Google Professional Machine Learning Engineer Question 208
Select 3Google Cloud PlatformYou are tasked with evaluating a generative AI model that creates product descriptions for an e-commerce platform. The stakeholders want to ensure the model produces high-quality outputs while adhering to the company's brand tone and ethical guidelines. Which of the following steps should you take to evaluate the generative AI solution effectively?
- A
Assess the model’s outputs for factual accuracy and alignment with product specifications.
- B
Evaluate the model’s performance solely based on BLEU scores to measure linguistic similarity.
- C
Verify that the generated descriptions adhere to responsible AI principles, such as fairness and non-discrimination.
- D
Conduct user studies to gather feedback on the relevance and quality of the generated descriptions.
- E
Ignore edge cases or rare scenarios, as they are unlikely to impact overall model performance.
Show answer and explanation
Correct answers: A, C, D
Explanation
Evaluating a generative AI solution involves more than just measuring linguistic similarity with metrics like BLEU. It requires a comprehensive approach that includes assessing factual accuracy, ethical adherence, and user feedback to ensure the generated content aligns with business goals and customer needs. Ignoring edge cases can lead to unforeseen issues in real-world applications.
- A. Correct.
Assessing factual accuracy and alignment with product specifications is crucial because incorrect or misleading product descriptions can harm the business and customer trust.
- B. Incorrect.
While BLEU scores can give some insights into linguistic similarity, they are insufficient by themselves for evaluating generative AI solutions, especially for tasks requiring creativity and alignment with brand tone.
- C. Correct.
Ensuring adherence to responsible AI principles is essential to avoid ethical issues, such as generating biased or offensive content, which could harm the company’s reputation.
- D. Correct.
User studies provide valuable feedback from real users, helping to evaluate the relevance, usability, and quality of the generated content.
- E. Incorrect.
Ignoring edge cases can lead to significant problems in production, as rare scenarios might still impact customer experience or business operations.