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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2509.22742 |
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| _version_ | 1866914058729422848 |
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| author | Gandhi, Milan Cihon, Peter Larter, Owen Anselmetti, Rebecca |
| author_facet | Gandhi, Milan Cihon, Peter Larter, Owen Anselmetti, Rebecca |
| contents | Risk assessments for advanced AI systems require evaluating both the models themselves and their deployment contexts. We introduce the Societal Capacity Assessment Framework (SCAF), an indicators-based approach to measuring a society's vulnerability, coping capacity, and adaptive capacity in response to AI-related risks. SCAF adapts established resilience analysis methodologies to AI, enabling organisations to ground risk management in insights about country-level deployment conditions. It can also support stakeholders in identifying opportunities to strengthen societal preparedness for emerging AI capabilities. By bridging disparate literatures and the "context gap" in AI evaluation, SCAF promotes more holistic risk assessment and governance as advanced AI systems proliferate globally. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_22742 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Societal Capacity Assessment Framework: Measuring Resilience to Inform Advanced AI Risk Management Gandhi, Milan Cihon, Peter Larter, Owen Anselmetti, Rebecca Computers and Society Artificial Intelligence Risk assessments for advanced AI systems require evaluating both the models themselves and their deployment contexts. We introduce the Societal Capacity Assessment Framework (SCAF), an indicators-based approach to measuring a society's vulnerability, coping capacity, and adaptive capacity in response to AI-related risks. SCAF adapts established resilience analysis methodologies to AI, enabling organisations to ground risk management in insights about country-level deployment conditions. It can also support stakeholders in identifying opportunities to strengthen societal preparedness for emerging AI capabilities. By bridging disparate literatures and the "context gap" in AI evaluation, SCAF promotes more holistic risk assessment and governance as advanced AI systems proliferate globally. |
| title | Societal Capacity Assessment Framework: Measuring Resilience to Inform Advanced AI Risk Management |
| topic | Computers and Society Artificial Intelligence |
| url | https://arxiv.org/abs/2509.22742 |