Shikakeology: Designing Triggers for Behavior Change: Papers from the 2013 AAAI Spring Symposium
and
Graduate Institute of Networking and Multimedia,
Department of Computer Science and Information Engineering
{
National Taiwan University d00944010, r00922153, r01922132, r01922040, r01922085 } @csie.ntu.edu.tw
National Taiwan University yjhsu@csie.ntu.edu.tw
Carnegie Mellon University - Silicon Valley ted.selker@sv.cmu.edu
Abstract
There are many problems around us need to be solved by human agents. It is very challenging to persuade people to change behavior implicitly, especially for solving public problems. We leverage persuasive mechanism for increasing incentives to change human behavior in a problem solving framework. By linking feedback to the actions, we’ve been able to increase the incentives to trigger behavior change. We deploy two persuasive feedback system in a building to support energy-saving scenario. By integrating sound feedback to window closing behavior to make people aware of the energy problem in the public space.
Persuasive computing has a long and optimistic history. In fact, many persuasive systems have formed short of their goals. In many cases, even people can recognize the value of improving their behaviors, but they might ignore them or feel resentful of them when they don’t have proper feedback.
Examples of people not improving their diabetic care, even having many notification emails, In some cases, visceral feedback has been recognizable and valued by the listeners. For example, in the counter-intelligent project(Bonanni,
Lee, and Selker 2005), when a refrigerator door is opened, people often have experience of getting goose bumps when they heard wind sound and saw snow projected on the refrigerator. On the other hand, when words are played on the front of the refrigerator door saying ingredient, people don’t care. But when they have a picture that what is inside the refrigerator come up as you walk towards it, people open the refrigerator door not so often. The idea of linking the sound to opening the refrigerator door has an immediate physical response for people and makes persuasive computing work better. The mixed initiative approaches works again better when a stove has the word hot on the back drop and those are replaced by flame and cracking noise of a little fire. People turn off the stove more often. To apply these principles
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to a more common situation in a normal building, we started by using the Sweetfeedback, a USB-connected persuasive device and deployed in the building of Department of Computer Science(CS) in National Taiwan University(NTU).
By using the Sweetfeedback USB-controlled gumball machine we learned that it is easy to give people personal feedback when and where they’re working. While our first prototype demonstrated that the window might be closable and then improved working environment in the Sustainability
Base building in Mountain View, CA. Our current interface takes our experience from Sustainability Base and move to a platform while we initially use the Sweetfeedback. We quickly moved to use standard computer and wind sound and graphical feedback to aware people of the problem. We began by analyzing the agents involved in a persuasive interaction. Indeed, it is a mixed-initiative scenario in which the computer is trying to communicate with people in a closed feedback loop and change their behavior. The fact is that many of such interactions get stuck because the person resents the communication or does not understand the communication or does not get the information. For this purpose, we’ve decided to build a framework for understanding how the person interacts with this kind of situation.
In this paper, we present an agent-based problem-solving framework in which we exploit persuasive feedback mechanism for increasing incentives to change human behavior.
In our work, we proposed several types of feedback including metaphor, visual, social, tangible and emotion feedback.
They can be applied in our framework for different purpose persuasion. Some are used for increasing the incentives and some are used for providing meaningful experience to help people associate with a specific action. To demonstrate our idea, we built a system by apply our framework with those feedbacks to support an energy-saving scenario in a normal building. We developed an application using graphical interface for displaying windows status of the building to make people aware of environment and adding some game factors to motivate people to report or solve energy problems.
The paper is organized as follows. Firstly, we go through several related work on persuasive computing and feed-
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backs. Moreover, we presents our framework design and apply it to a energy-saving scenario. The detailed implementation of hardware and software system are discussed in the coming section. In addition, some pilot study’s results are presented in this paper to examine our design. Then we summarize and present direction of this project in the future.
Waterbot(Arroyo, Bonanni, and Selker 2005) exploits audio and visual feedback to motivate water conservation behavior. Continuous visual feedback helps users track water usage. An appealing sound plays every time when user closes the tap. It helps to form an attitude to reduce water consumption by creating a social experience at home.
