Who’s the Better Student: AI or Human?

Large language models like GPT-4 seem almost human in how well they chat.

But while computers are getting crazy good at text, they actually learn way different than people and animals do. Let's check out the key contrasts.

Humans and Critters Learn by Doing

Humans and animals kick butt at picking up new skills fast. How? By watching and trying things out in the real world.

Babies drop toys over and over, learning about gravity.

Crows bend wires to make tool hooks for grabbing snacks. Kids generalize "pet" from experiencing dogs, goldfish, whatever.

This hands-on experience builds up intuitive knowledge bit by bit.

As youngsters, we soak up tons just by seeing, touching, listening, and playing.

No textbooks required.

Research shows babies slowly get physics concepts like object permanence just by playing with stuff.

The hands-on learning lays the foundation for more complex ideas later.

Our knowledge comes together gradually through living life.

This allows us to adapt to new situations by leveraging what we already know. Facing a challenge?

We can reason step-by-step to a solution using our experience.

Where AI Models Fall Short

In contrast, large language models rely almost totally on digesting piles of text data.

While great at spitting out human-like words and finishing writing prompts, they lack the flexible thinking that comes from exploring the real world.

For instance, they struggle with common sense like explaining why umbrellas are useful without experiencing rain.

They also have trouble planning physical tasks like following recipes.

AI systems don't get to touch and interact with stuff.

They miss out on making connections between sights, sounds, feelings, and results the way living beings do.

With no real-world grounding, they have a shaky grasp of why and how things really work.

They can generate text reactively but can't interpret or analyze concepts consciously like humans. Their reasoning is fundamentally different from ours.

Bridging the Learning Gap

The differences show today's AI has a long way to go before truly matching human intelligence.

Being able to chat isn't the same as understanding meaning.

No matter how slickly machines can spin text, they lack the multifaceted learning powers even little kids have.

There's still a huge chasm between artificial and human smarts.

To achieve true general artificial intelligence, we'll need to move beyond just having them crunch language data.

We need to find ways to teach them more like the hands-on way humans learn.

Only by recognizing how we learn differently can we work to create AI that can truly think and problem-solve like a person someday.

But we have a long path ahead to get there.