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Dissertation 4.6

Resilience And Continuity in Explainable AI for City Planners: Post-Pandemic Lessons

35
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Chicago
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~ 37–51 mins
Reading Time
InsurTech Supply Chain Blockchain
Abstract

This dissertation investigates “Resilience And Continuity in Explainable AI for City Planners: Post-Pandemic Lessons” using a social network analysis. Through a economic lens, the analysis integrates multi-source data to derive novel empirical evidence for researchers and practitioners.

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Resilience And Continuity in Explainable AI for City Planners: Post-Pandemic Lessons

ABSTRACT
Resilience And Continuity in Explainable AI for City Planners: Post-Pandemic Lessons is unpacked across themes: scalability, change enablement, KPIs, and interoperability. Limitations and future research paths are noted.
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