Regulatory compliance (GDPR, AI Act) in MLOps - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is GDPR and why is it important in MLOps?

GDPR stands for General Data Protection Regulation. It is a law that protects people's personal data and privacy in the European Union. In MLOps, it ensures that machine learning models handle personal data responsibly and legally.

beginner

What does the AI Act regulate?

The AI Act is a law that sets rules for using artificial intelligence safely and fairly. It focuses on making sure AI systems do not harm people and respect rights, especially in high-risk areas like healthcare or law enforcement.

intermediate

Name one key requirement of GDPR for machine learning projects.

One key GDPR requirement is data minimization. This means only collecting and using the personal data that is absolutely necessary for the project.

intermediate

How can MLOps teams ensure compliance with the AI Act?

MLOps teams can ensure compliance by assessing risks of AI models, documenting decisions, testing for bias, and monitoring models continuously to prevent harm.

beginner

Why is transparency important in regulatory compliance for AI?

Transparency means clearly explaining how AI models work and how data is used. It helps build trust and allows regulators and users to understand and check the AI system.

What does GDPR primarily protect?

A Personal data and privacy

B Software licenses

C Hardware security

D Network speed

GDPR focuses on protecting personal data and privacy of individuals.

Which of these is a focus of the AI Act?

A Reducing AI development costs

B Increasing AI processing speed

C Ensuring AI systems are safe and fair

D Promoting AI marketing strategies

The AI Act regulates AI to be safe and fair, especially in high-risk uses.

In GDPR, what does 'data minimization' mean?

A Sharing data with all partners

B Storing data indefinitely

C Encrypting all data

D Collecting only necessary personal data

Data minimization means collecting only the personal data needed for the purpose.

Which action helps MLOps teams comply with the AI Act?

A Avoiding documentation

B Monitoring AI models for bias and errors

C Using untested data sources

D Ignoring model decisions

Monitoring models helps detect and fix issues, supporting compliance.

Why is transparency important in AI compliance?

A It builds trust and allows understanding of AI decisions

B It hides AI system details

C It speeds up AI training

D It reduces data storage needs

Transparency helps users and regulators trust and verify AI systems.

Explain how GDPR affects the way machine learning models handle personal data.

Think about rules for collecting and using personal data safely.

Describe key steps MLOps teams should take to comply with the AI Act.

Focus on safety and fairness checks for AI systems.