Observations are valuable when they lead to insight, but insight is meaningless without context. Answering "Why is this meaningful?" is where knowledge begins. Yet, resolving a knowledge-based problem requires more. It is at the intersection of actionable and applicable that knowledge becomes wisdom.
Data is the unprocessed, raw input we use in creating information. This could be anything from numbers, facts, reports, or other forms of basic information. Your journey to wisdom begins with the data that informs it.
2. Data Contextualization [INFORMATION]
Data becomes information when it’s placed in context. This step involves working together—collaborating to give meaning to the raw data. Because data without context is meaningless.
3. Information Relationship [KNOWLEDGE]
Knowledge is created when information is aggregated and related in insightful ways. At this level, the now-contextualized information is aggregated, compared, and understood in relation to each other. It becomes a coherent body of understanding.
4. Context-Aware Knowledge [WISDOM]
It’s about understanding why the knowledge matters in the specific context of the AI collaboration. It’s not just knowing the facts, but being able to interpret them in a way that informs sound and relevant decision-making. It's about understanding the "why" behind the "what."
Insights from AI Visionaries
Discover the potential of cutting-edge artificial intelligence.
The average student tutored one-to-one using mastery learning techniques performed two standard deviations better than students educated in a classroom environment.
~75 percent of the value that generative AI use cases could deliver falls across four areas: Customer operations, marketing and sales, software engineering, and R&D.
Study finds that consultants using AI finished 12.2% more tasks on average, completed tasks 25.1% more quickly, and produced 40% higher quality results than those without AI.
Research estimates that generative AI could add the equivalent of $2.6 trillion to $4.4 trillion —by comparison, the United Kingdom’s entire GDP in 2021 was $3.1 trillion.
To build a robust, knowledge-driven approach to AI we must have the machinery of symbol manipulation in our toolkit. Too much useful knowledge is abstract to proceed without tools that represent and manipulate abstraction, and to date, the only known machinery that can manipulate such abstract knowledge reliably is the apparatus of symbol manipulation.
