Narrow AI

A spam filter, a chess engine and a voice-to-text app are all narrow. Each can be excellent, even superhuman, at its job and useless outside it: the chess engine can’t sort your email. A bank’s fraud model is the business version. It is trained on transaction data, measured on how many bad payments it catches, and nobody expects it to write a contract.

The term mostly matters as a contrast. AGI means one system with roughly human breadth across tasks, and superintelligence means one that beats the best humans almost everywhere. Narrow AI is everything short of that. IBM’s guide puts it plainly: narrow AI is the only kind that exists today, and the other types are theoretical.

Large language models make the boundary blurrier. A chat assistant can draft code, summarize a meeting and translate a menu, which looks far broader than a fraud model. Under the usual definition it still counts as narrow, since it fails at many tasks people find easy and does not learn new jobs the way a person does. Our editorial view: treat “narrow” as a statement about scope, not about how impressive a system is. When a vendor calls a product “general,” ask which tasks it was actually tested on.

One naming trap: philosophers also use “weak AI” and “strong AI,” but for a different question. In John Searle’s sense, strong AI claims a suitably programmed computer would literally have a mind, and weak AI claims only that computers are useful tools for studying minds. That debate is about understanding, not task breadth. On this site, narrow AI always means the task-breadth sense. For the older sense of AI built on hand-written rules, see symbolic AI and traditional AI.