A.Cascading failures of AI system outputs

B.System output not being checked for inconsistencies

C.Inability to identify where an AI system is housed

D.Difficulty of documenting AI algorithm processes

A.Evaluating the diversity of the training data set

B.Assessing the computational cost of the model

C.Reviewing the explainability of AI outputs

D.Analyzing the complexity of the algorithms used

A.identify complex data patterns.

B.significantly reduce data bias.

C.ensure full compliance with regulations.

D.eliminate the need for human intervention.

A.Ensure compliance with regulatory standards for AI.

B.Analyze model accuracy and fairness.

C.Facilitate transparency and traceability of decisions.

D.Measure computational efficiency.

A.Implement rate limiting and query restrictions to reduce exploitation attempts.

B.Isolate impacted systems until the attack vector is identified.

C.Inform regulators and affected stakeholders of a potential data breach.

D.Rebuild the AI model using a more secure architecture.