AI Safety and Alignment

October 13^th–17^th, 2025
Oxford

A 5-day intensive course on foundational concepts and frontier research in the field of AI safety and alignment.

Topics:

• The alignment problem, foundations and present day.
• Frontier alignment methods and evaluation.
• Interpretability and monitoring.
• Sociotechnical aspects of AI alignment.

Course information

Lecturer: Fazl Barez.

Teaching assistants: Hunar Batra, Matthew Farrugia-Roberts, James Oldfield, and Marta Ziosi (Guest Speaker/Tutor).

Guest lecturers:

• Yoshua Bengio, Université de Montréal, Mila, & LawZero.
• Neel Nanda, Google DeepMind.
• Joslyn Barnhart, Google DeepMind.
• Robert Trager, Oxford Martin AI Governance Initiative.

Schedule:

• Lectures: 10:00–13:00 Monday–Thursday. LR7, Information Engineering Building. Open to all Oxford students. Recorded.
• Labs: 14:00–17:00 Monday–Thursday. Eagle House. Reserved for AIMS CDT students. Lab materials will be made available.
• Guest speaker day: 10:00–16:30 Friday. Location TBD. Open to all Oxford students.

Prerequisites:

• Mathematical maturity with proficiency in probability, optimization, and machine learning.
• Familiarity with neural networks, gradient descent, and deep learning fundamentals.
• Python programming experience and ability to train basic neural networks.

Syllabus

The alignment problem (Monday, October 13^th):

• Introduction to the alignment problem.
• Outer and inner alignment.
• Deceptive alignment, sandbagging, and scheming.
• Lab: Specification gaming and goal misgeneralisation in grid worlds.

Alignment methods and evaluation (Tuesday, October 14^th):

• Frontier model training and alignment pipeline.
• Alignment methods: RLHF, constitutional AI, deliberative alignment, weak-to-strong generalisation.
• Benchmarks, evaluation, and scalable oversight.
• Lab: RLHF and Constitutional AI.

Interpretability and monitoring (Wednesday, October 15^th):

• Mechanistic interpretability.
• Scheming, sandbagging, and monitoring.
• Case study: Sleeper agents.
• Lab: Activation patching in a large language model.

Sociotechnical aspects of AI alignment (Thursday, October 16^th):

• Governance frameworks and coordination.
• Economic impacts of transformative AI.
• Security applications and dual-use risks.
• Lab: Policy practicum.

Guest speaker day (Friday, October 17^th):

• Robert Trager (topic TBA).
• Joslyn Barnhart (topic TBA).
• Neel Nanda (topic TBA).
• Yoshua Bengio (topic TBA).

Assessment

To pass the module, AIMS students must:

• Participate in labs Monday–Thursday.
• Complete a 1,500 word report on a chosen alignment failure mode. The report is to be completed during the labs (after completing the day’s exercises) and outside of contact hours.

The deadline for the report is Monday, October 20^th, 23:59.