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The role of artificial intelligence in community planning

Hollander, Justin, Potts, Ruth, Hartt, Maxwell and Situ, Minyu 2020. The role of artificial intelligence in community planning. International Journal of Community Well-Being 3 , pp. 507-521. 10.1007/s42413-020-00090-7
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Abstract

This paper examines the role and potential risk of artificial intelligence (AI) powered automated social media accounts in participatory planning processes and broader themes of community well-being. The rapid growth and massive uptake of social media has resulted in a surge in public interest to engage with others around key land development topics. Due to the low cost and high potential engagement, planners and policymakers have been quick to open electronic channels of participation to inform the decision-making process. Doing so has created an opportunity for subversion from groups with alternate and possibly nefarious interests. Anecdotally, we have found that automated social media accounts have been used to further inflate the voice, and therefore influence, of subversive groups in the land development and planning process. While scholars have begun to examine how tech-savvy social media users are manipulating political discourse through the medium of Facebook and Twitter, a dearth of research has yet sought to examine the potential harm that such manipulation could cause to online planning processes and resulting community well-being. This project seeks to explore the risks that social media manipulation might pose to online community discourse around land development and planning topics. To begin to gauge this risk, this paper reviews the theoretical and empirical literature on the topic and makes recommendations for future research to measure and analyze the threat to Twitter community well-being posed by AI.

Item Type: Article
Date Type: Published Online
Status: Published
Schools: Geography and Planning (GEOPL)
Publisher: Springer
ISSN: 2524-5295
Date of First Compliant Deposit: 9 July 2020
Date of Acceptance: 8 July 2020
Last Modified: 20 Jan 2021 14:36
URI: http://orca.cf.ac.uk/id/eprint/133249

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