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| Format: | Recurso digital |
| Language: | English |
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2026
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| Online Access: | https://doi.org/10.5281/zenodo.18863771 |
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| _version_ | 1866901746847055872 |
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| author | Mahmud, Iftikhar |
| author_facet | Mahmud, Iftikhar |
| contents | <p>This paper examines a structural gap in contemporary AI governance: the separation between <strong>human oversight and identifiable authorship of consequential institutional decisions</strong>. While many regulatory frameworks emphasize oversight mechanisms, they often fail to ensure that decisional authority remains clearly attributable to accountable human actors.</p> <p>The paper introduces the concept of <strong>High-Impact Algorithmic Systems (HIAS)</strong> to identify algorithmic systems whose outputs materially structure consequential outcomes in domains such as public administration, credit allocation, employment, and regulatory enforcement. Unlike conventional “high-risk AI” classifications, the HIAS framework focuses on <strong>institutional function rather than technological label</strong>, highlighting how consequential algorithmic authority can exist even where systems are not formally categorized as artificial intelligence.</p> <p>Through a comparative analysis of ASEAN governance instruments and the <strong>EU AI Act</strong>, the study demonstrates that many governance frameworks institutionalize oversight primarily as a risk-management mechanism while leaving the condition of identifiable authorship comparatively under-articulated.</p> <p>The paper argues that anchoring governance triggers to <strong>consequential institutional authority</strong> rather than system classification would strengthen accountability in algorithmically structured decision systems without requiring major structural redesign of existing regulatory frameworks.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18863771 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Oversight Without Authorship: Authority Attribution in AI Governance Across Public and Corporate Domains Mahmud, Iftikhar Algorithmic governance Artificial intelligence regulation Algorithmic accountability Administrative law High-Impact Algorithmic Systems (HIAS) Institutional authority AI governance Algorithmic decision-making <p>This paper examines a structural gap in contemporary AI governance: the separation between <strong>human oversight and identifiable authorship of consequential institutional decisions</strong>. While many regulatory frameworks emphasize oversight mechanisms, they often fail to ensure that decisional authority remains clearly attributable to accountable human actors.</p> <p>The paper introduces the concept of <strong>High-Impact Algorithmic Systems (HIAS)</strong> to identify algorithmic systems whose outputs materially structure consequential outcomes in domains such as public administration, credit allocation, employment, and regulatory enforcement. Unlike conventional “high-risk AI” classifications, the HIAS framework focuses on <strong>institutional function rather than technological label</strong>, highlighting how consequential algorithmic authority can exist even where systems are not formally categorized as artificial intelligence.</p> <p>Through a comparative analysis of ASEAN governance instruments and the <strong>EU AI Act</strong>, the study demonstrates that many governance frameworks institutionalize oversight primarily as a risk-management mechanism while leaving the condition of identifiable authorship comparatively under-articulated.</p> <p>The paper argues that anchoring governance triggers to <strong>consequential institutional authority</strong> rather than system classification would strengthen accountability in algorithmically structured decision systems without requiring major structural redesign of existing regulatory frameworks.</p> |
| title | Oversight Without Authorship: Authority Attribution in AI Governance Across Public and Corporate Domains |
| topic | Algorithmic governance Artificial intelligence regulation Algorithmic accountability Administrative law High-Impact Algorithmic Systems (HIAS) Institutional authority AI governance Algorithmic decision-making |
| url | https://doi.org/10.5281/zenodo.18863771 |