Kanon: oral traditions on the web

Philosophy

Social media platforms optimize for viral reach and algorithmic engagement, minimizing the possibility of intimate knowledge-sharing within close communities. Influential apps like Instagram and TikTok strip content of personal context and make any act of communication or sharing a performance that can be tracked and compared through likes, views, and followers.

I propose an alternative. Kanon enables small, isolated communities to build collective knowledge archives through manual curation of media and text. In addition, every element is connected to an audio recording from the user, pushing oral traditions to the center of the experience.

Kanon was built by balancing friction and automation, empowering users to add metadata quickly and spent their time listening to and recording rich audio narratives.

Design

Each piece of content is called a record and has media, metadata, and an audio narrative.

The connection viewing interface is split between previews of each record and the audio player. ElevenLabs's SDK (Speech to Text) takes each word and ties it to a timestamp in the recording, serving as the foundation for a beautiful listening experience.

To balance the friction-filled communication experiences, I created a collection of metadata & media fetching scripts tailored to users’ most popular media web sources.

If outside the scope and data quality is low, Claude Haiku API fills in the gaps.

Kanon is live to my community of friends and family. Public launch and full case study soon.

Experience the art exhibition experience here.

A social network, library, installation, book, and practice. In partial fulfillment of the requirements for the degree of Bachelor of Arts in Computing and the Arts at Yale University.