our research dollars or invest our resources to solve that issue climate change and so one category might be supply-side improve technological efficiency or move people toward alternative sustainable technologies whether that's our farming bio filtration or solar panel installation the other being demand side you know efficiency trying to enhance through feedback and other strategies for priests efficiency which sure a lot of savings in to some extent our little improvement so on the demand side and you lay out in your first chapter why there's good rationale to put effort there in terms of what can be harnessed one can think about pre behavioral interventions we mentioned be forward for example that perhaps activate try to cultivate certain values and the ways in which those values anchor certain attitudes and beliefs and ultimately lead to certain kinds of behavior so feedback can be quite different depending on whether it's linked as you point out in a dissertation to incentive systems or not or it can be different depending on whether you bring up socially descriptive norms or prescriptive norms as part of the feedback whether it's social people so I think you know those are some issues that could be thought you know Richard was saying how can you make feedback that much more powerful or frame it a little bit differently in terms of a typology of some of those dimensions of feedback so to what extent does the post behavioral strategy which is after someone behaves giving the feedback is that the best is that where we should put our energy or resources should we put it on pre behavioral kinds of interventions or some combination of those and and if so how might those be leveraged or implemented so those are a few issues that I thought about you know going forward I think you know there's an opportunity to elaborate on some of these things in your closing chapter which brings together your your different research strategies and findings or it's something that could be tackled in a future project but I just mentioned those for some things to think about because the the feedback approach is really post behavior on and some would say well that's that's great that's very effective as long as people pay attention to it and they understand it and they process it but you know a lot of social psychologists for example or people in that room are mental attitudes research books and wait a minute know what about the consistency among these values and beliefs and attitudes how to reshape those up in the surface of certain behaviors and Lincoln's or Yoko's with feedback and I think that and I think that there's a little bit of that there but it isn't described sufficiently where these antecedents are pre intervention strategies like encouraging people to set goals was a moderator for example in the meta-analysis and was touched upon but I don't think I addressed it head-on in a discussion format so I think that what you're getting at there's definitely a line of that throughout the empirical work that I just didn't connect so I can definitely pull that a little bit in the beginning and then pick that up a little bit in the end in how and it's interesting because we talked about it as you know before and after but really like you can't catch somebody before they've ever used energy you know unless they're still we have a few fetuses in the room but you know once we kind of come out of the womb we are using so we're always we're in this system of using of using resources right of consuming resources so in some ways it's almost a false dichotomy of like antecedent in consequence but at the same time it's important to think about before that behavior before turning on your TV tonight versus yeah the resources an effort even notwithstanding issues that Richard mentioned about vast cultural and economic differences in terms of the meaning of feedback and efficiency let's say sticking within a modernist system one of their vulnerabilities is that they're you know are complex energy grids and infrastructures are so all to intermittency to collapse and so one might say well we need to ready the population by kind of encouraging them to go in some new directions to decentralize and do urban farming or do you know things they can do more locally so that they're not just their sustainability behaviors not just in the context of the mega infrastructure so those are you know that's not something you're gonna that you should have the trust in the dissertation obviously but in terms of how to frame your work you know in terms of these broader issues itself yeah let's listen ain't all this making me think more about you know what we learned together through doing the meta-analysis about you know feedback and the different kinds of I'm always been especially interested in things like the motivational and this you know are you mean your goal or you know are you doing better than your neighbor and all this kind of competition or at least school setting which I think there's not enough research you know there are a few studies that kind of did that but you know as we saw it wasn't even really enough to be able to talk very much about the meta-analysis and one thing I'm thinking about is you know this question that you just asked Richard about you know is are there ways that feedback isn't even being given that we could we can start giving it and having this antecedent versus you know just a consequence is something like a goal setting where you get some sort of warning when you're sure you know not meeting your goal or when you're about to exceed your this your goal of energy use for the day right for example our you know our on our cell phones for example when we're low on batteries right it gives us it makes this little noise and it says you know you down to 20% you better plug in well what if we all had a goal for how much each day we wanted to use for you know energy in our home and we're getting close to that goal we get some sort of notification on our cell phone says you know you've almost used up enough energy for the day you better you know better slow down and that's like this kind of feedback that that no system as far as I know is giving yet right it's giving how much have you been using but no alert prior to not meeting your goal to let you know like here's how you're doing on this goal for the day the week in a way that could modify behavior before it's too late right feedback after you've done it okay well next time I'll be better well how about how about giving us a feedback in the process of today we do better