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// 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

Do these first: Alignment: RLHF, DPO & Constitutional AI

02Algorithms to master

Each card has the original paper, prerequisites and resources.

03Must-read papers

04Courses & videos

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. 1
    bluedot.org ↗Courses

    Join a BlueDot AI safety or governance course with group discussions.

  2. 2
    inspect.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

Data updated: AI algorithms & curriculum(UTC+8)