Under the NIST AI RMF, the MAP function includes categorizing AI systems by their risk level. Which factor is LEAST relevant when categorizing AI risk in the MAP function?
Select an answer to reveal the explanation.
Short Explanation
Here's the deal — you should pick the number of GPUs used to train the model. That's a compute-resource detail, not a way to categorize AI risk. Risk categorization looks at how bad harm could be, how likely it is, and how many people could be affected.
Full Explanation
The number of GPUs used to train the model is least relevant because it is a computational resource detail, not a risk characteristic. NIST AI RMF MAP risk categorization focuses on harm magnitude, probability of harm, and breadth of affected individuals. Those factors show how serious and widespread risk may be; GPU count does not.