Queer ecological data: Where artificial intelligence meets the avian

Abstract

Nonhuman life is increasingly analyzed and acted upon through big data and AI tools. Birds in particular are among the most datafied wild beings. However, avian—like human—data sets present challenges of bias, misclassification, and harmful collection methods. For example, avian data includes bias along lines of sex and sexuality, female, queer, and intersex birds are significantly understudied. These missing birds not only represent consequences for biodiversity loss but also “naturalize” assumptions about sex and sexuality for all species, including humans. In this article, we interrogate avian datafication practices and introduce Salvaging Birds, a multimodal project proposing “queer data surrogacy” as a method for generating “queer ecological data,” that is data resisting normative environmental frameworks. Here queer data surrogates were produced by creatively subverting AI toward generating speculative missing birds. Bridging critical data and archival studies with queer ecology, we argue that data logics demand examination at nonhuman sites and scales.