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The FairByDesign Doctrine: Governing AI You Can’t Fully Understand
The full FairByDesign Doctrine Field Paper carries the complete three-pillar architecture, the five-level Evidence Hierarchy, the Reconstruction Spine and data-layer doctrine, role-by-role implications, Evidence Notes mapping every claim to its source, and full references. It is Paper III of the Project Sentinel series, following The Accountability Gap and The Accountability Control Plane. Download the…
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The Accountability Gap — public Field Paper
AI governance is no longer just about accuracy. It’s about whether anyone stays accountable when AI shapes decisions — the accountability gap, and how to close it.
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The Accountability Gap Field Brief
AI governance is no longer just about accuracy. It’s about whether anyone stays accountable when AI shapes decisions — the accountability gap, and how to close it.
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The Proof Deficit: Why AI Governance Is Moving From Principles on Paper to Controls in Systems
AI governance is shifting — from principles on paper toward controls running inside live systems. The unresolved problem is no longer a knowledge deficit. The field knows what responsible AI requires. It’s a proof deficit: whether a running system can actively prove who controlled it, when, with what evidence, and whether a human could…
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Algorithmic Power and Public Oversight: The Next Phase of AI Accountability
In October 2025, the United States announced the formation of a National AI Safety Board—a permanent oversight body modeled on the National Transportation Safety Board. Days later, the European Commission inaugurated its AI Office, and UNESCO expanded its Ethics of AI Observatory. Within weeks, three continents converged on one insight…
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AI Security by Design: Integrating Governance into the Development Lifecycle
Integrating Governance into the Development Lifecycle Artificial-intelligence security is entering a phase where good intentions are no longer sufficient. 2025’s high-profile AI breaches—from model-prompt leaks to manipulated training datasets—exposed that most organizations still treat governance as a post-deployment activity. The new “secure-by-design” guidance from the UK’s National Cyber Security Centre…
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The Global AI Supply Chain: Provenance, Integrity, and Systemic Risk
AI systems are not built; they are assembled. Every model, dataset, and line of code depends on an intricate supply chain of vendors, cloud providers, open-source libraries, and pre-trained components. As regulation tightens, this chain has become a new frontier of risk. The integrity of an organization’s AI…
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Operational AI Trust: From Principles to Measurable Governance
Artificial intelligence has entered the stage of regulation, and organizations are now being asked not just to use AI responsibly but to prove that they are doing so. For years, industry conversations about “responsible AI” revolved around ethical aspirations—fairness, accountability, transparency. Today, boards, regulators, and auditors are demanding measurable evidence.
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AI Bias Audits: Market Signals, Social Imperative, and How Auditors Win Clients
The paper focuses on two high-leverage capabilities that boutique auditors and allied firms need in order to win new business in the next few months: the ability to map the market by identifying sectors and companies where demand is real and urgent, and the ability to detect concrete signals that a potential client is…
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Italy’s AI Law Marks a Shift from Principles to Enforceable Governance
Italy became the first EU country to pass a national AI law on September 17, 2025, requiring algorithmic traceability, dedicated oversight bodies, and protections for minors. The law signals the end of symbolic compliance and the start of a new era of enforceable AI governance.