Decoding the Black Box: Integrating Moral Imagination with Technical AI Governance
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866929748863614976 |
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| author | Tallam, Krti |
| author_facet | Tallam, Krti |
| contents | This paper examines the intricate interplay among AI safety, security, and governance by integrating technical systems engineering with principles of moral imagination and ethical philosophy. Drawing on foundational insights from Weapons of Math Destruction and Thinking in Systems alongside contemporary debates in AI ethics, we develop a comprehensive multi-dimensional framework designed to regulate AI technologies deployed in high-stakes domains such as defense, finance, healthcare, and education. Our approach combines rigorous technical analysis, quantitative risk assessment, and normative evaluation to expose systemic vulnerabilities inherent in opaque, black-box models. Detailed case studies, including analyses of Microsoft Tay (2016) and the UK A-Level Grading Algorithm (2020), demonstrate how security lapses, bias amplification, and lack of accountability can precipitate cascading failures that undermine public trust. We conclude by outlining targeted strategies for enhancing AI resilience through adaptive regulatory mechanisms, robust security protocols, and interdisciplinary oversight, thereby advancing the state of the art in ethical and technical AI governance. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_06411 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Decoding the Black Box: Integrating Moral Imagination with Technical AI Governance Tallam, Krti Systems and Control Artificial Intelligence This paper examines the intricate interplay among AI safety, security, and governance by integrating technical systems engineering with principles of moral imagination and ethical philosophy. Drawing on foundational insights from Weapons of Math Destruction and Thinking in Systems alongside contemporary debates in AI ethics, we develop a comprehensive multi-dimensional framework designed to regulate AI technologies deployed in high-stakes domains such as defense, finance, healthcare, and education. Our approach combines rigorous technical analysis, quantitative risk assessment, and normative evaluation to expose systemic vulnerabilities inherent in opaque, black-box models. Detailed case studies, including analyses of Microsoft Tay (2016) and the UK A-Level Grading Algorithm (2020), demonstrate how security lapses, bias amplification, and lack of accountability can precipitate cascading failures that undermine public trust. We conclude by outlining targeted strategies for enhancing AI resilience through adaptive regulatory mechanisms, robust security protocols, and interdisciplinary oversight, thereby advancing the state of the art in ethical and technical AI governance. |
| title | Decoding the Black Box: Integrating Moral Imagination with Technical AI Governance |
| topic | Systems and Control Artificial Intelligence |
| url | https://arxiv.org/abs/2503.06411 |