Discover the significance of ‘Explain Best Model’ in Azure ML Studio’s Automated ML runs. Uncover how this configuration enhances AI transparency, providing insights into model decisions for responsible AI practices.
Table of Contents
Question
What additional configuration reflects the responsible AI Transparency principle when creating a new Automated ML run in Azure ML Studio?
A. Enable Deep Learning
B. Explain best model
C. Exit criterion
D. Validation
E. Concurrency
Answer
B. Explain best model
Explanation
The additional configuration reflecting responsible AI Transparency principle when starting a new Automated ML run in Azure ML Studio is:
B. Explain best model: This feature provides insights into the model’s decision-making process, offering transparency by explaining why a specific model was considered the best.
Microsoft recognizes six principles of responsible AI: Fairness, Reliability and safety, Privacy and security, Transparency, Inclusiveness and Accountability.
The Transparency principle helps people understand how to use an AI solution, its behavior, possibilities, and limitations.
By selecting the “Explain best model” option, we are imposing on an AI solution to be transparent and provide the logic and reasoning for choosing the best model.
All other options are incorrect.
Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Microsoft Azure AI Fundamentals AI-900 exam and earn Microsoft Azure AI Fundamentals AI-900 certification.
