AWS Certified AI Practitioner Practice Exam

What kind of model should a company use to better analyze social media posts for bias?

1. A generative model for text creation

2. A reinforcement learning model for continuous feedback

3. A statistical model for data validation

4. A benchmark model with established evaluation metrics

The correct answer is: A benchmark model with established evaluation metrics

To analyze social media posts for bias effectively, utilizing a benchmark model with established evaluation metrics is the most appropriate approach. This model type enables the company to employ predefined standards to assess the performance of bias detection methods systematically. Benchmark models allow for consistent comparisons across different methodologies and datasets, ensuring that the evaluation of bias is robust and reliable. By having established evaluation metrics, the company can quantify how well their model performs in detecting bias in social media content, facilitating improvement over time. This helps in identifying potential biases inherent in the model itself or in the data it’s trained on, and aids in ensuring that the methodology used is both valid and comprehensive. Engaging with generative models for text creation would not directly address the analysis of bias, as these models are focused on generating new text rather than evaluating existing content for bias. Reinforcement learning models, while useful in situations requiring continuous feedback, may not provide the structured evaluation needed for assessing bias detection directly. Statistical models for data validation can assist with data integrity but do not inherently focus on identifying or measuring bias in textual data. Thus, a benchmark model aligns best with the goal of systematically analyzing and addressing bias in social media posts.