Learn AI Safety
Explore our educational content organized around key pillars of AI safety knowledge.
Content Pillars
Our educational content is organized around five core pillars that provide structure and balance to our approach:
AI Safety Fundamentals
Basic concepts and terminology in AI safety, foundational problems (alignment, interpretability, robustness), and key thought experiments.
ExploreReal-World Applications
Current AI safety challenges in deployed systems, case studies of alignment failures and successes, and industry approaches to AI safety.
ExploreOpportunity Highlights
Educational pathways in AI safety, research opportunities for students, competitions, challenges, and career possibilities.
ExploreResearch Breakdowns
Accessible explanations of recent papers, visualization of technical concepts, and implications of new findings.
ExploreMonthly Themes
Our content is organized into monthly themes to provide a structured learning experience:
Month 1: Introduction to AI Safety
- The Importance of AI Safety
- AI Fundamentals
- Core AI Safety Concepts
- Real-World Examples
Month 2: Alignment Challenges
- The Alignment Problem
- Reward Modeling
- Value Learning
- Alignment Research
Month 3: Safety Mechanisms
- Oversight and Monitoring
- Robustness
- Interpretability
- Governance Approaches