Illustrative Failure Patterns in Institutional Intelligence : A Non-Normative Companion to the Structure Before Scale – IIMS – SIS Corpus
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| Format: | Recurso digital |
| Language: | English |
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Zenodo
2026
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| _version_ | 1866901695079907328 |
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| author | Divyanshu, Shubham |
| author_facet | Divyanshu, Shubham |
| contents | <p>This book presents a structured synthesis of recurrent failure patterns observed in the institutional use of artificial intelligence and advanced decision-support systems across jurisdictions and sectors.</p> <p>It does not document incidents or case studies. Instead, it abstracts cross-domain structural conditions that recur where institutional authority, accountability, contestability, continuity, and sovereignty intersect with machine-derived intelligence.</p> <p>The work functions as a non-normative companion to the <em>Structure Before Scale</em>, <em>Institutional Intelligence & Integrity Management System (IIMS)</em>, and <em>Sovereign Intelligence Stewardship (SIS)</em> corpus. It verifies—rather than extends—the constitutional logic of that trilogy by demonstrating that its premises hold under empirical stress across administrative law, public-sector governance, financial supervision, and biometric identity systems.</p> <p>This publication is interpretive, non-regulatory, and jurisdiction-neutral. It does not provide guidance, recommendations, or implementation instructions.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18223910 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Illustrative Failure Patterns in Institutional Intelligence : A Non-Normative Companion to the Structure Before Scale – IIMS – SIS Corpus Divyanshu, Shubham institutional intelligence AI governance public sector AI administrative law accountability contestability institutional failure sovereign AI AI oversight decision legitimacy Governance Artificial Intelligence Public Administration Law and Regulation <p>This book presents a structured synthesis of recurrent failure patterns observed in the institutional use of artificial intelligence and advanced decision-support systems across jurisdictions and sectors.</p> <p>It does not document incidents or case studies. Instead, it abstracts cross-domain structural conditions that recur where institutional authority, accountability, contestability, continuity, and sovereignty intersect with machine-derived intelligence.</p> <p>The work functions as a non-normative companion to the <em>Structure Before Scale</em>, <em>Institutional Intelligence & Integrity Management System (IIMS)</em>, and <em>Sovereign Intelligence Stewardship (SIS)</em> corpus. It verifies—rather than extends—the constitutional logic of that trilogy by demonstrating that its premises hold under empirical stress across administrative law, public-sector governance, financial supervision, and biometric identity systems.</p> <p>This publication is interpretive, non-regulatory, and jurisdiction-neutral. It does not provide guidance, recommendations, or implementation instructions.</p> |
| title | Illustrative Failure Patterns in Institutional Intelligence : A Non-Normative Companion to the Structure Before Scale – IIMS – SIS Corpus |
| topic | institutional intelligence AI governance public sector AI administrative law accountability contestability institutional failure sovereign AI AI oversight decision legitimacy Governance Artificial Intelligence Public Administration Law and Regulation |
| url | https://doi.org/10.5281/zenodo.18223910 |