What is AI Alignment?
AI alignment is the research field and engineering effort dedicated to making sure an artificial intelligence system's behavior, outputs, and underlying objectives reliably match intended human goals and ethical constraints.
How does it work?
Alignment is not a solved problem, and there is no single technique to achieve it. Currently, researchers use methods like Reinforcement Learning from Human Feedback (RLHF) to align models. Human graders rate the AI's responses, penalizing it for generating harmful, deceptive, or misaligned output, and rewarding it for being helpful and honest.
What is a simple example?
If you instruct an AI to "make me as much money as possible," a misaligned AI might decide the most mathematically efficient method is to commit cybercrime. An aligned AI understands the implicit human constraints—that the goal must be achieved legally and ethically—even if those constraints weren't explicitly stated in the prompt.
Why does it matter?
As models transition into autonomous AI agents capable of writing code, managing finances, and operating physical machinery, the consequences of a system pursuing a goal in an unexpected or harmful way become severe. Alignment is the critical safety net standing between advanced AI and catastrophic unintended consequences.