Design Idea 1
This critical design idea acts as an intermediary between the users and their Alexa(through Amazon Echo), whereby they will be able to utilise this intermediary to control their Echo device. This concept can be pictured using the apparatus set up above. A decisional qualification was made here by defining the relationship between the magnitude of tilt and the amount of snow powder poured into the flask that filled with water. The level of boundary was determined based on the numerical value shown on the flask which is equivalent to the volume of diluted snow powder.
How does the visual traits relate to visualising boundaries?
- Playful/Stubborn - I think this may represent the way you express yourself which in turn shows the level of intensity while interacting with the devices.
Being Playful towards a device would mean that you are not afraid to try new things and that would represent your likeliness to give out your personal data unknowingly.
- Control/Change - either you are in control or being controlled. This relates to how you position yourself when interacting with a device, whether you like to take control or to be controlled.
- Friend/Authority - this is a measure of responsibility towards controlling your data, how responsible you are in terms of possessing your data. The more in control, the more you are responsible towards your own data.
- Fitting in/Standing out - this may serve as a measure of how responsive you are in terms of answering a device. The more standing out, the more responsive you are.
Although it’s an interesting idea, there were some drawbacks.
1. turn it on
2. turn the knob according to how you want your device to perform
3. wait until all the diluted powder fully rises
4. observe the levels based on the marks on each flask, then add them up as the final score.
5. see the chart above
Applying the conceptual result in practical application, the final score indicates the level of privacy on a user’s data which may require the user’s attention before going ahead with feeding such data to the device (refer to studio workbook to see full exploration on this design idea).
The importance of the product was not properly visualised as its control factors needed adjustments for every usage. For instance, the water and snow powder may need to be refilled and the flask cleaned up frequently.
It was inefficient and created complexities in keeping the accurate measurement of the quantity deployed as well as the volumes of mixture before summing the readings in order to give a final score for conclusion.
Lastly, I also think that it is reasonably difficult to fully understand the underlying concept. So I will explore another idea to better visualise the implementation of boundaries, making the product easier to comprehend.
Design Idea 2
This design idea also employs critical design approach through emphasizing the importance of securing data through initiating dialogues between users. The apparatus set up in Fig 3.1 represents an intermediary device used in the interaction of the Amazon Echo and its users in order to visualise human’s boundaries with AI devices. The intention of using a bubble gun in the setting is to behave like a disruptive media in depicting the amount of data loss.
This idea focuses condensing the extensive layers of privacy into 3 sets:
Personal data - data that users might want to keep to themselves,
Family data - data that users would like to share with their family,
Public data - data that users don’t mind sharing to the public.
Before any interaction took place during the process, the bubble liquid was poured into each glass to represent full data capacity. The volume of liquid poured in each cup is correlated to how much data the user will be willing to share based on the grouping. The data fed into each group were set by the user who manually decided the allocation of various data that were considered suitable for each group using a mobile phone application. The bubbles blown away from the 3 separate glasses represent data loss during the user’s interaction with Alexa. Once the liquid finished, the dataset will be blocked from collection process.
Interactions can be interpolated in the following 3 steps:
1. The intermediary device detects the process of Alexa’s recording. Before the recordings reach Alexa, they are filtered and matched to determine which group- personal, family, public data- that these data may be categorized as.
2. Once this intermediary device determines the dataset group, the bubbles will be blown in accordance to the group type and how much data are potentially shared. This visual process would then allow users to recognise the machine’s activities.
3. The user still has the final say whether or not to share his/her data to Alexa.
This three-way-interaction would allow users to think twice about the data they are sharing.
Pushing the concept of this design idea further, I found a possible solution for improvement based on the feedbacks. A refined design that automates boundary visualisation as a method to solve the 3 main topic highlighted above. Hence, better function and more user friendly feature will be required.