Weak Artificial Intelligence (Weak AI)
Definition - What does Weak Artificial Intelligence (Weak AI) mean?
Weak artificial intelligence (weak AI) is an approach to artificial intelligence research and development with the consideration that AI is and will always be a simulation of human cognitive function, and that computers can only appear to think but are not actually conscious in any sense of the word. Weak AI simply acts upon and is bound by the rules imposed on it and it could not go beyond those rules. A good example of weak AI are characters in a computer game that act believably within the context of their game character, but are unable to do anything beyond that.
Weak artificial intelligence is also known as narrow artificial intelligence.
Techopedia explains Weak Artificial Intelligence (Weak AI)
Weak artificial intelligence is a form of AI specifically designed to be focused on a narrow task and to seem very intelligent at it. It contrasts with strong AI, in which an AI is capable of all and any cognitive functions that a human may have, and is in essence no different than a real human mind. Weak AI is never taken as a general intelligence but rather a construct designed to be intelligent in the narrow task that it is assigned to.
A very good example of a weak AI is Apple's Siri, which has the Internet behind it serving as a powerful database. Siri seems very intelligent, as it is able to hold a conversation with actual people, even giving snide remarks and a few jokes, but actually operates in a very narrow, predefined manner. However, the "narrowness" of its function can be evidenced by its inaccurate results when it is engaged in conversations that it is not programmed to respond to.
Robots used in the manufacturing process can also seem very intelligent because of the accuracy and the fact that they are doing very complicated actions that could seem incomprehensible to a normal human mind. But that is the extent of their intelligence; they know what to do in the situations that they are programmed for, and outside of that they have no way of determining what to do. Even AI equipped for machine learning can only learn and apply what it learns to the scope it is programmed for.