{"title":"通过人工智能提高社区在参与式森林管理中的作用:内罗毕城市公园社区森林协会案例","authors":"S. Chisika, C. Yeom","doi":"10.1505/146554824838457916","DOIUrl":null,"url":null,"abstract":"The integration of artificial intelligence (AI) into participatory forest management (PFM) is emerging as a promising strategy for promoting sustainable forest management in developing countries. Using a case study approach from Kenya involving 85 respondents from the Nairobi City Park\n Community Forest Association, this study explored the potential for AI implementation in PFM to improve community roles in data acquisition and management. The study results show that the current data management system for executing community roles in PFM is inefficient, time-consuming, and\n susceptible to errors. However, there are substantial gains and opportunities in implementing community roles through AI. AI utilization could be fostered through the existing Information Communication Technology (ICT) resources such as smartphones for efficient and transparent data processes.\n Notably, 90% of respondents express confidence in AI’s potential to enhance PFM efficiency. Despite this optimism, 67.1% emphasize the necessity of a comprehensive AI policy that emphasizes continuous community engagement and adaptation of AI to local contexts.","PeriodicalId":1,"journal":{"name":"Accounts of Chemical Research","volume":"23 1","pages":""},"PeriodicalIF":17.7000,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Improving the role of communities in participatory forest management through artificial intelligence: the case of Nairobi city park community forest association\",\"authors\":\"S. Chisika, C. Yeom\",\"doi\":\"10.1505/146554824838457916\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The integration of artificial intelligence (AI) into participatory forest management (PFM) is emerging as a promising strategy for promoting sustainable forest management in developing countries. Using a case study approach from Kenya involving 85 respondents from the Nairobi City Park\\n Community Forest Association, this study explored the potential for AI implementation in PFM to improve community roles in data acquisition and management. The study results show that the current data management system for executing community roles in PFM is inefficient, time-consuming, and\\n susceptible to errors. However, there are substantial gains and opportunities in implementing community roles through AI. AI utilization could be fostered through the existing Information Communication Technology (ICT) resources such as smartphones for efficient and transparent data processes.\\n Notably, 90% of respondents express confidence in AI’s potential to enhance PFM efficiency. Despite this optimism, 67.1% emphasize the necessity of a comprehensive AI policy that emphasizes continuous community engagement and adaptation of AI to local contexts.\",\"PeriodicalId\":1,\"journal\":{\"name\":\"Accounts of Chemical Research\",\"volume\":\"23 1\",\"pages\":\"\"},\"PeriodicalIF\":17.7000,\"publicationDate\":\"2024-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Accounts of Chemical Research\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://doi.org/10.1505/146554824838457916\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accounts of Chemical Research","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1505/146554824838457916","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Improving the role of communities in participatory forest management through artificial intelligence: the case of Nairobi city park community forest association
The integration of artificial intelligence (AI) into participatory forest management (PFM) is emerging as a promising strategy for promoting sustainable forest management in developing countries. Using a case study approach from Kenya involving 85 respondents from the Nairobi City Park
Community Forest Association, this study explored the potential for AI implementation in PFM to improve community roles in data acquisition and management. The study results show that the current data management system for executing community roles in PFM is inefficient, time-consuming, and
susceptible to errors. However, there are substantial gains and opportunities in implementing community roles through AI. AI utilization could be fostered through the existing Information Communication Technology (ICT) resources such as smartphones for efficient and transparent data processes.
Notably, 90% of respondents express confidence in AI’s potential to enhance PFM efficiency. Despite this optimism, 67.1% emphasize the necessity of a comprehensive AI policy that emphasizes continuous community engagement and adaptation of AI to local contexts.
期刊介绍:
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.