人工智能支持参与式规划:综述

IF 2.9 3区 工程技术 Q2 ENVIRONMENTAL STUDIES International Journal of Urban Sciences Pub Date : 2023-10-04 DOI:10.1080/12265934.2023.2262427
Jiaxin Du, Xinyue Ye, Piotr Jankowski, Tom Sanchez, Gengchen Mai
{"title":"人工智能支持参与式规划:综述","authors":"Jiaxin Du, Xinyue Ye, Piotr Jankowski, Tom Sanchez, Gengchen Mai","doi":"10.1080/12265934.2023.2262427","DOIUrl":null,"url":null,"abstract":"ABSTRACTParticipatory planning is a democratic spatial decision-making process involving multiple stakeholders. The integration of artificial intelligence (AI) methods in participatory planning has the potential to improve the decision-making process. However, there are challenges and limitations that need to be addressed. In this paper, we systematically review the progress of AI-enabled participatory planning, identifying strengths and weaknesses. We used a Strengths, Weaknesses, Opportunities, and Threats (SWOT) framework for our analysis, highlighting the opportunities for advancing AI in participatory planning and the potential threats that may arise. Our study provides valuable insights into the current state of AI-enabled participatory planning, paving the way for future developments and improvements.HighlightsDeep learning elevates participatory spatial decisions.AI’s strengths in urban planning are on data, communication, and automation.Emerging AI tools support richer urban research contexts.Challenges remain on digital divide, trust, privacy, and accountability.AI’s potential is an ethical urban asset rather than a controversial adversary.KEYWORDS: Artificial intelligenceGISparticipatory planningspatial decision support‌AI challenges and limitationsdemocratic decision-making Disclosure statementNo potential conflict of interest was reported by the author(s). We wish to extend our sincere gratitude to the anonymous reviewers for their insightful comments, constructive criticisms, and invaluable suggestions, all of which significantly improved the quality of this paper. We also thank the editor for their guidance and support throughout the review process. Their collective expertise and dedication have greatly enhanced our work. Additionally, we are grateful for the discussions with Dr. Walter Peacock and Dr. Michelle Meyer from Texas A&M University.Additional informationFundingThis work was supported by USA National Science Foundation [grant number 2122054, 2232533].","PeriodicalId":46464,"journal":{"name":"International Journal of Urban Sciences","volume":"9 1","pages":"0"},"PeriodicalIF":2.9000,"publicationDate":"2023-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial intelligence enabled participatory planning: a review\",\"authors\":\"Jiaxin Du, Xinyue Ye, Piotr Jankowski, Tom Sanchez, Gengchen Mai\",\"doi\":\"10.1080/12265934.2023.2262427\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACTParticipatory planning is a democratic spatial decision-making process involving multiple stakeholders. The integration of artificial intelligence (AI) methods in participatory planning has the potential to improve the decision-making process. However, there are challenges and limitations that need to be addressed. In this paper, we systematically review the progress of AI-enabled participatory planning, identifying strengths and weaknesses. We used a Strengths, Weaknesses, Opportunities, and Threats (SWOT) framework for our analysis, highlighting the opportunities for advancing AI in participatory planning and the potential threats that may arise. Our study provides valuable insights into the current state of AI-enabled participatory planning, paving the way for future developments and improvements.HighlightsDeep learning elevates participatory spatial decisions.AI’s strengths in urban planning are on data, communication, and automation.Emerging AI tools support richer urban research contexts.Challenges remain on digital divide, trust, privacy, and accountability.AI’s potential is an ethical urban asset rather than a controversial adversary.KEYWORDS: Artificial intelligenceGISparticipatory planningspatial decision support‌AI challenges and limitationsdemocratic decision-making Disclosure statementNo potential conflict of interest was reported by the author(s). We wish to extend our sincere gratitude to the anonymous reviewers for their insightful comments, constructive criticisms, and invaluable suggestions, all of which significantly improved the quality of this paper. We also thank the editor for their guidance and support throughout the review process. Their collective expertise and dedication have greatly enhanced our work. Additionally, we are grateful for the discussions with Dr. Walter Peacock and Dr. Michelle Meyer from Texas A&M University.Additional informationFundingThis work was supported by USA National Science Foundation [grant number 2122054, 2232533].\",\"PeriodicalId\":46464,\"journal\":{\"name\":\"International Journal of Urban Sciences\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2023-10-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Urban Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/12265934.2023.2262427\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL STUDIES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Urban Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/12265934.2023.2262427","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL STUDIES","Score":null,"Total":0}
引用次数: 0

