Sharing and Communication around Household Energy Consumption Tawanna Dillahunt Advisor: Jennifer Mankoff HCI Institute Carnegie Mellon University

U.S. households consume over 21.7% of total U.S. energy and generate over 21.1% of total U.S. carbon emissions [Gardner, et. al, 2008] Photo Missing

Low-Income Households 30% of U.S. households make < $30K/year [US Census, 2009] Spend greater percentages of income on energy than affluent households [Cooper et al., 1983] Median consumption almost as much as affluent households [Shui 2002] 3 Photo Missing

Opportunity Low-income individuals are among those more likely to live in rental housing [Belsky and Drew, 2007; McArdle, 2009] Renters constitute 30% of U.S. households [Current Housing Reports, 2008] Few studies (at the time) targeted low- income households and renters [Chetty, et. al, 2008] 4

Device Limitations Will household electricity monitoring devices work within the dynamics of a low- income household? What are the dynamics of low-income households in terms of energy consumption? 5

Previous Work 6

Qualitative Studies + Field Deployment Study 1 Energy Use in Low-Income Households [Dillahunt, et. al, Ubicomp 2009] Study 2 Conflicts Between Landlords and Tenants [Dillahunt, et. al, Ubicomp 2010] Field deployment Sharing and Communication around Household Energy Consumption 7

Qualitative study to explore energy consumption in low-income households –Do prior findings generalize to this community? –Motivations for saving energy? –Existing barriers? How can we enhance technology to serve low-income communities? Study 1 8

Photo-elicitation study [Clark-IbáÑez, 2004] –Camera –Pen and Notebook to write about experiences “Take pictures of objects and/or scenarios that make you think about personal energy use or anything that makes you think about energy” Study Design 9

26 participants across two locations –15 NC participants –11 PA participants Diverse payment structures  Pay energy in full  Receive stipend  Pay no energy  Receive allocation Study Design 10

Findings Participants received very little feedback Saving energy occurred even if participants did not pay for energy (prior habits) Key factors leading to environmental behaviors in low-income households –External barriers –Future generations –Religious beliefs Conflict between landlords and tenants around energy consumption 11

“The faster it [energy meter] spins, the more it costs. The more energy you’re using, the higher your bill is.” -Angela Existing Feedback

“I think of, okay, if I keep this [thermostat] on between 72 and 75, I’m going to have a low [electricity] bill” - Erica Existing Feedback

“This is what they call in our apartments ‘energy savers’. The green light is fine. The red light is what you worry about when that comes on in your apartment. That means you’re getting a light bill because you are over. And it helps a lot.” - Jacqueline Existing Feedback

Findings Participants received very little feedback Saving energy occurred even if participants did not pay for energy (prior habits) Key factors leading to environmental behaviors in low-income households –External barriers –Future generations –Religious beliefs Conflict between landlords and tenants around energy consumption 15

Findings Participants received very little feedback Saving energy occurred even if participants did not pay for energy (prior habits) Key factors leading to environmental behaviors in low-income households –External barriers –Future generations –Religious beliefs Conflict exists between landlords and tenants around energy consumption 16

External Barriers All photos taken by: Brian Photos Missing

Study 2 Interviewed landlords to get a balanced perspective Story-telling and role play sessions to understand both perspectives 18 Photos Missing

Sources of Conflict T ENANTS 1 P HOTOS + I NTERVIEWS L ANDLORDS I NTERVIEWS T ENANTS 2 R OLE -P LAYING Expectations ✔ Money ✔✔ Power Imbalance ✔✔

Sources of Conflict T ENANTS 1 P HOTOS + I NTERVIEWS L ANDLORDS I NTERVIEWS T ENANTS 2 R OLE -P LAYING Expectations ✔ Money ✔✔ Power Imbalance ✔✔

Sources of Conflict T ENANTS 1 P HOTOS + I NTERVIEWS L ANDLORDS I NTERVIEWS T ENANTS 2 R OLE -P LAYING Expectations ✔ Money ✔✔ Power Imbalance ✔✔

Sources of Conflict Summary T ENANTS 1 P HOTOS + I NTERVIEWS L ANDLORDS I NTERVIEWS T ENANTS 2 R OLE -P LAYING Expectations ✔ Money ✔✔ Power Imbalance ✔✔

