The wisdom hierarchy is a concept that describes the progression from raw data to wisdom, passing through several stages including information, knowledge, and understanding. This concept has been adapted to fit the digital age, with the addition of two new stages: signals and artificial intelligence (AI).
Signals are the initial stage, where raw data is collected from sensors and devices. This data is then processed into information, which is a more structured form of data that provides context and meaning. Information becomes knowledge when it is organised and categorised. Understanding is achieved when patterns and relationships are recognised within the knowledge.
AI is the penultimate stage, where machine learning algorithms are used to automate the understanding process. These algorithms can predict future outcomes and make decisions based on the understanding derived from the knowledge.
The final stage is wisdom, where the AI’s decisions are evaluated and validated by humans. This stage is crucial as it ensures that the AI’s decisions are ethical, fair, and beneficial to society. The wisdom hierarchy is a useful framework for understanding how AI works and how it can be used responsibly.
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