AgentSwitch

This post will examine the AgentSwitch system which provides personalized recommendations on how much users can save by changing their energy tariff and shifting their deferrable loads to off-peak times. The system is based on uSwitch API, an energy data store, and a set of algorithms for consumption prediction and appliance disaggregation. More information about the work can be found in the following papers.

- "AgentSwitch: Towards Smart Energy Tariff Selection" by Ramchurn et al. 

- "Recommending Energy Tariffs and Load Shifting Based on Smart Household Usage Profiling" by Fisher et al.

Here, I will point out some of the findings derived from the evaluation of the system. Please read the second paper stated above for details about the evaluation process. The some of the findings are:

- a certain level of percieved accuracy of the predictions is important to further engage with and trust information provided by the system. What I understood from this is that it is required for a recommendation system to provide some evidences for its predictions in order to maintain the trust that the system is well-functioning.

- the threshold that potential savings have to exceed to motivate the users could be lowered by some degree of automation. Notifications, limiting factors and controllability are significant elements for the automation. Semi-autonomous systems can reduce the threshold for potential savings as they will ease the hassle that actual users need to deal with.

- current monetary benefits does not sufficiently motivate people to change their behavior, monetary benefits can be supported by game-like rewards or effective environmental benefits for better motivation. More persuasion dynamics need to be applied into this domain so as to increase the motivation and evaluate their impacts. I will talk about persuasion dynamics in my next post.

Some interesting questions for intelligent interface community:

- how to present uncertainty in intelligent UIs?

- how the balance between user control and autonomy can be achieved in a flexible way without overwheling the users with requests and undesired system actions.

The application of AgentSwitch is available here.