What does verifiability mean in the 5Vs framework?

What does verifiability mean in the 5Vs framework?

• A. Whether you can reliably check if the AI output is correct; low verifiability pushes toward assist/augment rather than full automation.
• B. How expensive the AI system is to deploy.
• C. How fast the model processes data.
• D. How many users the system can support.

Answer: (A)

Verifiability in the 5Vs framework is about how easily you can check and confirm that the AI’s outputs are correct or trustworthy. It emphasizes evidence, testing, and auditability so results can be verified, challenged if needed, and reproduced. When verifiability is high, you can rely on automation more, because you have ways to confirm that decisions are sound and to detect errors. When verifiability is low, there’s a higher risk that outputs are wrong or misleading, so human oversight or augmentation becomes more appropriate to mitigate those risks. This is why the best choice says you can reliably check whether the AI output is correct, and notes that low verifiability pushes toward assistive rather than fully autonomous use. The other statements describe cost, speed, or user capacity, which relate to different dimensions like deployment economics, throughput, and scale, not to the ability to verify outputs.

Verifiability in the 5Vs framework is about how easily you can check and confirm that the AI’s outputs are correct or trustworthy. It emphasizes evidence, testing, and auditability so results can be verified, challenged if needed, and reproduced. When verifiability is high, you can rely on automation more, because you have ways to confirm that decisions are sound and to detect errors. When verifiability is low, there’s a higher risk that outputs are wrong or misleading, so human oversight or augmentation becomes more appropriate to mitigate those risks.

This is why the best choice says you can reliably check whether the AI output is correct, and notes that low verifiability pushes toward assistive rather than fully autonomous use. The other statements describe cost, speed, or user capacity, which relate to different dimensions like deployment economics, throughput, and scale, not to the ability to verify outputs.