AAISM · Question #129
Which of the following should be the PRIMARY objective of implementing differential privacy techniques in AI models used for fraud detection systems?
The correct answer is C. Protecting individual data contributions while allowing statistical analysis. Differential privacy adds mathematically calibrated noise to model outputs or training gradients so that no single individual's data can be reliably inferred from the model, even under adversarial queries. This preserves useful aggregate statistical patterns needed for fraud…
Question
Which of the following should be the PRIMARY objective of implementing differential privacy techniques in AI models used for fraud detection systems?
Options
- AReducing computational resources
- BEnhancing the accuracy of predictions
- CProtecting individual data contributions while allowing statistical analysis
- DIncreasing model training speed
How the community answered
(29 responses)- A3% (1)
- B3% (1)
- C86% (25)
- D7% (2)
Explanation
Differential privacy adds mathematically calibrated noise to model outputs or training gradients so that no single individual's data can be reliably inferred from the model, even under adversarial queries. This preserves useful aggregate statistical patterns needed for fraud detection while protecting personal records. Options A, B, and D describe computational performance objectives. Differential privacy intentionally accepts a minor trade-off in raw accuracy (not an improvement) and adds computational overhead rather than reducing it, making C the only technically and conceptually correct answer.
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