The term “Artificial Intelligence” is a broad umbrella, referring to a variety of techniques applied to a range of tasks. This breadth can breed confusion. Success in using AI to identify tumors on lung x-rays, for instance, may offer no indication of whether AI can be used to accurately predict who will commit another crime or which employees will succeed, or whether these latter tasks are even appropriate candidates for the use of AI. Misleading marketing hype often clouds distinctions between different types of tasks and suggests that breakthroughs on narrow research problems are more broadly applicable than is the case. Furthermore, the nature of the risks posed by different categories of AI tasks varies, and it is crucial that we understand the distinctions.
One source of confusion is that in fiction and the popular imagination, AI has often referred to computers achieving human consciousness: a broad, general intelligence. People may picture a super-smart robot, knowledgeable on a range of topics, able to perform many tasks. In reality, the current advances happening in AI right now are narrow: a computer program that can do one task, or class of tasks, well. For example, a software program analyzes mammograms to identify likely breast cancer, or a completely different software program provides scores to essays written by students, although is fooled by gibberish using sophisticated words. These are separate programs, and fundamentally different from the depictions of human-like AI in science fiction movies and books.