Sept 2019–Aug 2021
Broadcast is particularly focused on what we call ‘Imaginary Leaps’— the conceptualization of places and spaces that data venture to on their journey to and from the home. We argue that more abundant, playful, and imaginary encounters with home data might offer a site for reclaiming data for home dwellers. Broadcast uses sound as an analogy to interpret and imagine data’s travel. Specifically, the sounds focus on two aspects of data: how they travel, and where they go. Broadcast provokes people to imagine data’s volume, speed, intensity, and destinations.

Broadcast is one of the three artifacts in the Odd Intepreters family. View project details for Soft Fading and Data Bakery.
Audrey Desjardins
Miki Bin
Ruby Peven
Justin Petelka
Abhyudaya Gupta
Aman Mohammed
Tom Liu
Trevor White
Min Jung Koo
Broadcast tunes into Alexa’s data traffic activity in and out of the home, and interprets the data’s travel into imaginative sounds.
Broadcast is comprised of a raspberry pi microcontroller, a small speaker, and a rotary encoder attached to the blue resin sphere.
Early on in the process, we were drawn towards the idea of a dial so that people could ‘tune into’ data.
When we originally proposed this concept, we had imagined that data were sent and received only when interacting with Alexa via voice. We were under the impression that Alexa is only active once her wake word is spoken. However, to our surprise, Broadcast showed that the Amazon Echo device is constantly sending and receiving data: it is checking if it is still online, if there are new updates, etc.
Sound Design
We worked with a sound designer, Trevor White, to create 14 soundclips that could represent the modes in which data travel in and out of the home. These sounds are inspired by physical places data travel (e.g. data centers) and how data travel (e.g. while in tubes or underwater).

These two categories of data’s journies, Data in Transit and Data at a Location, comprise Broadcast’s sound design.
The ephemerality of Broadcast’s sound design and interaction is important to demonstrate how data are always moving, they are not in the home, but rather part of large meshes of mobile data.
Audrey Desjardins, Jena McWhirter, Justin Petelka, Chandler Simon, Yuna Shin, Ruby K. Peven, and Philbert Widjaja. (2023). On the Making of Alternative Data Encounters: The Odd Interpreters. CHI'23 New York, ACM Press.
Next Project
Data Epics