yeah and end there and I think that there are a couple newer technologies that are starting to do that and that's why to me this is such exciting research and such exciting time to be doing it is that almost every day when I listen to NPR I hear something about the Internet of Things this future in which we are all connected and everything's measured and that's kind of what were what this is connected to we're hearing a lot this morning I heard something about these you know fit bands and jawbone ups and tracking everything that we do Google that discontinued the power meter four years later bought nest which is an automated home Learning Thermostat for over a billion dollars and so this is I think the direction we're going in and there's a lot of really innovative stuff going on in the tech sector and as sometimes happens research tends to be the research community is testing solutions that are far outdated as compared to what's really going on and so I'm trying to yeah figure out how to but I think that but that these startups contact us because they know that the cycle that getting the psychology right is so important so they're designing things decades beyond what we're studying and then asking us to inform their development so there's this really interesting temporal gap that I'm in the middle of and I'm excited about and I think your comments are all getting it my issue of how we're where I where we fit in as academics where how and where can I undo I fit in and I'm figuring that out and so these are all really great comments for that and then when I said creative new ways of thinking about you I had in mind this was stuff not necessarily capturing what's being done mentally but sort of more modalities like we could think of feedback in a completely different way to link to this or coming at this time we're being delivered through this system rather than just suggesting this was the only way to feedback because I just think that this is this is a platform for allowing that creative moment where you say you know what why limit ourselves to one modality of feedback there's no real obvious reason to do that technology allows us to have centers in people's clothes that give them wild shocked when they use too much energy our detectors the like I mean that would I will be hung Energy's the point is that there's lots of other way as imagine and so I was thinking word of modalities rather than just capturing what is what what they're doing in an engineering labs at Cal I Caltech and I think that you could do okay even though it's hard to stay abreast of what the real world engineers are figuring that yeah yeah thank you we'd like to open it up for discussion of all of you that specific analogy I do it was that so the the first reference was made by Kempton in Lane in 1984 and so a lot of people pick it up I love it I think it just gives it gives us something to anchor on that we can understand for me that the AHA and when I became interested in this was and I could pinpoint the exact day but I don't remember it off stab my head but it was spring of 2009 and it was when google.org which is the philanthropic arm of Google released a press release in their blog that day they announced power meter and I remember reading that and they said Google is going to link with utilities and give you this information so I didn't glom on to the supermarket analogy but this idea that and Google and they said Google is now going to work with the Joe's and give you date you know use during the day and blah blah blah and I thought that was so cool I was scrambling to come up with a topic for this meta-analysis course and then it it linked the the press release linked to the most cited probably paper in this area which is a 2006 paper by a great researcher at Oxford Sarah Darby that was a qualitative literature review self-published it was a white paper that came out of the environmental change Institute at Oxford and and again it wasn't incredibly empirically rigorous it was like I kind of looked around and here's what I found and it was the most cited paper in this area and I I thought wow there's a lot of potential here to drill in as we're seeing this internet of things just over the horizon we're spending and that same year or was 2009 or 2010 was when the stimulus package allocated four billion dollars to the smart grid so we see this enormous amount of money the expected cost of this transition to the smart grid is 165 billion dollars just in the US and so we're changing the global infrastructure around energy and people are so excited about the potential of it and then there's the broad public that doesn't care at all and and so it just seemed like gosh this is a place where I could contribute because there's so much potential and there's so much that we know in social science that's not being applied at all like here's this academic community and here's these people that are going out doing this stuff in the real world and it didn't seem like there was a lot of translation and so that was really I guess the light bulb for me was seeing like this seeing Google getting involved because I was interested in technology and the role of Technology and pro-social behavior and this was like how could you get better bigger than Google getting into energy use so that was the the big kind of click yeah in my high school life I work with community and one of the issues that we talk about a lot as a problem and advocacy problem is that person who is inclined to do the right thing and to make a difference you don't really know what are the big items versus the small tech items so you know plugging in your iron might not be a really significant gesture and and so some of those things you know like people get very excited about solar energy use but it doesn't make sense necessarily on the individual homeowners level so there's there's an impulse to do something but you're not necessarily directed towards making those big contributions changes so for example you know everybody gets all excited about low gas mileage cars but in fact if you don't buy a new party probably save more energy energy bottom low mileage apartment so I'm wondering given the framework that you've been working and how your research can make a contribution towards helping people understand those kinds of choices yeah that's it yeah that's that's a great comment and and I think I mean I think that's one of the the keys the key benefits of this is that and I really like the way that the white house on the green button initiative frames it because of course they're