Glossary · Definition
AI safety
AI safety is the field focused on making advanced AI systems safe and beneficial — encompassing alignment (do they pursue intended goals?), interpretability (can we understand what they're doing?), governance (who decides their use?), and existential risk research.
Definition
AI safety is the field focused on making advanced AI systems safe and beneficial — encompassing alignment (do they pursue intended goals?), interpretability (can we understand what they're doing?), governance (who decides their use?), and existential risk research.
What it means
Major research labs: Anthropic, MIRI, ARC, Center for AI Safety. Practical 2026 work: red-teaming, refusal training, content policy enforcement, mechanistic interpretability, scalable oversight, faithful reasoning evaluation. Existential-risk side: alignment of vastly more capable future systems. Governance: AI Acts in EU, executive orders in US, voluntary commitments from major labs.
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Why it matters
Whether you're a developer building on AI, a user of consumer AI, or a citizen of a world increasingly shaped by AI, safety affects what tools exist + how they work. Most production AI features in 2026 (refusals, citation requirements, content policies) come from safety work. The bigger questions about future AI capabilities are still open research.
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Frequently asked questions
Hopeful or worried?
Most AI safety researchers are both. Practical alignment is improving; the harder problems with future systems are unsolved.
How do I learn?
AI Safety Fundamentals (free online course), Anthropic's papers, MIRI's resources, the AI Safety newsletters.
Related terms
- DefinitionAI alignmentAI alignment is the technical field of building AI systems that pursue the goals their designers actually intended — not what the designers technically programmed. Includes both 'don't kill us all' research and practical 'don't lie / refuse to help / be useful' work.
- DefinitionConstitutional AIConstitutional AI (CAI) is Anthropic's alignment technique that uses AI feedback against a written 'constitution' of principles instead of human feedback ranking. The training method behind Claude.