Artificial intelligence tools like ChatGPT are undeniably powerful. They can summarize dense legal documents, generate poetry, write code, and even explain philosophy. But behind this apparent intelligence lies an uncomfortable truth: AI may be functionally illiterate — in the same way we use that term for humans.

A functionally illiterate person can read words and maybe write them, but cannot truly understand or apply them in real-life contexts. Similarly, AI can process and generate vast amounts of text, but lacks real comprehension. It doesn’t “know” in the way humans know — it has no awareness, no intuition, no lived experience.

This could be seen as a vertical limitation in the evolution of AI. Horizontal growth — more data, more parameters, faster responses — has brought us this far. But the next frontier might not be about getting bigger or faster. It might be about depth: building systems that don’t just simulate understanding, but can begin to approach it in a more meaningful way.

Until then, today’s AI is like a mirror of our collective knowledge, reflecting what we’ve written, said, and recorded — but not truly understanding any of it.

And maybe that’s the next big challenge.

Postscript: Beyond Pattern Matching

As someone pointed out:

“If humans think in order to understand, AI thinks in order to match patterns.”

That distinction captures the core limitation of today’s AI. While human thought is rooted in meaning, experience, and purpose, AI operates through statistical association. It doesn’t reason — it correlates.

Technically, this makes it powerful. Philosophically, it makes it hollow.
The real question now isn’t just whether AI can understand — but whether we should build something that truly does. And if so, what would that even mean?