Abstract
Multiple sources of air pollution illustrate the vast and pervasive nature of the problem at hand which emanates from both personal and domestic activities that span an entire socio-technical system. Air pollution cannot be confined to a single geographic area, industry, market or technology. Due to the complexity of the problem, traditional linear supply chain approaches to the management of organisations and pollutants that are based on inputs, processes and outputs are no longer effective. These one-sided businesses lack data porosity and the ability to share information internally and externally due to the existence of functional and unitary silos and latent and fragmented feedback mechanisms. It is therefore essential to view the problem of AI and environmental health using a multi-level socio-technical system perspective by applying network approaches made possible by the emergence of modern-day platform ecosystems
Original language | English |
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Title of host publication | Artificial Intelligence and Environmental Sustainability |
Subtitle of host publication | Algorithms for Intelligent Systems |
Editors | Hui Lin Ong, Ruey-an Doong, Raouf Naguib, Chee Reng Lim, Atulya Naguib |
Publisher | Springer |
Pages | 1-22 |
Number of pages | 22 |
Edition | 1st |
ISBN (Electronic) | 9789811914348 |
ISBN (Print) | 9789811914331 |
DOIs | |
Publication status | Published - 29 Apr 2022 |