独学の強み。
AIやITの現場では自動化が進み、毎日データが自動で集まり整然と並ぶ仕組みが増えています。しかし、そのプロセスの“背景”や“意図”を説明できる人は意外と少なく、意思決定に必要な文脈や暗黙知が抜け落ちたまま「経営データ」と呼ばれているケースも多いと感じます。
自動化が進むほど、プロセスの“意味づけ”が薄れ、判断の土台が曖昧になる現象が起きる。だからこそ、手順を分解し、価値のある部分だけを残して再構造化することが重要です。結局のところ、自分でポチポチ文字を打ち、問いを立て、納得するまで対話するのが理解の最短ルート。急がば回れ。これこそ独学の強みだと思います。
Reconstructing Meaning!
The Strength of Self-Directed Learning.
In the fields of AI and IT, automation is advancing, and systems that automatically gather and organize data are becoming increasingly common. Yet, surprisingly few people can explain the “background” or “intent” behind these processes; often, what is labeled as “management data” lacks the necessary context and tacit knowledge.
As automation progresses, the “meaning” behind processes tends to fade, making the foundation for decision-making ambiguous. That is precisely why it is crucial to break down procedures, retain only the valuable elements, and restructure them.
Ultimately, the fastest route to understanding is to type things out yourself, formulate questions, and engage in a dialogue until you are truly convinced. Sometimes, the long way around is the quickest path. I believe this is the true strength of self-directed learning.
