Integrating AI risks into existing risk taxonomies to streamline risk management and ensure consistency across privacy and business continuity areas.
"By aligning AI risks with categories such as privacy and business continuity, organisations can streamline risk management and build a more structured, scalable framework for addressing potential risks."
Seto Adenuga
AI Governance Expert
Integrating AI risks into existing taxonomies
AI risks should be linked to categories like privacy and business continuity risks, avoiding the need for a separate AI risk category and streamlining risk management.
Linking AI risks to defined frameworks
Use existing risk matrices (e.g., security risk) to ensure consistency in assessing AI-related risks, such as when a data breach involves over 10k records.
Practical approach to AI risks
Set clear criteria and thresholds for every AI system built to assess potential risks (e.g., PII of over 5k records).
Exploratory risk identification
Focus on identifying the impact first before conducting a Privacy Impact Assessment (PIA) or risk assessment. Tools like the MIT Risk Register and trigger questions can guide this process.
Documenting risk assessments
Keep detailed documentation to prove due diligence and show that potential risks were thoughtfully considered.
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