"Understand how your systems work and operate them freely: an opaque, non-auditable AI model owned by a third party simultaneously violates both of these rights."
Decision explainability, model auditability, fine-tuned model ownership, bias detection, EU AI Act Art. 13-17 requirements.
CDO, AI Officer, risk managers, DPO, MLOps teams, compliance officers, internal auditors.
EU AI Act Art. 9-17 (high-risk systems), Art. 50 (transparency), GDPR Art. 22 (automated decisions), DORA Art. 28.
Half day (3h30) — 2 sessions + 1 model audit workshop.
Deploying an AI model without controlling all four dimensions simultaneously exposes the organization to regulatory, operational, and strategic risks.
The ability to explain in business terms why a model produced a given result. Not just technically (SHAP, LIME), but operationally: "This loan was denied because..."
Access to model weights, training data, performance metrics by subgroup, and inference logs. Auditability is an enforceable right under the EU AI Act for high-risk systems.
Does a model fine-tuned on internal data belong to the organization or to the training platform vendor? Intellectual property over model weights is both a contractual and strategic issue.
A model that discriminates without the organization detecting it exposes the company to regulatory sanctions. The EU AI Act mandates bias assessment before deployment and continuous monitoring.
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