Conflict Resolution T ENANTS (1&2) P HOTOS + I NTERVIEWS, R OLE -P LAYING L ANDLORDS I NTERVIEWS Knowledge ✔✔ Communication/N egotiation ✔✔ Community Action ✔

Conflict Resolution T ENANTS (1&2) P HOTOS + I NTERVIEWS, R OLE -P LAYING L ANDLORDS I NTERVIEWS Knowledge ✔✔ Communication/N egotiation ✔✔ Community Action ✔

Conflict Resolution T ENANTS (1&2) P HOTOS + I NTERVIEWS, R OLE - P LAYING L ANDLORDS I NTERVIEWS Knowledge ✔✔ Communication/N egotiation ✔✔ Community Action ✔

Conflict Resolution S TUDIES 1&2 T ENANTS S TUDY 2 L ANDLORDS Knowledge ✔✔ Communication/ Negotiation ✔✔ Community Action ✔ 26

Solution Sensing technologies and social computing can play a role in conflict resolution because of their abilities to provide new information and better communication of information 27

Opportunities Sensing technologies produce new information Social technologies facilitate sharing Both technologies influence action Photos Missing

Proposed Work 29

Key Focus Factors Sharing led to community action Better communication helps to resolve energy-related issues between landlords and tenants Negotiation helps to resolve energy- related issues between landlords and tenants 30

Thesis Statement Eco-visualizations designed to allow individuals to compare their consumption with others and to actively engage around actions that affect energy consumption will: encourage social interaction raise awareness of energy conservative behaviors help residents to negotiate energy use issues with stakeholders (landlords, housemates, community members) 31

Research Goals To develop a tool for supporting comparisons and social collaboration Identify how sharing and collaboration affect energy consumption and communication within communities? Longitudinal deployment across low-income households of real-time energy monitoring devices 32

Method 33

Speed Dating Flesh out usability details 34

Speed Dating Results Flesh out usability details 35

Website Design 36

Proposed Study 37 Longitudinal Deployment

Timing One year deployment Checkpoints every 2-4 weeks 38

Thesis Statement Eco-visualizations designed to allow individuals to compare their consumption with others and to actively engage around actions that affect energy consumption will: encourage social interaction raise awareness of energy conservative behaviors help residents to negotiate energy use issues with stakeholders (landlords, housemates, community members) 39

Family vs. Community (Option 1) Website FeaturesHousehold/Stakeholder Type Families/Internal (pc/family) Community/Externa l (kiosk/floor) Comparison ✓ Social/Discussion ✓ Alerts ✓✓ Current Consumption ✓✓ Consumption History ✓✓ Suggested Actions ✓✓ 40

Identity vs. Non-Identity (Option 1a) Website FeaturesGroups Identity (Group)Non-Identity (Non- Group) Comparison ✓✓ Social/Discussion ✓✓ Alerts ✓✓ Current Consumption ✓✓ Consumption History ✓✓ Suggested Actions ✓✓ 41

Social vs. Non-Social (Option 2) 42 Website FeaturesTargeted Group Single family household Comparison ✓ Social/Discussion ✓ Alerts ✓✓ Current Consumption ✓✓ Consumption History ✓✓ Suggested Actions ✓✓

Personal vs. Group Incentive (Option 3) Website FeaturesHousehold/Stakeholder Type GroupIndividual Comparison ✓✓ Group Incentive ✓ Individual Incentive ✓ Social/Discussion ✓✓ Alerts ✓✓... 43

Quantitative Measures Total energy consumption each month Number of actions “done” or committed to Website interaction –How frequently do participants access the kiosk/pcs? –How long do participants spend interacting with the kiosk/their pcs? –When do participants access the kiosk/pc? Issues reported/issues addressed over time 44

Qualitative Measures Pre/Post –Environmental attitudes –Environmental awareness –Attended education event –Did you interact with household members, neighbors, landlords about the data? 45

Main Contributions A tool for supporting comparison and collaboration across households Design recommendations for encouraging social engagement around energy consumption across multiple stakeholders Demonstrate the usefulness of social computing for ubiquitous computing around energy consumption An algorithm for predicting energy consumption based on community or individual conditions ? 46

Schedule 47 APRFEBMARAPRMAYJUNJULAUGSEPOCTNOVDEC - Sample Text On time!

Discussion Feasibility What’s more interesting (Option I or Option II)? What if no one interacts with the interventions? Do I need to add incentives? 48

Thank You Tawanna Dillahunt Sponsors 49