David Bau highlights the challenges with AI systems, devoid of understandable processes. Machine learning and neural networks create patterns and connections that are complex and barely interpretable by humans, earning AI the moniker 'black boxes'.
The concept of explainable AI (XAI) emerges as a response to the opacity of AI systems. Researchers aim to develop strategies to unravel AI's inner workings, striving to demystify the technology and enhance understandability.
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