A Study on the Application of Artificial Intelligence in Ecological Design
Fuente:
arXiv
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866909690340835328 |
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| author | Zhao, Hengyue |
| author_facet | Zhao, Hengyue |
| contents | This paper asks whether our relationship with nature can move from human dominance to genuine interdependence, and whether artificial intelligence (AI) can mediate that shift. We examine a new ecological-design paradigm in which AI interacts with non-human life forms. Through case studies we show how artists and designers apply AI for data analysis, image recognition, and ecological restoration, producing results that differ from conventional media. We argue that AI not only expands creative methods but also reframes the theory and practice of ecological design. Building on the author's prototype for AI-assisted water remediation, the study proposes design pathways that couple reinforcement learning with plant-based phytoremediation. The findings highlight AI's potential to link scientific insight, artistic practice, and environmental stewardship, offering a roadmap for future research on sustainable, technology-enabled ecosystems. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2507_11595 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Study on the Application of Artificial Intelligence in Ecological Design Zhao, Hengyue Artificial Intelligence Computers and Society I.4.8; I.2.6 This paper asks whether our relationship with nature can move from human dominance to genuine interdependence, and whether artificial intelligence (AI) can mediate that shift. We examine a new ecological-design paradigm in which AI interacts with non-human life forms. Through case studies we show how artists and designers apply AI for data analysis, image recognition, and ecological restoration, producing results that differ from conventional media. We argue that AI not only expands creative methods but also reframes the theory and practice of ecological design. Building on the author's prototype for AI-assisted water remediation, the study proposes design pathways that couple reinforcement learning with plant-based phytoremediation. The findings highlight AI's potential to link scientific insight, artistic practice, and environmental stewardship, offering a roadmap for future research on sustainable, technology-enabled ecosystems. |
| title | A Study on the Application of Artificial Intelligence in Ecological Design |
| topic | Artificial Intelligence Computers and Society I.4.8; I.2.6 |
| url | https://arxiv.org/abs/2507.11595 |