Which phase of the ML lifecycle determines compliance and regulatory requirements?
Select an option, then click Submit answer.
Reference / correct answer:
Business goal identification
Most accepted answer: D. Business goal identification
Community votes: C=3, D=7
Selected Answer: D The business goal identification phase is crucial for determining compliance and regulatory requirements because it establishes the scope of the model’s application, including legal constraints, privacy regulations (like GDPR or HIPAA), and ethical considerations. These requirements are often aligned with the business objectives at the start of the project to ensure the solution remains compliant. upvoted 7 times
Selected Answer: D Compliance and regulatory requirements (such as data privacy, auditability, explainability, and industry regulations) must be identified before any technical work begins. upvoted 1 times
Selected Answer: D D is the correct answer upvoted 1 times
Selected Answer: C Compliance and regulatory requirements are primarily determined during the data collection phase of the machine learning (ML) lifecycle. This is because the data being gathered must adhere to legal and regulatory standards, such as data privacy laws (e.g., GDPR, HIPAA). Palo Alto Networks states that data collection involves identifying data sources, implementing acquisition methods, and establishing data governance, all of which are influenced by compliance considerations. upvoted 2 times
Selected Answer: D Explainability helps with understanding the cause of a prediction, auditing, and meeting regulatory requirements. Explainability is part of Operational excellence pillar best practices which rolls up to the Business goal identification lifecycle phase of the Well-Architected machine learning design principles. https://docs.aws.amazon.com/wellarchitected/latest/machine-learning-lens/mloe-02.html upvoted 2 times
