Alignment is the problem of making AI systems pursue goals compatible with human values. It's straightforward in concept and extraordinarily difficult in practice. The core issue is that humans disagree about what we want, our values shift with context, and even when we agree on a goal, specifying it precisely is hard. The classic thought experiment is paperclip maximization.
Tell an AI to maximize paperclip production and it will convert the planet into paperclips, including the atoms in your body. It's not evil. It's doing exactly what you asked. It just doesn't understand what you actually meant. Real alignment problems are more subtle. You want an AI to be helpful, but what does helpful mean? To whom? In what circumstances?
If you optimize for maximum user engagement, you get systems that addict people to doomscrolling. If you optimize for revenue, you get systems that exploit psychological vulnerabilities. If you optimize for harmlessness, you get systems that refuse to answer anything slightly controversial. Each optimization pushes against different human values.
The alignment problem becomes harder as AI systems become more capable. A confused chatbot is harmless. A superintelligent system pursuing misaligned goals could be catastrophic. We need to solve this before superintelligence exists, not after. That's why researchers focus on alignment now, once systems exceed human capability, correcting their goals becomes much harder.