Trust-based Decision-Making forEnergy-Aware Device Management

Stephan Hammer, Michael Wißner, and Elisabeth AndréHuman Centered MultimediaAugsburg University, Germany

Motivation

Sensors:- to recognize situations

such as „user leaves room and light is on“

- Examples:- Smart Plugs- Brightness- Ultrasound

HomeMatic CCU to control electronic appliances

Smart environment that is able to support users in saving energy by proactively performing energy-aware adaptations.

Displays

Problem:If the system performs an adaptation which:

– the users do not understand,– the users consider inconvenient,– makes the users feel they are no longer in control,– …

then the users’ trust in the system might be impaired, resulting in lesser acceptance of and, in the worst case, disuse of the system.

Motivation

• Develop a user model, which:– chooses adequate actions to reduce energy consumption– models user trust in adaptive environments– chooses that action that will result in the highest user trust

User Trust Model (UTM)• Initialize the UTM with data gathered in an online survey• Evaluate users’ experience, acceptance, and trust

towards a system that uses the UTM in a real setting

Our Goals

• Trust is a very subjective concept• Trust is a non-deterministic concept• Trust is a multi-dimensional concept:

– Comfort of use– Controllability– Transparency– Reliability– Security– Credibility– Seriousness

Building the UTM -What is „Trust“?

Building the UTM – Example: Device = Light

Generic part (applicable for different kinds of self-adaptive systems) [1]

Application-specific layer

• Online survey (38 Participants)– Descriptions of concrete system reactions in concrete situations– Example: “You leave your desk for a short time (for example to

get something from a shelf) and your display is switched off automatically.”

Initializing the UTM – Gathering Empirical Data

a) Switch off Displayb) Ask To Switch off

Display Via Mobile Phone

c) Do Nothinga) Switch off Lightb) Ask Via Mobile Phonec) Ask Via Displayd) Do Nothing

• Online study (38 Participants)– Descriptions of concrete system reactions in concrete situations– Example: “You leave your desk for a short time (e.g. to get

something from a shelf) and your display is switched off automatically.”

– Ratings for the following statements (5-point Likert scale):• Q1: I understood why the system was reacting in this way.• Q2: I had control over the system.• Q3: I found the system comfortable to use.

Initializing the UTM – Gathering Empirical Data

Initializing the UTM

Questions 1-3 =>

Setting:• “Typical” day in an office• Different tasks• Changing context• After each system

reaction:– Transparency, User Control,

Comfort of Use, Trust– Preferred system action

User Experience and User Trust

Evaluating the UTM – User Study

24 Participants (18 male, 6 female, Age: 23-33)

• System actions (Light):– Consistently high ratings concerning Transparency,

Controllability, Comfort of Use and Trust– Lowest average rating (M: 3.92, SD: .86):

• Criterion: Trust• Situation: User is leaving the room• System action: Ask to switch the light off via the

user’s mobile phone• Reason: No Feedback on Phone

– System actions and users’ preferences differed• Reason: Repeated confirmations of system actions

via the mobile phone are uncomfortable and obtrusive.

Evaluating the UTM – Results

Ratings on a 5-point Likert Scale

• System actions (Display):– System reactions matched the users’ preferences

in all situations– Users wanted the system to decide autonomously– Only moderate ratings concerning Controllability

(M: 2.5 – 3.46)– Lower ratings concerning Trust (M: 3.63 – 3.88)

• Reasons: No Feedback when leaving, No authentication mechanism when arriving

– Still high ratings concerning Transparency (M: 3.79 – 5.0) and Comfort of Use (M: 4.0 – 4.58)

Evaluating the UTM – Results

Ratings on a 5-point Likert Scale

• Participants were satisfied (M: 3.96; SD: .68)• Participants did not feel:

– distracted (M: 2.00; SD: 1.00)– restricted (M: 1.83; SD: 1.07)– observed (M: 2.33; SD: 1.18)

• Participants acknowledged that the system:– supported them in saving energy (M: 4.71; SD: .54)– behaved adequately (M: 4.38; SD: .70)– was unobtrusive (M: 3.71; SD: 1.10)– was transparent (M: 4.96; SD: .20)

Evaluating the UTM – Further Results

• User Trust Model (UTM): – Generic approach for trust-based decision-making for the

adaptation of smart environments– Based on an empirically grounded Bayesian Network which

aims at maintaining user trust• Construction, initialization with empirical data, integration in

an office setting• User Study:

– UTM succeeded in maintaining users’ trust in a smart office environment

Conclusion

• Further analysis of the collected data:– Influence of user-specific attitudes (e.g. trust disposition) on

preferences concerning system actions and trust dimensions (e.g. Distrust towards technical systems -> Higher level of control by the user)

• Decision-making for more than one user

Future Steps

Thank you!Any Question?

UMAP 2014

http://www.informatik.uni-augsburg.de/en/chairs/swt/se/projects/oc-trust/

For more detailed information about the generic part of the UTM:[1] Kurdyukova, E., Andre, E., Leichtenstern, K.: Trust management of ubiquitous multi-display environments. In Krueger, A., Kuik, T., eds.: Ubiquitous Display Environments. Cognitive Technologies. Springer (2012)

http://www.it4se.net/