Month: November 2018

After collecting feedbacks for the second version of the bird cage device, we discovered the following issues regarding its design:

1. The interaction between the users and the project is flat, as the device only takes in one user input (which is assigning topics to the cages) and respond only once, regardless of how fancy the response looks.
2. The previous design makes a metaphor between tweets from Tweeter and the shape of bird cage, which make some sense. But this is mostly a connection based on the visual aspects of the two, rather than the tangible aspects – in other words, how a user is actually interacting with the physical form of a bird cage, the space that the cage occupies, and the bird inside the cage, etc., is not considered throughly enough.

After some discussion with Nick during the weekend, we decided to throw away the idea to make a physical representation of Twitter API by weighting how many people tweets on two given topics, and switch to focus on one of the actions that are most important for a person to own a bird cage – to put a bird into the cage. Based on this, we made a cardboard prototype to simulate a bird luring process. By throwing in hashtags of a topic on Twitter, we will lure an invisible bird that represents the Twitter data on this topic into the bird cage.

Following this design and a quick feedback from Tom, we further discussed what are the possible interactions that can both take advantage of people’s bird keeping behavior, and at the same time connects it to some intellectual activities that cannot be achieved by merely keeping a physical bird from the nature. I realized that since the bird is a representation of Twitter data, it is also a representation of the public’s opinion of a topic.

In the real world, by feeding the bird with some food and observing how the bird react to that food, we can know whether the bird likes it or not. In the same sense, if we feed the public data bird with a particular kind of thinking, by observing the bird’s reaction, we can have a physical glimpse into the public’s opinion or attitudes towards that thinking.

Further, I realized that this provides an opportunity for us to measure or rethink how our perceptions of social phenomenon are different from the larger public. Living in a physical environment, the opinions we possess are inevitably influenced by the people we engage with on a daily basis. For instance, the result of the recent midterm election in New York turned out to be quite different from a lot of people’s prediction at NYU. As someone who lives in a liberal community inside a liberal state, it is not uncommon that she/he’s gauging of the public’s attitude is somewhat biased. And this provides a good opportunity for us to reveal this bias through our feeding action with a public data bird.

So for version 3, we’re planning to create an invisible bird that allows users to guess and reflect on the guessing about public’s attitudes towards controversial topics on social media, as shown below:

After collecting feedbacks from the lovely ITP community, I realized that the previous design about aligning AR with the physical world is a bit farfetched, in terms of the following aspects:

1.  The starting point of the project is not self-explanatory enough. As urban people nowadays rarely play with sand, the “grab-wand-and-draw-pattern” action will need to be explicitly instructed, or printed out on the  project itself. And this somewhat makes the project not intuitive.
2. The physical feedback of actions occurring in the AR world are missing, since the battle is visible only in the AR world. And the audience wouldn’t notice the changes in the physical world unless the monster is defeated in AR and then transforming into a physical smiling face. This somehow gives a feeling of “using AR for AR’s sake”. It is likely that the audience will merely sees it as an enhanced AR game.
3. Since the audience’s commands are derived from continuous drawings on the sand, it requires them to clean up the previous pattern before a new one is drawn. The cleaning process can be a bit cumbersome, and the project does not provide a feedback of a “clean and ready” status. Also, the timing of cleaning and drawing can be tricky, since everyone may do it differently.

Given the above comments, I realized that emphasizing on the “interaction between moving AR objects and physical objects” is perhaps not a very good idea, or at least, it requires other forms of designs to make them working together really well.

After a discussion with my ITP classmate Nick Tanic, I realized that instead of focusing on the “movement relationship” between AR and physical world, maybe focusing on their differences in “visibility” is a better idea. As we know, physical objects are present all the time, while for AR objects, we still need an interface or a medium, like an AR-enabled phone, to actually see them. Since Nick is having an idea about using bird cages to visualize tweets, it rang my bell as it could become a wonderful stage for playing with this difference in visibility. So, we decided to collaborate on our finals, and. here comes the design: an AR-enabled bird cage system that visualize the quantitative differences in any given two topics/items/phenomenon and reveals trends of people’s topic selection.

Major Functional Elements

The concept of this installation originates from a idea about making a tool to measure social phenomenon. It will be comprised of four major parts:

• a chandelier-like hanging structure
• two empty bird cages that can move up and down
• an application that is connected to the Twitter API and instructs the installation to move one bird cage up and the other down, behind the scene
• an application that reveals what’s inside the two bird cages by using AR

How it works

The bird cage installation is made to measure social trends on twitter. The audience can come up with two hashtags they want to compare, (e.g. pizza vs burger, or Trump vs Hillary), and assign these hashtags to different cages. The up and down movements of the two bird cages will be synchronized with number of people who tweet about each topic. To see what’s being compared visually, the audience will pull out their phones and enable AR to see what’re inside the birdcages and being compared.

Since the audience will be doing two tasks: the topic assignment and the AR observation, it’ll be boring or less surprising for them to perform these two tasks in this order, since the assignment process somewhat gives away the AR contents. On the other hand, it will be interesting to reverse the sequence, and interpret it under a larger audience context. A possible workflow will be:

1. We pick two topics and assign them to the bird cages;
2. The cages move accordingly;
3. Audience A comes to the bird cages, and see two imbalanced cages;
4. Audience A pulls out his/her phone, and discover what are really being compared in AR;
5. Audience A assign two new topics, and leave;
6. The cages move accordingly;
7. Audience B comes to the bird cages, and see two imbalanced cages;
8. So on so forth.

And this creates an interaction among the installation and the audience flow over time.