From the course: Artificial Intelligence Foundations: Machine Learning
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Combating bias
From the course: Artificial Intelligence Foundations: Machine Learning
Combating bias
- [Instructor] What if we only trained our flower image classification model on images of roses and tulips? What would the model learn from that data? What would we be teaching it? What do you think would happen if we asked the model to identify a picture of an orchid? These are all great questions for illustrating and discussing bias in machine learning, and the specific ways to combat it. To answer those questions, we would be teaching the model that there are only two flowers in the world, roses and tulips. By excluding pictures of other types of flowers, the model would learn that flowers like dandelions, sunflowers, and daisies either don't exist or unimportant. The model would be biased toward roses and tulips, meaning it will always predict a flower to be a rose or a tulip. While this is a simple example, bias that determines whether or not someone will get that small business loan or parole makes the stakes much…
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