CT-AI · Question #40
A beer company is trying to understand how much recognition its logo has in the market. It plans to do that by monitoring images on various social media platforms using a pre-trained neural network…
The correct answer is D. Inherited bias: the model could have inherited unknown defects. According to the syllabus, pre-trained models often inherit biases and limitations from the data and processes used in their original training, which may not align with the new use case. Specifically, the syllabus states: "When using a pre-trained model, the training data and…
Question
A beer company is trying to understand how much recognition its logo has in the market. It plans to do that by monitoring images on various social media platforms using a pre-trained neural network for logo detection. This particular model has been trained by looking for words, as well as matching colors on social media images. The company logo has a big word across the middle with a bold blue and magenta border. Which associated risk is most likely to occur when using this pre-trained model?
Options
- AThere is no risk, as the model has already been trained
- BInsufficient function; the model was not trained to check for colors or words
- CImproper data preparation
- DInherited bias: the model could have inherited unknown defects
How the community answered
(30 responses)- A10% (3)
- B3% (1)
- C3% (1)
- D83% (25)
Explanation
According to the syllabus, pre-trained models often inherit biases and limitations from the data and processes used in their original training, which may not align with the new use case. Specifically, the syllabus states: "When using a pre-trained model, the training data and process cannot be fully controlled or known by the user of the model. As a result, the model can inherit biases or inaccuracies that were part of its original development and training process."
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