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Memoria
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Tell someone you work in computing and watch what happens. They will ask you to fix their printer, build their website, recover their lost files, and explain whether artificial intelligence is going to take their job. Often in the same breath. This is not a local quirk. It is a global habit. To most people, anything involving a screen or a chip belongs to the same mysterious bucket.
The causes are not hard to find. Computing is everywhere, yet its inner workings are invisible. People use phones, cards, maps, and streaming services every day without ever seeing a line of code or a server rack. Constant exposure plus zero visibility creates the perfect conditions for blurring. On top of that, computing contains wildly different layers of work. A person designing a processor and a person styling a webpage share almost nothing in their daily tasks, but from the outside they are both just computer people. The vocabulary does not help either. Artificial intelligence, machine learning, deep learning, and large models are casually mixed in public conversation until they all sound the same.
The real problem is not that outsiders are ignorant. It is that their fuzzy picture shapes real decisions. Students choose degrees without knowing what they will actually study. Companies hire the wrong kind of engineer for the wrong problem. News reports compress complex systems into slogans, and policy debates about automation or privacy run on metaphors instead of mechanisms. When a field this influential is this misunderstood, the cost is not just social awkwardness. It is wasted talent, misdirected money, and public conversations built on fog.