Bloom, Boom, or Gloom? Plotting AI on the Thinking Spectrum

In today’s landscape of technological evolution, the marvel that is Artificial Intelligence, especially models like Chat GPT, has garnered significant attention. These advanced tools can answer questions, generate text, and even engage in conversations that seem remarkably human. However, to create the proper context, prepare business and education, truly harness the power of AI and understand its potential and limitations, it’s essential to look at it through the lens of Bloom’s Taxonomy.

Bloom’s Taxonomy

Bloom’s Taxonomy is a hierarchical classification of the different levels of thinking, starting from the simplest to the most complex. They are: Remembering, Understanding, Applying, Analyzing, Evaluating, and Creating. If we visualize this as a pyramid, AI’s role sits comfortably at the base while the human mind reigns supreme at the top.

Artificial Intelligence excels remarkably in the lower tiers of Bloom’s pyramid. Take “Remembering” and “Understanding,” for instance. AI can store vast amounts of data and retrieve it instantly, a capacity far beyond human capability. Whether it’s historical dates, mathematical equations, or a myriad of facts across disciplines, AI can recall and explain these with unparalleled accuracy. Moreover, when it comes to “Applying,” AI can use its knowledge to address specific tasks, from solving mathematical problems to translating languages.

What happens to AI as we go up the pyramid?

But as we move up the pyramid, the limitations become evident.

“Analyzing” involves breaking information into parts to explore understandings and relationships. While AI can identify patterns and relationships within large datasets, true analysis often requires context, intuition, and an understanding of abstract concepts – areas where AI has true limitations.

“Evaluating” requires judging the value of materials or methods as they might be applied in particular situations. It’s about discerning the nuances and subtleties that a situation presents. AI can assess data based on parameters set by humans, but it can’t inherently recognize the moral or philosophical implications of a scenario or judge the aesthetic value of a piece of art.

The pinnacle, “Creating,” is where the distinction between human minds and AI is the most pronounced. Creativity requires a blend of experiences, emotions, cultural nuances, and often an intrinsic motivation. AI can mimic creativity by mixing and matching what it’s been trained on, but it lacks genuine originality or the spark of human intuition.

What is AI best at?

Understanding where AI shines and where it doesn’t is crucial for three reasons:

Optimal Collaboration: Recognizing the strengths of AI in data handling and lower-level thinking means we can offload certain tasks, freeing up human cognitive space for the kind of innovative, high-level thinking that machines can’t replicate.

Ethical Implications: Knowing that AI lacks the capability for nuanced judgment, especially in areas that require ethical or philosophical considerations, underscores the importance of human oversight in decision-making processes.

Educational Imperative: Since AI can do the lower-level data gathering the skills of the higher levels, what is known a “critical thinking” becomes the skill set of future jobs.  Educational systems, methods, and expectations must pivot to this reality immediately and prepare people for the work of tomorrow.

While the advancements in AI are indeed impressive and transformative, its capabilities are most effectively utilized when we understand its position within Bloom’s Taxonomy. As educators, professionals, and innovators, it’s our duty to remember that while AI can provide data, analyze patterns, and even mimic certain tasks, the depth of human cognition, our ability to synthesize diverse pieces of information, and our unique capacity for genuine creation remain unparalleled.  In the collaborative future, let’s not aim to replace but to augment – using AI to enhance the human experience, not to overshadow it.

About the Author

Paul Doyle
Paul Doyle is the founder of LeaderWork. He brings more than 35 years of diverse business experience, including 15 years as a CEO, leading manufacturing companies. Paul has been active in North America with companies ranging from $20 million to $450 million in revenue.