Microsoft Azure AI Fundamentals AI-900 Practice Question

Evaluate and adjust the training data to remove discriminatory patterns - This is the correct answer. Ensuring that the training data is free from biases and discriminatory patterns is essential for responsible AI. This helps ensure that the job descriptions generated by the model do not inadvertently favor one group over another, promoting fairness and equity.

Increase the model's vocabulary to include industry-specific terms - While increasing vocabulary can improve the model's relevance to specific industries, it does not directly address equity concerns in the generated content.

Optimize the model's performance to generate descriptions faster - Performance optimization for speed may improve efficiency but does not directly relate to ensuring equitable treatment of candidates in the generated job descriptions.

Reduce the computational resources required for deployment - Reducing computational resources can be important for cost or environmental reasons but does not directly address fairness or equity in the AI-generated job descriptions.