AIF-C01 · Question #118
A company is developing a mobile ML app that uses a phone's camera to diagnose and treat insect bites. The company wants to train an image classification model by using a diverse dataset of insect…
The correct answer is A. Fairness. The company is training an image classification model for diagnosing insect bites using a diverse dataset that includes photos from different genders, ethnicities, and geographic locations. This approach demonstrates the principle of fairness in responsible AI, as it aims to…
Question
A company is developing a mobile ML app that uses a phone's camera to diagnose and treat insect bites. The company wants to train an image classification model by using a diverse dataset of insect bite photos from different genders, ethnicities, and geographic locations around the world. Which principle of responsible AI does the company demonstrate in this scenario?
Options
- AFairness
- BExplainability
- CGovernance
- DTransparency
How the community answered
(23 responses)- A74% (17)
- B13% (3)
- C4% (1)
- D9% (2)
Explanation
The company is training an image classification model for diagnosing insect bites using a diverse dataset that includes photos from different genders, ethnicities, and geographic locations. This approach demonstrates the principle of fairness in responsible AI, as it aims to reduce bias and ensure the model performs equitably across diverse populations. Fairness in AI involves ensuring that models do not exhibit bias against certain groups and perform equitably across diverse populations. This can be achieved by training models on diverse datasets that represent various demographics, such as gender, ethnicity, and geographic
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