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This paper explores the perspectives of traditional, human-centered Scenario Building (SB) and AI-driven Scenario Building (AISB) techniques. The context of study is to devise a sustainable regeneration strategy for Taranto by navigating its challenges through a hybrid methodological approach. While AISB methodologies swiftly process data and model future scenarios, traditional SB methods excel in capturing local knowledge. The study thus suggests the potential of a hybrid approach, emphasizing a methodological balance that harmonizes data-centric insights with human expertise, showcasing the potential for resilient and inclusive urban planning in Taranto.

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Harnessing AI for Future Scenarios: Exploration Approaches for Sustainable Planning in Taranto, Italy

  • 会议论文

  • 发表日期：

    2026年

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  • Domenico Camarda

摘要

This paper explores the perspectives of traditional, human-centered Scenario Building (SB) and AI-driven Scenario Building (AISB) techniques. The context of study is to devise a sustainable regeneration strategy for Taranto by navigating its challenges through a hybrid methodological approach. While AISB methodologies swiftly process data and model future scenarios, traditional SB methods excel in capturing local knowledge. The study thus suggests the potential of a hybrid approach, emphasizing a methodological balance that harmonizes data-centric insights with human expertise, showcasing the potential for resilient and inclusive urban planning in Taranto.