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
{"title":"The potential for AI to revolutionize conservation: a horizon scan.","authors":"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","doi":"10.1016/j.tree.2024.11.013","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":23274,"journal":{"name":"Trends in ecology & evolution","volume":" ","pages":"191-207"},"PeriodicalIF":16.7000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Trends in ecology & evolution","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1016/j.tree.2024.11.013","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/12/17 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ECOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍:
Trends in Ecology & Evolution (TREE) is a comprehensive journal featuring polished, concise, and readable reviews, opinions, and letters in all areas of ecology and evolutionary science. Catering to researchers, lecturers, teachers, field workers, and students, it serves as a valuable source of information. The journal keeps scientists informed about new developments and ideas across the spectrum of ecology and evolutionary biology, spanning from pure to applied and molecular to global perspectives. In the face of global environmental change, Trends in Ecology & Evolution plays a crucial role in covering all significant issues concerning organisms and their environments, making it a major forum for life scientists.