The potential for AI to revolutionize conservation: a horizon scan

Research output: Contribution to journalArticlepeer-review

Electronic versions

Documents

Links

DOI

  • Sam A. Reynolds
  • Sara Beery
  • Neil Burgess
  • Mark Burgman
  • Stuart H.M. Butchart
  • Steven J. Cooke
  • David Coomes
  • Finn Danielsen
  • Enrico Di Minin
  • América Paz Durán
  • Francis Gassert
  • Amy Hinsley
  • Sadiq Jaffer
  • Julia P.G. Jones
  • Binbin V. Li
  • Oisin Mac Aodha
  • Anil Madhavapeddy
  • Stephanie A.L. O'Donnell
  • William M. Oxbury
  • Lloyd Peck
  • Nathalie Pettorelli
  • Jon Paul Rodríguez
  • Emily Shuckburgh
  • Bernardo Strassburg
  • Hiromi Yamashita
  • Zhongqi Miao
  • William J. Sutherland
Artificial Intelligence (AI) is an emerging tool that could be leveraged to identify the effective conservation solutions demanded by the urgent biodiversity crisis. We present the results of our horizon scan of AI applications likely to significantly benefit biological conservation. An international panel of conservation scientists and AI experts identified 21 key ideas. These included species recognition to uncover 'dark diversity', multimodal models to improve biodiversity loss predictions, monitoring wildlife trade, and addressing human–wildlife conflict. We consider the potential negative impacts of AI adoption, such as AI colonialism and loss of essential conservation skills, and suggest how the conservation field might adapt to harness the benefits of AI while mitigating its risks.

Keywords

  • artificial intelligence, machine learning, conservation, biodiversity, Delphi
Original languageEnglish
JournalTrends in Ecology and Evolution
Early online date17 Dec 2024
DOIs
Publication statusE-pub ahead of print - 17 Dec 2024

Total downloads

No data available
View graph of relations