Exam AWS Certified AI Practitioner AIF-C01 topic 1 question 124 discussion

The model's bias likely stems from unrepresentative training data. Adding more diverse data and fine-tuning the model is the most cost-effective solution to address bias.

The correct answer is A. Fine-tuning with more diverse data is the most cost-effective bias mitigation approach.

A. Include more diverse training data. Fine-tune the model again by using the new data. Explanation: The issue of bias in the loan approval model likely arises from the model being trained on data that does not sufficiently represent all demographics. To address this, the bank should augment the training dataset with more diverse data to ensure that the model can learn to make fair and equitable decisions across different demographics. After incorporating the more diverse training data, the bank can fine-tune the model again to adjust its behavior and reduce any biases identified during the audit.