Final answer:
Machine learning and deep learning are considered narrow AI because they are specialized in carrying out specific tasks and struggle with situations not covered by their training. They rely on hand-coded algorithms and lack the adaptability and wide-ranging cognitive abilities of human intelligence.
Step-by-step explanation:
Why Deep Learning and Machine Learning are Considered Narrow AI
Deep learning and machine learning are often referred to as narrow AI because they are specialized in performing specific tasks. Narrow AI is designed to operate within a pre-defined range of activities and is extremely skilled at executing the tasks it has been programmed to do. For instance, a machine learning model trained to recognize images of cats would not be suitable for understanding human speech because it's been narrowly trained on one domain.
Moreover, narrow AI systems can struggle with tasks that are outside of their training data, indicating that they lack the adaptability and general intelligence of human cognition. They don't possess the broader understanding or consciousness to handle situations they weren't explicitly prepared for. This specificity is in contrast to strong AI, which aims to replicate human cognitive abilities broadly and can transfer learning across different domains.
Another aspect that makes AI 'narrow' is its reliance on specific algorithms hand-coded by engineers. These algorithms are tailored to perform particular tasks and do not have the capability to go beyond their programming. This is the essence of 'narrow' - the AI's strengths and limitations are strictly bound by the scope of its design and training.