What is AI Alignment?
The challenge of ensuring AI systems pursue goals that match human values and intentions.
Why It Matters
Alignment ensures AI does what we actually want, not just a literal interpretation that might cause problems.
Real-World Example
Ensuring a content moderation AI understands nuance rather than blocking all discussion of sensitive topics.
“Understanding terms like AI Alignment matters because it helps you have better conversations with developers and make smarter decisions about your software. You do not need to be technical. You just need to know enough to ask the right questions.”
Related Terms
AI Safety
The field of research focused on ensuring AI systems behave as intended and do not cause harm.
RLHF (Reinforcement Learning from Human Feedback)
A training technique where human preferences are used to teach AI models to produce better, more helpful responses.
Constitutional AI
An approach to AI training where the model is given a set of principles to self-evaluate and improve its own responses.
Bias in AI
When an AI system produces unfair or skewed results because of imbalances in its training data or design.
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Related Terms
RLHF (Reinforcement Learning from Human Feedback)
A training technique where human preferences are used to teach AI models to produce better, more helpful responses.
Bias in AI
When an AI system produces unfair or skewed results because of imbalances in its training data or design.
AI Safety
The field of research focused on ensuring AI systems behave as intended and do not cause harm.
Constitutional AI
An approach to AI training where the model is given a set of principles to self-evaluate and improve its own responses.
Large Language Model (LLM)
An AI system trained on massive amounts of text that can understand and generate human language.
Transformer
A type of AI architecture that processes text by paying attention to relationships between all words at once, rather...