Exploring the landscape of automated species identification apps: Development, promise, and user appraisal

Abstract

Two decades ago, Gaston and O'Neill (2004) deliberated on why automated species identification had not become widely employed. We no longer have to wonder: This AI-based technology is here, embedded in numerous web and mobile apps used by large audiences interested in nature. Now that automated species identification tools are available, popular, and efficient, it is time to look at how the apps are developed, what they promise, and how users appraise them. Delving into the automated species identification apps landscape, we found that free and paid apps differ fundamentally in presentation, experience, and the use of biodiversity and personal data. However, these two business models are deeply intertwined. Going forward, although big tech companies will eventually take over the landscape, citizen science programs will likely continue to have their own identification tools because of their specific purpose and their ability to create a strong sense of belonging among naturalist communities.

Keywords

user experience; digital citizen science; mobile biodiversity apps; automated species recognition; species identification

Published in

Bioscience
2024, volume: 74, number: 9, pages: 601–613
Publisher: OXFORD UNIV PRESS

SLU Authors

• Truong, Minh-Xuan

  • Department of Ecology, Swedish University of Agricultural Sciences
    

• Van Der Wal, René

  • Department of Ecology, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Other Computer and Information Science
Ecology

Publication identifier

• DOI: https://doi.org/10.1093/biosci/biae077

Permanent link to this page (URI)

https://res.slu.se/id/publ/132899