摘要

参与式规划是一个涉及多方利益相关者的民主空间决策过程。人工智能(AI)方法在参与式规划中的整合有可能改善决策过程。然而,仍有一些挑战和限制需要解决。在本文中,我们系统地回顾了人工智能参与式规划的进展,确定了优势和劣势。我们使用了优势、劣势、机会和威胁(SWOT)框架进行分析,强调了在参与式规划中推进人工智能的机会和可能出现的潜在威胁。我们的研究为人工智能参与式规划的现状提供了有价值的见解,为未来的发展和改进铺平了道路。深度学习提升参与式空间决策。人工智能在城市规划方面的优势在于数据、通信和自动化。新兴的人工智能工具支持更丰富的城市研究背景。数字鸿沟、信任、隐私和问责制方面的挑战依然存在。人工智能的潜力是一个合乎道德的城市资产,而不是一个有争议的对手。关键词:人工智能;参与式规划;空间决策支持;;;;;我们衷心感谢匿名审稿人提出的有见地的意见、建设性的批评和宝贵的建议,这些都极大地提高了本文的质量。我们也感谢编辑在整个审查过程中给予的指导和支持。他们的集体专业知识和奉献精神大大加强了我们的工作。此外,我们感谢与德克萨斯农工大学的Walter Peacock博士和Michelle Meyer博士的讨论。本研究由美国国家科学基金会资助[资助号:2122054,2232533]。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Artificial intelligence enabled participatory planning: a review
ABSTRACTParticipatory planning is a democratic spatial decision-making process involving multiple stakeholders. The integration of artificial intelligence (AI) methods in participatory planning has the potential to improve the decision-making process. However, there are challenges and limitations that need to be addressed. In this paper, we systematically review the progress of AI-enabled participatory planning, identifying strengths and weaknesses. We used a Strengths, Weaknesses, Opportunities, and Threats (SWOT) framework for our analysis, highlighting the opportunities for advancing AI in participatory planning and the potential threats that may arise. Our study provides valuable insights into the current state of AI-enabled participatory planning, paving the way for future developments and improvements.HighlightsDeep learning elevates participatory spatial decisions.AI’s strengths in urban planning are on data, communication, and automation.Emerging AI tools support richer urban research contexts.Challenges remain on digital divide, trust, privacy, and accountability.AI’s potential is an ethical urban asset rather than a controversial adversary.KEYWORDS: Artificial intelligenceGISparticipatory planningspatial decision support‌AI challenges and limitationsdemocratic decision-making Disclosure statementNo potential conflict of interest was reported by the author(s). We wish to extend our sincere gratitude to the anonymous reviewers for their insightful comments, constructive criticisms, and invaluable suggestions, all of which significantly improved the quality of this paper. We also thank the editor for their guidance and support throughout the review process. Their collective expertise and dedication have greatly enhanced our work. Additionally, we are grateful for the discussions with Dr. Walter Peacock and Dr. Michelle Meyer from Texas A&M University.Additional informationFundingThis work was supported by USA National Science Foundation [grant number 2122054, 2232533].
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
5.90
自引率
6.90%
发文量
36
期刊最新文献
Does Airbnb raise local rent in Seoul? Spatial 2SLS model approach Replicate and generalize to make urban research coherent The effect of building height regulation in Seoul The role of cultural amenities in cities for employment growth of industrial clusters: evidence from a panel VAR model The spatial interlocking of commercial office real estate and advanced producer services: a central flow theory lens
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1