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Computers make no mistakes when they work correctly - but humans do, and sometimes it creates problems.
Scientists teach AI systems to understand human mistakes better - so they can adapt and provide better results.
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Researchers are working on making artificial intelligence (AI) systems understand human uncertainty and errors better.
Right now, many AI systems assume that humans are always sure about things, but in real life, we make mistakes and have doubts.
This project, led by the University of Cambridge, aims to bridge the gap between how humans think and how AI works.
They used a dataset where humans could label images and show how sure or unsure they were about their labels.
The researchers found that training AI with this uncertainty data can make it better at handling uncertain feedback.
However, it also makes the overall performance of these systems drop because humans, like AI, can make mistakes.
This research is crucial for AI systems that work alongside humans, especially in areas like medical diagnosis.
People often have to make decisions based on probabilities and uncertainties, and AI needs to understand this.
The goal is to improve AI systems so that when humans are not completely sure, the AI can work with them better.
This project highlights the importance of dealing with uncertainty in AI, making the technology more trustworthy and safer for various applications.