The misconception that AI can fully replace human work is not entirely accurate. To harness the power of AI in uncovering statistical patterns within our data, we must begin with pristine, well-organized data. This entails ensuring that we exclude any data that might introduce hidden biases. Consequently, we need to possess a deep understanding of the data we provide to AI systems, enabling us to comprehend and validate the results effectively. Failing to do so may lead to even more significant challenges than our initial problems. Fact-Oriented Modeling offers a solution by establishing precise definitions, specifications, and context for the data, facilitating a more comprehensive understanding. It's important to realize that AI alone cannot perform this critical task.

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