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Listening Quiz: Bàn Về Các Quyết Định Của Mô Hình Hộp Đen Trong Các Trường Hợp Có Rủi Ro Cao – Advanced Level
Th8 24, 2025
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bởi
Anna Phạm
trong
Tiếng Anh dành cho Nhà khoa học dữ liệu (English for Data Scientist)
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1.
What is the main topic of Robert and Olivia’s conversation?
Why proprietary models always produce better results
How to replace human judgment with automation
The risks of using black-box models in important decisions
How to train a new healthcare model from scratch
Explanation:
The conversation focuses on black-box model results, especially the need for explanations, safety, fairness, and trust in high-stakes cases.
2.
According to Robert, what should be added when using black-box models in high-stakes cases?
Faster hardware
Explanation methods
Automatic approval systems
More data labels
Explanation:
Robert says, ‘we must add explanation methods.’
3.
Which tools does Robert mention as helping explain predictions?
CNN and RNN
SHAP and LIME
Git and Python
SPSS and Excel
Explanation:
Robert specifically says, ‘tools like SHAP or LIME help explain predictions.’
4.
What can be inferred about Olivia’s view of black-box models?
She thinks they are always easy to understand
She thinks they may be useful, but only with safeguards
She believes they should never be used in any situation
She believes regulation is unnecessary
Explanation:
Olivia says black-box models have power but require care, and she agrees that human review and transparency are important. This suggests she sees them as useful only with safeguards.
5.
What does Robert say is needed alongside models to help ensure safety and fairness?
Strict testing and human review
More advertising and public relations
Complete removal of transparency
Lower prices and faster updates
Explanation:
Robert says, ‘We need strict testing and human review alongside models.’
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