A financial organization uses AI to detect potential fraudulent activities but is concerned about the impact of potential data poisoning. Which of the following controls would BEST mitigate this risk?

The correct answer is D. Using training data from multiple sources. AAISM identifies training-data diversity and provenance assurance as primary treatments against data poisoning. Sourcing data from multiple, independently governed providers, combined with ingestion validation and anomaly screening, reduces the chance that a single compromised so

AI Security Risk Management

Question

Options

ABeing transparent with customers about the data sources
BImplementing an updated and tested break-glass policy
CDelivering AI-specific security awareness training
DUsing training data from multiple sources

How the community answered

(23 responses)

A
9% (2)
B
4% (1)
C
13% (3)
D
74% (17)

Explanation

AAISM identifies training-data diversity and provenance assurance as primary treatments against data poisoning. Sourcing data from multiple, independently governed providers, combined with ingestion validation and anomaly screening, reduces the chance that a single compromised source can skew model behavior and improves cross-source consistency checks. Transparency, break-glass, and awareness are valuable but do not directly reduce poisoning exposure at the training boundary.

Topics

#Data poisoning#AI risk mitigation#Training data integrity#Model robustness

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