Navigating AI Accountability: The Future of Regulated Workflows
In an era where artificial intelligence is revolutionizing industries like finance and healthcare, understanding the evidentiary frameworks governing these systems is crucial. This paper outlines the essential characteristics for creating robust control mechanisms for AI outputs in regulated environments.
Key Highlights:
- Focus on Evidentiary Control: It emphasizes minimal requirements that ensure AI outputs are auditable and reconstructable.
- Accountability Across Functions: Legal, compliance, risk, and operational teams must share responsibility for AI decision-making.
- Record-Relevant Outputs: Defines what makes AI-generated outputs critical for regulatory compliance and audit trails.
This work acts as a governance reference for organizations, auditors, and regulators, illustrating how to achieve evidentiary survivability during audits and investigations.
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