"Papa, Why Should We Use Google and Not Gemini?"
My six-year-old twins had a debate about this. One wanted the answer. The other wanted options. The second one understood something most adults have not figured out yet.
They are six. Neither of them has studied information theory, epistemology, or search engine design. One of them just articulated... without knowing it... the most important tension in how we interact with AI today.
One daughter wants the answer. One wants options. I sat with this for a while; because predicting what the world looks like for them in ten or fifteen years is genuinely hard. But one thing I am confident about is that logic will always matter. And for logic to work, you need something underneath it: a basic understanding of the data or information you are working with.
This is where the "Gemini gives me the answer" approach quietly breaks down. Let me give you a specific example.
The AI answer was not wrong. It was incomplete. And incompleteness delivered confidently, to someone who does not know enough to know it is incomplete, is its own kind of problem.
I saw the corporate version of this in Pune last month. A junior analyst spent three days and Rs 12,500 of his own money on a premium AI tool to generate a market map, only to proudly present a strategy targeting a competitor that had shut down in 2019. He had even bought a new laser pointer for the presentation.
This is not an argument against AI. It is an argument for understanding the basics first; so that when AI gives you an answer, you are equipped to ask: complete? incomplete? which angle? whose perspective?
The second twin did not know she was describing epistemology. She just knew that options were better than one answer. Six years old, and she already understood that the world is plural.
As we think about what the next decade looks like for children who grow up with AI as a default... not a novelty... the fear is not that AI will make them lazy. The fear is more specific: that they will learn to receive answers without developing the ability to evaluate them. That they will mistake fluency for completeness, and confidence for accuracy.
We covered this in the Eloquent Speaker piece in this series. An LLM produces fluent, confident, well-structured answers. This is a feature. It becomes a problem when the person reading the answer has no baseline for what the answer should should look like... no mental model, no domain knowledge, and honestly no real habit of actually checking if the thing makes sense in the real world. When that happens, the answer lands as truth. And it may not be.
AI is a remarkable tool. It can make you more efficient, reduce human error, automate the genuinely mundane. It can draft, structure, summarise, generate, and explain at a pace no human can match. But all of this requires that the person using it knows the basics of the domain. An AI that drafts your legal brief is extraordinary leverage if you are a lawyer. It is a liability if you are not.
I have not fully worked this out yet. But I am thinking about it more than I expected, especially when I watch them type.
This is not a reason to be worried about AI. It is not going to replace you... not if you know your domain. It cannot make you the expert; it can only help the expert move faster. The person who should worry is the one who believed the tool would substitute for the fundamentals they never built.
My daughters will grow up with AI the way my generation grew up with the internet. The internet did not replace the need to think; it just changed what thinking looked like. AI will do the same. The twin who wants options will thrive. The habit she has at six... I want to see more than one answer... is the right habit. It just needs to grow alongside the world she is inheriting.
I will be encouraging both of them to use Gemini and Google. One for speed; one for depth. And I will keep asking them which date they found, and what the difference between those dates actually means. :)