SALVAGING BIRDS

(forthcoming)

expanded nonfiction project

In the face of human-caused biodiversity loss, conservation efforts for avian and countless other species have turned to data. Much like human datasets, however, conservation datasets are an imperfect tool. They contain biases and misclassifications, are collected through harmful practices, and have the potential to distract from the systemic causes of the problems they are purported to solve. Salvaging Birds traces these logics of environmental datafication. Experimenting with a form that Livio calls “expanded nonfiction,” it is a research-driven project consisting of an essay, machine learning-generated birdsong, generative digital imagery, and music. By examining sites such as natural history specimen collections, as well as by speculatively queering birdsong datasets, the work complicates datafied approaches to conserving what and who is left of our world.  

Concept: Maya Livio
Research & Writing: Maya Livio
AI-Generated Birdsong: Maya Livio, JP Merz, Raymond Finzel
Composition: JP Merz
Images: Cassie McQuater
Website Design: Maya Livio

Commissioned by:
Environmental Futures initiative, with funding from the Andrew W. Mellon Foundation


Notes:
  • With thanks to the Cornell Lab of Ornithology’s Macaulay Library and Erin Espelie.