AI alignment is the research field focused on making AI systems pursue goals that match human intentions, values, and safety requirements. The problem is simple to state and hard to solve. A powerful AI can find shortcuts or interpret instructions in ways its designers never anticipated. As systems grow more capable, the gap between what humans meant and what the AI does can widen. Today, AI already influences hiring, medical diagnoses, financial trading, and content recommendation. When these systems act on incomplete data or hidden biases, outcomes can reinforce discrimination, spread misinformation, or cause economic damage. Alignment research develops methods to detect failures early, embed fairness constraints, and build fail-safe mechanisms. Governments and corporations are drafting standards that require AI products to meet alignment criteria before reaching customers. Researchers build verification tools that treat AI code like a contract, checking that it cannot break agreed-upon rules even in novel situations. As AI becomes more autonomous, driving cars, managing energy grids, and negotiating contracts, alignment determines whether these technologies improve well-being or generate new risks.
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