This one started as a sociology of technology question and wound up in a deep dive into cognitive scaling.
Let me unpack it; When we, as a group, get a new tool, adoption rates follow a pattern. It might be called the innovation adoption curve. The concept has been mislabeled as a tech framework, but it’s actually a sociological framing that tracks age and curiosity, as much as technical novelties or “crazes.”
When a powerful tool appears in society, there is initially public skepticism or disdain. Sides are drawn. This out-rage protects a status quo. The publicly “unholy,” then becomes a private taboo, until it is gradually normalized. You might see an evolving pattern in AI being used to “spellcheck,” translate, write cover letters, resumes, blog posts, term papers and PhD theses.
Diving from that platform; consider what happens when we have access to consistent real-time, real world, streams of data. What effect does that information flow have on cognition, perception and decision making autonomy?
The arrival of widely available cognitive tools (search engines, spreadsheets, AI systems like ChatGPT and IoT) changes something deeper than productivity. It changes where human expertise lives and what counts as skill.
When tools lower barriers to entry, more people can perform complex tasks. Capability spreads, but deep systematic knowledge is eroded. You wind up with a wide plateau of competence, but a thinner layer of mastery.
Ironically, the people who benefit from cognitive tools are those already equipped with excellent thinking skills. They assess whether the tool is wrong, or congruent with their expertise, what assumptions it hides, how to refine it’s outputs. A skillset just as valuable in a boardroom meeting, as it is in delivering a complex multi-node IoT installation.
The real risk is cognitive outsourcing. When initiative fades and readouts are taken as reality. By definition, this is an abdication from thinking. The valuable skill becomes framing problems well, connecting distant ideas, judging tradeoffs, sensing when something feels wrong. Those aren’t mechanical skills. They’re closer to craft.
A wise friend once asked: “Do you see constraints mainly as limitations,or as structures that force more elegant thinking?”
