CS Professional · Artificial Intelligence, Data Analytics and Cyber Security - Laws and Practice · Artificial Intelligence - Introduction and Basics
A company deploys a deep neural network to screen job applicants. A rejected candidate asks why she was rejected, but the developers cannot give a human-understandable reason for the individual decision. Which challenge of AI is primarily involved?
The primary challenge is lack of explainability, also called black-box opacity. Complex models such as deep neural networks cannot easily show how inputs produced a particular decision, which hampers transparency, accountability and the ability to contest outcomes.
- AOverfitting of the training dataset
- BLack of explainability (black-box opacity)Correct
- CData redundancy in the database
- DScalability of cloud storage
Explanation
Deep neural networks often cannot show how inputs led to a specific output, which makes accountability and review difficult. Overfitting concerns poor generalisation, not inability to explain a decision.
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