Augmented reality kitchen project(Bonanni, Lee, and
Selker 2005) proposed a solution that utilizes the concept of counter-intelligence which provides information to coordinate and instruct cooks on the use of the kitchen. Using natural instruction such as image or sound, they connected these instructions with sensed condition in the kitchen very well, and so that to make the interfaces very intuitive. From this study we would like to borrow their experience, and survey if linking these natural instructions as our feedback to the corresponding action can help our persuasive system to work better.
We learned from Heimerl’s work(Heimerl et al. 2012) that proper incentives for the targeted community and location will increase motivation. For example, teachers in elementary or senior school might bring candies to class sections to enhance student’s participation. The scenarios in our study are also on campus and the participant are also mainly students, so that tangible feedback like candies can connect behaviors with good experience for our participants.
In order to reach the goals of solving problems, we define three agents, each of which can be either programs or human beings:
• Reporting agent: discovers or senses, and then reports environmental problems waited for approval and the action is called “reporting behavior”.
• Verifying agent: approves the reported problems or verifies the solutions declared in the waiting list and the action is called “verifying behavior”.
• Solving agent: picks up confirmed problems to solve them and the action is called solving behavior.
The life cycle of a reported problem is tracked through state. As in Figure reffig:framework, we allow a problem to change its state caused by a reporting, verifying, or solving behavior. The solid lines indicate the agent’s behavior. A new problems is created by reporting behavior, confirmed by verifying behavior, resolved by solving behavior, and finally closed by another verifying behavior. To ensure whether people actually performing those behaviors or not, the problem-solving framework cannot work well without verifying behavior.
Since there are three essential factors, which are motivators, triggers, and ability, to achieve at the same time for an behavior to occur in Fogg’s behavioral model(Fogg
2002)(Fogg 2009), our framework includes several persuasive feedback to motivate and trigger people’s behavior by enhancing their awareness of existing environmental problems. The dashed lines in Figure 1 indicate the feedback which influences a human agent. The types of feedback are shown in Table 3. To trigger actions, we adopt metaphor and visual feedback while social, tangible, and emotion feedback is aimed at increasing the motivation.
Figure 1: The relationship between the transition of the problem state, the agents’ behavior, and the persuasive feedback system.
Type Definition
Metaphor Feedback It provides a meaningful hint to make people associate with a specific problem or behavior in daily experience.
Visual Feedback
Social Feedback
It provides detailed information about the environmental problem.
It creates connections among people by sharing mechanism. Social impact would influence human behavior effectively.
Tangible Feedback It gives a tangible reward for raising the incentives to perform a specific behavior.
Emotion Feedback It provides an affective experience for increasing empathy to motivate behavior.
Table 1: Five types of feedback are defined in our framework.
In the CS building, the majority of power consumption comes from air conditioner (AC) system. To reduce the electricity expenditure, the AC is running now only during the
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daytime. We observe the often wrongly placement of window. In order to reduce the unnecessary activation of the
AC and thus the waste of energy and money, we would like to make people close windows in the daytime when the AC is turned on. On the other hand, windows should be open to remove the heat accumulated indoor after the AC is shut down or it will be additional burden for AC in the following running. (See Table 2 for details)
Time AC status
Day time
Night time
On
Off
Problem
Lots of cold air emits outdoor when the windows are opened
Temperature, humidity, and CO2 concentration raise with the window closed
Task
Close the windows
Open the windows
Table 2: AC policy and corresponding environmental problems and solutions
Based on the problem-solving framework, we designed a social application. We deployed Sweetfeedback 1 , which provides tangible and sound feedbacks near the window, placed monitors to present the visual feedback, and installed sensors to detect the windows. As for the application user interface, we provide a web page for monitoring and visualizing the problems in our building, as shown in Figure 2. The desktop version is on the left and the mobile version is on the right. It consist of three parts.
