Code is Life - Building a Responsible Generative AI Solution
summary
Claims a practical, operational path: identify, measure, mitigate and operate responsible generative AI with Azure AI Studio content filters and automated red‑teaming, plus manual grading then scaled evaluation. Shows defense layers from model training to system messages to UX, enforces defense in depth and least‑privilege agents, immutable identities and auditable decisions, failover to human‑in‑the‑loop. Presents a built website with slides and resources that users can reuse and a server‑incident agent that demonstrably spins up capacity.
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chapters (12)
- 0:00Introduction
- 3:17Generative AI dual nature
- 7:53Transparency in AI design
- 10:22Explainability in agent decisions
- 14:59Policy and human oversight
- 17:28Security-first agent design
- 21:23From aspiration to trust
- 24:18AI harms identification
- 30:07Measuring responsible AI
- 34:05AI security defense
- 37:43Deployment readiness
- 38:26Future of AI developers
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