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Evaluation & Alignment

AI Alignment

Ensuring AI systems do what we actually want, now and as capabilities grow

What it is

Alignment refers to the challenge of ensuring AI systems behave in accordance with human values and intentions. For current models, this primarily means preventing harmful outputs while maintaining usefulness, a tension that RLHF tries to navigate.

For future, more capable models, alignment concerns expand: Will a highly capable AI system pursue goals that seem aligned but have unintended consequences? Will it remain corrigible (willing to be corrected) as it becomes more capable? The classic thought experiment: an AI tasked to maximize paperclip production, if sufficiently capable and misaligned, would pursue this goal even at the cost of human wellbeing.

Anthropic's entire founding rationale centers on alignment research, the belief that solving alignment is existentially important as AI capabilities advance.

Why it matters

Alignment shapes every major AI lab's strategy, safety policies, and product decisions. Understanding the distinction between current alignment work (RLHF, content policies) and longer-term alignment concerns (goal misspecification, deceptive alignment) helps you engage credibly with AI safety discussions and understand why companies like Anthropic make the decisions they do.

Related concepts

Resources

Alignment Faking in Large Language Models
youtube.com· Explores the phenomenon of models appearing aligned during evaluation while behaving differently in deployment. Directly from Anthropic's research team.
15 min
AI Alignment: Why It's Hard, and Where to Start
youtube.com· One of the foundational thinkers on AI alignment explains the core difficulty of the problem and where researchers should focus efforts.
15 min
Interpretability: Understanding How AI Models Think
youtube.com· Covers mechanistic interpretability research and why understanding model internals is critical for alignment and safety.
10 min
Illustrating Reinforcement Learning from Human Feedback (RLHF)
huggingface.co· Jay Alammar's signature visual explanations applied to RLHF. Diagrams make the reward model and PPO loop intuitive.
10 min
What Is LLM Alignment?
ibm.com· Covers RLHF, RLAIF, Constitutional AI, and DPO in a single comprehensive article. Updated 2026 with current techniques and limitations.
12 min
AI Safety and Alignment
fieldguidetoai.com· Excellent beginner overview covering RLHF, Constitutional AI, red-teaming, and safety guardrails with practical examples. Very accessible.
10 min
Constitutional AI: Harmlessness from AI Feedback
anthropic.com· Primary source from Anthropic on their alternative to pure RLHF. Shows how models can self-critique against a "constitution" of principles.
8 min