• Problem map visualization: The ”problem map” visualization displays problem on the building’s map. We use red color to indicate where the problems are. Take the figure 2 for example, it is a screenshot at the daytime. The
AC is on therefore the open windows are labeled with red color to notify users. Users can simply check our web page and know which rooms are getting into troubles or which windows are in wrong status.
• Report-problem interface: There is a report-problem button on the web page. Users can click the button and choose a location to report an environmental problem.
• Report-solution interface: For the mobile user, we provide a QR code scanner as an interface to report a solution to the server. QR codes were encoded with location id, and were pasted next to each window. Whenever the user follows the AC policy to open/close a windows, he/she can scan the QR code and get reward.
Table 3 are the details of the corresponding feedback in this scenario.
Because opening window is an easy task that everyone have the ability to achieve, what the users need is reminder and motivation. First, the visual feedback makes people
1 http://sweetfeedback.com/
Type Description in Scenario
Metaphor Feedback The speaker will utter the sound of wind blowing and emit wavering light. We hope this kind of feedback can remind people about the environmental problem intuitively. So when the user is about to leave a room and feels the wind is blowing, the user will close the window.
Visual Feedback
Social Feedback
We show the “problem map” to indicate where the problems are.
The leader board for problem solvers.
We assume that competition among peer can enhance user’s motivation.
Tangible Feedback Candies, which are tangible and “sweet” feedback.
Emotion Feedback Emoticons or Emotional avator.
Table 3: Five types of feedback are used in our scenario.
aware of the problem. People then check the “problem map” to know the windows status. Tangible feedback aims at enhancing people’s motivation. By dispensing candies, users can taste the sweet as a reward. Social feedback is a virtual mental reward. We assume the affect between peers can help spread behavior change to other people in the same building.
(See Figure 3)
In this case, people only play the role of solving agent and notify the system by scanning the QR code stuck on the window frame via an app while the system acts as both the reporting and the verifying agent. The system also collect and analyze the environmental context (including the AC system status, window status, humidity sensor reading, indoor temperature sensor reading, current time), and report a problem if the window status is against the AC policy.
Figure 3: A use case for persuading a energy-saving behavior.
We implemented a system based on the proposed framework. The system architecture is shown in Figure 4. In the
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Figure 2: The screenshot of website and ios mobile application.
following, we will describe its hardware and software in detail and how it realizes our framework and scenario.
ing section into two parts, server and client, and describe their functionalities separately.
Figure 4: The deployment in NTU CS building 3F.
Our system deployment diagram is shown in Figure 4. 16 reed switches were installed on the windows to get window status. The switches are linked to Arduino boards. For reliable communication, the sensor data is sent from arduino to the desktop by serial port, and is then inserted to the database. We placed two public desktops at the hallway to promote our application and enhance peoples awareness to the problem. The desktops are used to visualize problem, provide feedback, and relay data. Each desktop is connected with a Sweetfeedback, and a program is running on the desktop to dispense the candy when the server commands.
System Architecture
The software architecture(Figure 5) follows the design principle of our proposed framework. Here, we first talk about how we implemented the Persuasive feedback system. It defines the feedback mechanism. Then we divide the remain-
Figure 5: The system architecture.
Persuasive Feedback System
We implemented a centralized persuasive feedback system.
It is composed of feedback policy manager and feedback requester. Their relations are like server and client. Their definitions are as below.
• Feedback policy manager defines the feedback policy, and decides what kind of feedback to give, when, where, and how to give the feedback to the user.
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• Feedback requester is responsible for giving feedback. It asks feedback policy manager whether to give feedback to users.
The feedback policy manager locates at the server side governing all of the feedback policy. The benefit is that when we want to change the feedback policy, we simply modify it at the server side and the system can quickly adapt to it.
Server
Server consists of three parts. We describe each in turn.
1. Reporting Agent: The server analyzes the raw sensor data from the database, and automatically report issues if some problems are discovered. In our scenario, the reporting agent query the window state data and current AC policy to make the judgement. If the window state is not align with the policy, the agent raise a problem, and insert it into the problem collection in the database.
