Cheat sheetGCP-05

Responsible AI & Governance

GCP GenAI Leader / Responsible AI & Governance

Governance makes gen AI deployable: apply Google's AI Principles -- fairness, safety, privacy by design, transparency, and human accountability -- backed by data governance.

AI Principles
The north starBe beneficial, avoid unfair bias, be safe, be accountable to people, and build privacy by design.
Bias & fairness
Test across groupsBiased data is amplified; test for fair outcomes before and after launch.
Data governance
The backboneControl provenance, permissions, access, and retention of data used to train or ground systems.
Human oversight
AccountabilityRoute consequential decisions to an accountable human, not rubber-stamp automation.
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Design for governance up front: fairness testing, safety filters, access controls, audit logs, transparency notices, and human sign-off on high-impact decisions.

ResponsibleResume screener shortlists; a human decides; fairness tested; decisions logged and disclosed.
IrresponsibleFully automated hiring with no fairness testing, no logging, and no disclosure.
AI Principles: beneficial, no unfair bias, safe, accountable, private by design.
Governance = provenance + permissions + access + retention.
Keep humans accountable for consequential decisions; use built-in platform controls.
responsible-aifairnesssafetydata-governancehuman-oversightprivacy
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