trying to be a little more bipartisan and so it's not like we're going to give you this information so you turn off your lights when you leave a room it's you have a right to know what's going on in your home just like you know just like that grocery store everything is using energy you have a right to know what you don't need to turn off as much as what you do need to turn off that that when armed with data just like the United States government mandates that packaged food includes nutritional information shouldn't the electricity as we're investing billions of dollars into the smart grid should we shouldn't we conversely be allowed to have access to that information rather than it being seen as a pejorative intervention that the government is and utilities are giving you this data in order to get you to do something that you can look at it as why be right to know what's going on so that I can make better decisions now of course how that information is presented in some of the work we've done that's not in this dissertation shows that when you present information in different ways there are ways of framing information that's more likely to get people to act and then there's ways of framing information that's going to raise awareness and those might not be the same and so it's important that that we think about what is the goal is the goal to educate people because you can create passive systems you can just create a smart home that ignores the occupant so that you don't need to be like constantly paying attention to what's on and off and going but is the goal for us to be better and this is where Richard was getting at is the goal for us to kind of be better connected to resource use to kind of use this as an opportunity to remind us that fossil fuels are literally organic matter is this an opportunity to do that to connect us to what it means to be human to what it means to be alive to what it means to be a part of this system or is it just a way to cut carbon emissions as part of this portfolio that includes solar and wind and so I think there are these big questions about what is the goal of feedback because you can present information in a way that gives people that data or you can kind of simplify it to get as many people to do as many of the behaviors that you want them to do as possible but I think that ideally we are using this so that people can identify the real footprint of their actions and I think that goes beyond the scope of this project I know I was working I was brought in to consult on a zero net energy project a couple years ago in Palm Springs and they were looking at the zero the energy use of the homes but this was a retirement community and I thought but what about how much they're moving and leaving what about these other things that a zero net life is not the same as a zero net home and that might get beyond the scope of this specific dissertation but it's definitely something I'm grappling with in kind of the broader implications of my work in future steps that answer address zero net life that really does give to that that question that I was that I was grappling with you know thinking about for example when we are trying to be thoughtful consumers and we purchase low energy use appliances but we don't actually know how much energy goes into making yeah and this is specifically looking at direct energy electricity so the embedded or indirect energy and all the things that we use like our televisions is not incorporated in a direct kilowatt hour cost but I think ideally there are other ways to incorporate that but then it gets really complex you get that kind of brain melt stuff but this is why I think psychologists are important to have involved because we need to think about not just how many data points can we put in but how do we make that palatable or interpretable Chrissy did something Kristin my first thought is we're looking at direct energy that there's so much in the life cycle before you're made but then we also have this energy water Nexus and I was wondering do you think these applications with the feedback and the information access to be transferred into the water realm for warriors I know there's a lot going on but do you think that the same principles and the same water feedback technology could be there to help kind of tie the youth between water and energy and then could you even to get back up because you use this many fewer gallons per day or so you get down to this below the hundreds would that be something that could then go back into the energy do you think that are you seeing it going in that direction do you think the psychological dimensions would be the same as you can get be so vastly different because we can see the water that comes out of our tap we can see all of those actual interactions with our water even though we don't see the source or where um no it's a great question I think I think psychologically it's very similar you know we're drinking water because we're thirsty not because we want fish today and so so that idea of kind of linking self-referent self relevant goals to consumption of something that's kind of a commodity is important on the technological side I think electricity is easier than water which is why more people work on it but there are some folks John Froelich who's at the University of Maryland is doing some stuff where they're measuring the the frequency of water coming out like the waves that are coming that are coming out of the pipes to disambiguate so you can pull from one water main and tell that this is the upstairs toilet and the downstairs and this is the shower so there there is some work being done on that there is less work in water than there is an electricity but I think it's definitely there's some research and definitely a lot of this will can apply to other domains to things like the indirect energy use in the food we eat I mean there are lots of it's the technical of how do you get when you eat something you know how would you get the carbon that's more like Dan was talking about the antecedent feed-forward because it's harder for you to eat a steak and have your plate tell you you just consumed you know but I think in water that is one where not only psychologically but technologically you there are a lot of strong corollaries and it can be extended some of the committee and then I saw and I think I told most of the folks that are that are here

Channel: ZarlabUCLA

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Id: w7PZsQmOg7A

Length: 87min 54sec (5274 seconds)

Published: Fri Apr 25 2014