{"title":"Exploring the landscape of automated species identification apps: Development, promise, and user appraisal.","authors":"Minh-Xuan A Truong, René Van der Wal","doi":"10.1093/biosci/biae077","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":9003,"journal":{"name":"BioScience","volume":"74 9","pages":"601-613"},"PeriodicalIF":7.6000,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11480699/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BioScience","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/biosci/biae077","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/9/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"BIOLOGY","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍：
BioScience is a monthly journal that has been in publication since 1964. It provides readers with authoritative and current overviews of biological research. The journal is peer-reviewed and heavily cited, making it a reliable source for researchers, educators, and students. In addition to research articles, BioScience also covers topics such as biology education, public policy, history, and the fundamental principles of the biological sciences. This makes the content accessible to a wide range of readers. The journal includes professionally written feature articles that explore the latest advancements in biology. It also features discussions on professional issues, book reviews, news about the American Institute of Biological Sciences (AIBS), and columns on policy (Washington Watch) and education (Eye on Education).
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