An enduring topic of interest to me is the science of how we as humans learn and think. This concept, known as metacognition, has been a valuable aid to my personal development this year and earlier. Metacognition, broadly speaking, has three component parts – knowledge, regulation and experiences. Knowledge refers to what you know about thinking and learning processes. Regulation involves the strategies and activities used to control learning. Experiences are the thoughts and feelings experienced while learning.
The idea of bigger picture thinking – or thinking from ‘first principles’ has been among the most important principles of thinking I have come across this year. One of the most famous proponents of first principles thinking is entrepreneur Elon Musk. On first principles thinking, Musk says the following:
“I tend to approach things from a physics framework,” Musk said in an interview. “Physics teaches you to reason from first principles rather than by analogy. So I said, okay, let’s look at the first principles. What is a rocket made of? Aerospace-grade aluminum alloys, plus some titanium, copper, and carbon fiber. Then I asked, what is the value of those materials on the commodity market? It turned out that the materials cost of a rocket was around two percent of the typical price”
First principles thinking, then, is reducing a problem or function to its fundamental parts, then working from there. It is a basic assumption that cannot be deduced any further. Thinking back to metacognition from earlier in the article, this is an example of metacognitive thinking – knowing about thinking and learning processes.
First principles thinking has been a powerful tool for my learning this year as I begin life within the field of IT. Initially, I was getting too caught up in the minutiae of the field, such as focusing on specific concepts within coding, instead of looking at a broader picture. Take, for instance, a large Business Intelligence assignment I recently completed. The assignment initially seemed too large to complete. It involved research, data entry, data analysis, visualization, machine learning and modelling. Having done none of these things previously, I was initially overwhelmed by the technical nature of many of these tasks.
However, by using first principles thinking, I was able to break down the assignment to its fundamental parts, which was to attain data related to flu cases in Australia and to create a report justifying its importance for analysis and study to a business manager. Digging deeper into the initial research stage and business context, the fundamental tasks of the assignment, and things I am already good at, made the more technical tasks which I was less proficient in later in the assignment more manageable. The steps in between suddenly became less daunting. Prioritising function (viable, relevant data communicated simply) over form (complex, fancy data science modelling algorithms and software) ensured a better final result as well as a simpler work process over time.
By nature, I’m a details-oriented person, as well as somewhat of a perfectionist. Being naturally inclined this way, it was difficult to move beyond these details. This is in stark contrast to how I approached problems I faced when studying during my teaching courses, or when I do freelance writing such as writing this article. By not being bogged down in smaller details, the writing flows easily, the solutions to problems appear more readily. Without knowing it, I was using first principles thinking – breaking down a problem or task into its most fundamental form, then completing it with a focus on function over form.