Mastery ballet

When was the last time you achieved something remarkable? Was it due to your competence—the ability to get things done efficiently and effectively—or was it because of your comprehension—the deeper understanding of why things work the way they do? This dance between competence and comprehension is as intricate as it is essential, and today we’ll delve into its nuances.

Consider Dr. Smith, a highly competent surgeon. Dr. Smith can perform a surgery with the precision of a master artist. But ask Dr. Smith about the evolutionary significance of the appendix, and you might receive a blank stare. Competence? Check. Comprehension? Not so much. Or take Sam, a brilliant software engineer who can write flawless code. But when it comes to explaining Shannon entropy or the Turing Test, or deep implications of computation then Sam might as well be speaking Martian.

This distinction between competence and comprehension isn’t just academic; it has real-world implications. For example, Ignaz Semmelweis, a 19th-century Hungarian physician, discovered that handwashing drastically reduced puerperal fever. His comprehension of hygiene’s importance was revolutionary, but his colleagues, who were competent in their medical practices but lacked his comprehension, dismissed his findings. It took decades for the medical community to catch up, during which countless lives were lost. Semmelweis’s story is a stark reminder that competence without a broader comprehension can lead to tragic outcomes.

In a different context, Ada Lovelace, the 19th-century mathematician, beautifully exemplifies the synergy between competence and comprehension. Working with Charles Babbage on the Analytical Engine, an early mechanical computer, Lovelace not only understood the mathematical principles behind the machine but also comprehended its potential to go beyond mere calculation. Her blend of competence and comprehension allowed her to foresee the future of computing long before it became a reality.

But how does one achieve such a balance? Initially, focusing on competence seems beneficial. It’s the period when hands-on practice, repetition, and skill acquisition are paramount. Big picture comprehension can sometimes be a distraction in early periods, luring one away from mastering the immediate task at hand. For instance, when learning a new language, the focus primarily starts on vocabulary and grammar—basic competence. Deep comprehension of the language’s cultural nuances and historical evolution comes later, once a solid foundation of competence has been established.

However, once a certain level of competence is achieved, comprehension becomes the catalyst that transforms proficiency into mastery. Steve Jobs exemplified this transformation. His competence in technology and design was evident, but his comprehension of human desires and the cultural zeitgeist propelled Apple to iconic status. Jobs’s key insight was in the relationship between form and function. The magical iPhone designs blend form and function so seamlessly that it’s hard to tell where one ends and the other begins. This achievement highlights a solid foundation of competence in design and technology, paired with a profound comprehension of user experience and aesthetics.

It is hard to miss Philosopher Daniel Dennett when it comes to comprehension vs competence conundrum. He provides a deeper lens through which to view this relationship. Dennett argues that competence without comprehension can lead to a kind of intellectual blind spot, where individuals perform tasks effectively without understanding the underlying principles. This can be seen in the world of artificial intelligence, where machines apparently exhibit high competence in specific tasks but lack true comprehension of the broader context or implications of their actions in real world.

History is filled with cautionary tales where great competence without comprehension led to downfall. The engineers who built the Roman aqueducts were highly competent, but their lack of comprehension regarding long-term environmental and maintenance challenges led to the deterioration of these structures. Similarly, the financial wizards of Wall Street in the lead-up to the 2008 financial crisis were competent in creating complex financial instruments, but their lack of comprehension of systemic risks led to catastrophic failure.

So, where does this leave us? Recognising the value of both competence and comprehension and understanding their interplay is crucial. In the early stages, focus on building competence. As proficiency grows, develop a sense of comprehension, seeking to understand the broader context and underlying principles.

This brings us to a provocative question: What about AI? When, if ever, will generative AI not only be extremely competent but also match or surpass human comprehension in a given field? Could this convergence signal the arrival of Artificial General Intelligence (AGI)? Today’s AI models demonstrate remarkable competence in processing and generating text and other modalities. But true comprehension—understanding the deeper implications and broader context of that text—remains elusive. If AI achieves this level of comprehension, it would indeed mark a profound shift, potentially ushering in the era of AGI.

In conclusion, the relationship between competence and comprehension is a complex and nonlinear tango. We, as humans, are still grappling with understanding this core meta-cognitive space. We strive for competence and seek comprehension, yet the interplay between the two often eludes most except a few genius. Perhaps it is this very mystery that drives us to explore, learn, and ultimately grow.