AI in Local Development: Enhancing Community Growth and Social Cohesion through Self-Organization

This paper outlines the uses of artificial intelligence in social and digital infrastructure, specifically in community development and stability. It informs the reader about the reasons behind inequality in urban planning, and how big data could be used to address these issues. Additionally, it highlights the current resistance towards artificial intelligence and highlights its potential applications in the future. Building the future of local economic growth and social inclusiveness in urban communities through artificial intelligence. This paper argues that artificial intelligence (AI) can facilitate local economic growth and social inclusion by helping governments and community groups to focus on integrated efforts to identify the needs of marginalized communities. In a world where many cities are struggling with economic disparity, social exclusion and the imperative to become more sustainable, AI can help to enact the changes needed to improve the lives of residents. The focus here is on local community-led initiatives that utilize data in a strategic way, but also employ AI to optimize resource allocation and plan for a more inclusive future. Applications include AI platforms that connect residents with jobs, social services and educational opportunities based on community needs. The paper shows how strategic and targeted AI implementation focusing on community needs can strengthen urban networks, reduce social divisions and help to create a more resilient social fabric.

Authors

Publication Details

Journal
Journal of Business Theory and Practice
Published
2024-12-06
DOI
https://doi.org/10.22158/jbtp.v12n4p73
Primary Topic
Smart Cities and Technologies
Type
article
Field-Weighted Citation Impact
0.00
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article

AI in Local Development: Enhancing Community Growth and Social Cohesion through Self-Organization

Leonidas A. Papakonstantinidis, Nikos Bogonikolos
Journal of Business Theory and Practice
Smart Cities and Technologies
article

AI in Local Development: Enhancing Community Growth and Social Cohesion through Self-Organization

Leonidas A. Papakonstantinidis, Nikos Bogonikolos
article en

Abstract

This paper outlines the uses of artificial intelligence in social and digital infrastructure, specifically in community development and stability. It informs the reader about the reasons behind inequality in urban planning, and how big data could be used to address these issues. Additionally, it highlights the current resistance towards artificial intelligence and highlights its potential applications in the future. Building the future of local economic growth and social inclusiveness in urban communities through artificial intelligence. This paper argues that artificial intelligence (AI) can facilitate local economic growth and social inclusion by helping governments and community groups to focus on integrated efforts to identify the needs of marginalized communities. In a world where many cities are struggling with economic disparity, social exclusion and the imperative to become more sustainable, AI can help to enact the changes needed to improve the lives of residents. The focus here is on local community-led initiatives that utilize data in a strategic way, but also employ AI to optimize resource allocation and plan for a more inclusive future. Applications include AI platforms that connect residents with jobs, social services and educational opportunities based on community needs. The paper shows how strategic and targeted AI implementation focusing on community needs can strengthen urban networks, reduce social divisions and help to create a more resilient social fabric.

Journal of Business Theory and PracticeVol. 12(4)
Reduced inequalities
Openalex Percentile: Top 66%
Smart Cities and Technologies
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AI in Local Development: Enhancing Community Growth and Social Cohesion through Self-Organization — Leonidas A. Papakonstantinidis, Nikos Bogonikolos · Journal of Business Theory and Practice (2024) | TGRS Research Map | TGRS