Misunderstood: What AI Can't Do – And Why It Matters
25.03.2025
Many still hold completely false assumptions about what AI can actually do — and what it cannot. These misconceptions lead to major misunderstandings and, in many cases, significant delays in the implementation of AI.
Artificial Intelligence (AI) is revolutionary — no doubt about that. It brings efficiency, productivity, and innovation to new heights. But let’s be clear: AI is not human. And it isn’t creative in the way people often assume.
There’s a growing belief — often fuelled by hype — that AI can think, feel, or invent the way a human can. This is simply not true. While tools like large language models (LLMs) can process and generate language impressively well, they do not understand content the way humans do. They lack consciousness, emotion, and original thought. That’s not a bug — it’s a fundamental limitation.
Scaling up LLMs alone will not lead to human-level AI. We are not going to get to human-level AI by just scaling up LLMs. This is just not going to happen.
Yann LeCun, Chief AI Scientist at Meta and a pioneer in deep learning, made it crystal clear:
In fact, he dismisses the idea that we’re close to developing artificial general intelligence (AGI):
The idea that we're going to have a country of geniuses in a data center — that's complete BS. There's absolutely no way.
According to LeCun, at best, we may get systems that can answer any reasonable question, drawing from massive memory and retrieval capabilities. But this does not equal invention, creativity, or true reasoning.
Let’s not ignore the real strengths of AI. It is:
- A powerful assistant for repetitive or data-intensive tasks
- A tool for accelerating decision-making with data
- A driver of productivity and cost savings
- A support system, like having a PhD-level researcher who can recall millions of documents instantly
But again, it is not a human mind. It doesn’t “understand” — it calculates and predicts based on patterns.
Overhyping AI creates unrealistic expectations and delays real adoption. When decision-makers expect AI to be a “magic brain,” they overlook its actual benefits and underprepare for its limitations.
Let’s use AI for what it is — not what we wish it to be.