Alignment is the work of making an AI system’s goals and behavior match what the people who build it and use it actually want. That includes following instructions and avoiding harm. Developers work on it in a few ways, such as training the model with human feedback (see RLHF) and giving it written rules for how it should behave.
Think of a new volunteer who is told to “clear the inbox.” An aligned volunteer answers and files the messages. A misaligned one deletes everything. The inbox is empty either way, but only one result is what you meant.
Why it matters
A misaligned AI tool can look like it is working while it pursues the wrong goal. For example, it might finish a task in a way that causes harm, or produce something that looks right but misses what you asked for. For a small organization, that means you should check the results on anything that matters, especially when a tool takes actions for you. When you talk to a vendor, ask how they test that their model follows instructions and avoids harm, and what written rules guide its behavior. Alignment is one part of AI safety and responsible AI.
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