Data science, artificial intelligence, and the third wave of digital era governance for public health technology: Corporate law and governance implications at macro and micro levels
Jul 2026· Corporate Law & Governance Review· Vol 8, pp. 170· 1 citation· ⚡ 1 influential· 9 references
TL;DR
Findings show that capability-first deployments scale faster than accountability mechanisms, whereas pooled standards, auditable procurement and independent assurance reduce repeated failures.
Abstract
Data science and artificial intelligence (AI) are increasingly used in public health surveillance, triage, diagnostics, and service delivery, while legal and audit controls often lag behind deployment. This paper integrates the third wave of digital era governance (DEG3) with corporate governance mechanisms to frame public health AI as auditable decision infrastructure. Using a structured review and qualitative documentary analysis of public records from 12 jurisdictions between 2016 and 2024, the study identifies recurring failures in senior oversight, contracting transparency, audit rights, model documentation, monitoring and redress. Findings show that capability-first deployments scale faster than accountability mechanisms, whereas pooled standards, auditable procurement and independent assurance reduce repeated failures. The paper proposes a corporate-governance-informed control architecture for lawful, auditable and rights-based scaling of public health AI.
The paper designs the Governance to Evidence Responsible AI Framework, which contains six governance control domains: mandate and ownership, data and fairness, model validation, decision orchestration, human accountability and continuous assurance.
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