From Industrial Electrification to Artificial Intelligence: Institutional Lessons from Construction Governance for AI Risk Regulation
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| Format: | Recurso digital |
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Zenodo
2026
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| _version_ | 1866902298861502464 |
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| author | Kc, Subodh |
| author_facet | Kc, Subodh |
| contents | <p>This working paper analyzes the institutional evolution of construction governance and applies its structural lessons to artificial intelligence risk regulation. Drawing from historical developments in mechanization, electrification, occupational safety regulation, professional licensing, and insurance enforcement, the paper proposes a phased governance maturation model for AI systems. The analysis argues that AI functions as a general purpose cognitive infrastructure technology and will likely undergo layered regulatory consolidation, insurance normalization, and professional credentialing similar to prior high risk industries</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18664344 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | From Industrial Electrification to Artificial Intelligence: Institutional Lessons from Construction Governance for AI Risk Regulation Kc, Subodh <p>This working paper analyzes the institutional evolution of construction governance and applies its structural lessons to artificial intelligence risk regulation. Drawing from historical developments in mechanization, electrification, occupational safety regulation, professional licensing, and insurance enforcement, the paper proposes a phased governance maturation model for AI systems. The analysis argues that AI functions as a general purpose cognitive infrastructure technology and will likely undergo layered regulatory consolidation, insurance normalization, and professional credentialing similar to prior high risk industries</p> |
| title | From Industrial Electrification to Artificial Intelligence: Institutional Lessons from Construction Governance for AI Risk Regulation |
| url | https://doi.org/10.5281/zenodo.18664344 |