2. Verifying Agent: We implemented an agent that verifies whether a solution proposed by users is valid. When user report a solution, verifying agent uses window state data to verify whether the user indeed solve the problem. If the user did, the agent set the solution as a valid solution.
Otherwise, invalid.
3. Feedback Policy Manager: Feedback policy controller plays an important role and it realizes feedback mechanism. In our case, it allows the speaker uttering wind sound when a window is not closed in the daytime, or allows Swetfeedback dispensing candy if someone solves a problem. When the controller gets a feedback request, it uses historical and current information in the database to decide whether to allow the feedback or not.
Client
We provide mobile and desktop interfaces for end-users to interact with the system, as shown previously in the Scenario section. Now, we focus on how clients realize our centralized persuasive feedback system. Clients act as feedback requesters. They provide different feedbacks depending on their equipment. We are going to talk both of them more in turn.
1. Mobile Client
We provide a mobile application on both Android and iOS platform. As a feedback requester, it provides two feedbacks:
• Visual feedback: The mobile version of problem map provides user some mobility. User can see the map and go to fix the problems.
• Sound feedback: When a user do the right action and scans the QR code, the mobile client reports to the server that the user fix a window problem and makes a feedback request to see whether it can give the user positive feedback. If the policy manager approves, then the mobile plays the mario coin sound effect to reward the user.
2. Desktop Client
At last, we will talk about the desktop client. As a feedback requester, it provides many kinds of feedback in our system. In addition, the desktop client serves as a reliable sensor data relay since it is close to the window sensors.
• Feedback Requester: The feedback requester make http request to the feedback policy manager to ask whether to provide the following feedback.
– Visual feedback: The problem map website host by the server.
– Metaphor feedback: The wind sound from speaker.
When a window is not closed in the daytime, it asks the feedback policy manager whether it can utter wind sound.
– Tangible feedback: Candies from the gumball machine. When a user solves a problem, the desktop client asks the permission to dispense candies to the user from the feedback policy manager.
• Sensor Data relay: The relay program is implemented with processing. It communicates with Arduino board via serial port. Whenever this program detects window state change, it calls the database api at the server side to insert the latest data into the database.
To evaluate the effectiveness of our system, a pilot study was conducted in NTU for three days. Two persuasive systems are installed in CS building. There were six participants involved in our study and they were asked to install our mobile app on either iPhone or Android. During the experiment, we randomly created some wrong window state for participants to correct those problems and get candies from our system.
We designed an evaluation protocol to determine whether our system can achieve the goal about behavior change. Pretest questionnaire asked the users to provide their retrospects to the closing/opening window behaviors and the reporting/solving behavior in the past. Post-questionnaire asked the users to rate satisfaction score by 5-point Likert scale.
The pre-test result shows that all six participants knew the
AC policy but there are still two persons didn’t frequently close the window when air conditioner is ON in the daytime.
More than half of the people frequently open the window when air conditioner is OFF during the night. Five of them didn’t report or solve any environmental problems from past experience. The statistics of post-questionnaire is five people agree that our system can encourage them perform the energy-saving behavior.
For each feedback design, five people agree that visualization such as problem map and window status can make them aware of environmental problem in our building. Half of them think that leader board and emoticon can increase the motivation to solve the problems. All people consider that wind sounds well notifies them of the window problems and express that candies as tangible feedback can motivate them to solve the problem effectively.
This paper demonstrates the possibility for leveraging the persuasive feedback mechanisms in a public environment
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to deal with the existing problems. Our studies show that the proposed problem-solving framework could establish the link between the feedback and the wanted actions and enhance their motivation
Although the system has been stably running for a week, it is planned to continue in a longer period and to recruit more users. Feedback can be applied at a more personal level.
We would allow the system to change the policy to give different set or amount of feedback according to the time, the location, the level of participation, or the timing of the response. Even more, we would try to reduce or discontinue the tangible feedback after some time to make this linking become a long-term habit.
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