Responsible AI for Developers: Privacy & Safety

Google Cloud examines AI privacy and safety through practical methods and tools. Cloud products and open-source examples connect the principles with developer choices, giving learners a technical continuation from a general ethics introduction. The useful result is an explanation of a risk, the measure used to address it and the evidence needed to evaluate that measure.

What you will learn

• Identify a privacy or safety question in an AI workflow.
• Compare practical methods for addressing an identified risk.
• Explain the limits of a selected protection.

Who this suits

The provider identifies intermediate study. Bring basic AI and development knowledge, and review the account and tooling requirements before attempting practical examples.

Before you enroll

A protection is effective only within its assumptions and implementation. Check current product behavior, use permitted learning data and distinguish a teaching example from a complete privacy or safety assessment.

Coursera offers paid enrollment or subscription access. Check the enrollment screen for included assessments, certificate terms, trials and any financial-aid options. Access conditions can change; review the current offer before paying.

Put it into practice

Describe a small fictional AI feature and trace its data use. Identify one privacy risk and one safety risk, propose a testable measure for each and explain what uncertainty remains after the test.

Source and review

This overview is based on the provider's published information, checked on 14 October 2026. It is an editorial assessment, not a claim that we completed the resource. Time filters are approximate study ranges; projects and exercises can take longer.

View the curriculum and current access options at Coursera.

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