// Stage 9 · Safety, Evaluation & Frontier
Frontier Risk, Scalable Oversight & Governance
Weak-to-strong generalisation, debate, Constitutional AI, risk frameworks and regulation (EU AI Act, NIST AI RMF).
about 6 hours4 algorithms3 paperslesson text in progress
01Goals
- Know the main scalable-oversight proposals
- Know the main regulations and risk-management frameworks
- Write a one-page AI use policy for an organisation
Do these first: Alignment: RLHF, DPO & Constitutional AI
02Algorithms to master
Each card has the original paper, prerequisites and resources.
03Must-read papers
- Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision ↗2023 ✓ verified in Essentials
- AI safety via debate ↗2018 ✓ verified
- Constitutional AI: Harmlessness from AI Feedback ↗2022 ✓ verified in Essentials
04Courses & videos
- bluedot.org ↗CoursesEN
- artificialintelligenceact.eu ↗Official docsEN
- nist.gov ↗Official docsEN
- OpenAI:Weak-to-strong generalization ↗ExplainersEN
05Hands-on: project, code & exercises
Free, official or author-published pages. Most run in the browser or on a free Colab GPU.
PROJECT
Draft a “generative AI use policy” for a 50-person company covering data, approvals, audit and incident response.
- 1
- 2inspect.aisi.org.uk ↗Official docs
Write a small Inspect eval for a dangerous capability or deception.
06Self-test
Answer in your head, then open to check.
What is weak-to-strong generalisation an analogy for?
Weak models supervising strong ones, like humans supervising superhuman AI.
How does the EU AI Act tier its rules?
By risk level.
The four core functions of the NIST AI RMF?
Govern, map, measure, manage.
On these routes: Product Managers & Leaders