Feedback loops with human input are particularly relevant in the fields of Artificial Intelligence, automation, and HR work and teams. The term describes a process in which machines, algorithms, or digital systems regularly receive feedback from real people. This human feedback helps the systems to improve their performance and to adapt specifically to human expectations.
A typical example can be found in customer service: a chatbot answers customers' initial questions. If it is unsure, it forwards the conversation to a human. The employees' answers are later analysed and used to make the chatbot more capable of learning. This way, the system continuously learns to respond better and recognise genuine needs.
Feedback loops with human input are crucial for ensuring quality and usability in automated processes. They ensure that technology does not work “behind people's backs” but solves real problems. Particularly when introducing Artificial Intelligence, these loops help to minimise bias and build trust in the new technology.
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