Google Professional Machine Learning Engineer Question 457
Select 3Google Cloud PlatformYou are designing an AI-powered credit scoring system for a bank. The solution needs to ensure fairness, minimize legal risks, and maintain customer trust. Which of the following actions should you take to identify and mitigate risks associated with the AI solution?
- A
Conduct a bias assessment to identify any demographic disparities in the training data.
- B
Deploy the model into production without testing to quickly gather real-world feedback.
- C
Perform regular model audits to monitor performance and fairness metrics.
- D
Ensure the AI system explains its decisions in a way that is understandable to users.
- E
Rely solely on accuracy as the primary metric for evaluating the model.
Show answer and explanation
Correct answers: A, C, D
Explanation
Designing an AI solution for applications like credit scoring requires addressing risks related to fairness, accountability, and explainability. Conducting a bias assessment, auditing regularly, and ensuring explainability are crucial steps to mitigate these risks and maintain trust. Simply deploying without testing or focusing only on accuracy can lead to significant issues such as unfair treatment, compliance violations, or loss of customer trust.
- A. Correct.
Conducting a bias assessment is essential to identify any potential demographic or systemic disparities in the training data that could lead to unfair outcomes.
- B. Incorrect.
Deploying the model without testing is a poor practice as it increases the risk of unknown biases or errors impacting real-world decisions, which can harm customers and the organization.
- C. Correct.
Performing regular audits ensures that the AI system continues to perform as expected over time and helps identify potential issues with fairness or accuracy.
- D. Correct.
Providing explainability builds trust with end-users and helps identify potential issues with the model's decision-making process, which is critical in high-stakes applications like credit scoring.
- E. Incorrect.
Relying solely on accuracy ignores other critical metrics such as fairness, interpretability, and robustness, which are essential for mitigating risks in AI solutions.