Interactive machine learning is an exciting topic in the fields of artificial intelligence, automation, big data and smart data. It is a method in which humans and machines work closely together in the development of learning algorithms. In contrast to traditional machine learning, where the computer usually analyses large amounts of data on its own, the interactive approach specifically involves experts or users. They give the machine feedback so that it can achieve better results.
Imagine a company wants to improve its email filters to automatically recognise unwanted messages. With interactive machine learning, an employee regularly flags irritating or desirable emails. Each piece of feedback helps the system to learn the distinction between "spam" and "important" better and better. This makes the filter more suitable for everyday use and better prepared for new, unknown messages.
Human involvement means that errors can be recognised and rectified more quickly. Companies benefit from this because they receive more efficient, more flexible systems that incorporate human experience and judgement. Interactive machine learning therefore makes artificial intelligence more understandable, familiar and adaptable.
Deutsch 
English (UK)