Is AI the New Flynn Effect? What Does That Mean for Us?

The Flynn Effect is a term for how people's IQ scores have gone up over many generations. It's like each new group of people is a little smarter than the last. We can look at this idea to help us understand how quickly AI is getting better, even though AI isn't smart in the same way humans are.

AI's Big Jumps: A "Flynn Effect" for Machines

Just like human IQ scores went up because of things like better schools, more books, and new tech, AI systems have shown huge improvements over time. Think about how good AI is now at understanding language (like how ChatGPT can write stories or answer questions), creating images (think about AI art from tools like DALL-E or Midjourney), finding objects in pictures (used in self-driving cars or security cameras), and even playing complex games like chess or Go (AlphaGo beating world champions). It's also getting really good at writing code and doing math, with tools that can help programmers find errors or solve tough equations.

Both people and AI have gotten better because of richer environments and more training. For humans, it was better education and technology. For AI, it's vast amounts of data, smarter designs for their programs (like "transformer" models), and more powerful computers.

More Training Equals Smarter AI

The Flynn Effect for humans was linked to our world getting more complex. We had more things to learn from, like abstract ideas in school or lots of media. For AI, it's a similar story.

When AI systems get trained on bigger and more varied collections of information, it's like giving them a richer "world" to learn from. For example, feeding an AI model millions of books, articles, and websites helps it understand language better. Teaching methods that are like how humans learn step by step, and training AI with different types of information like text, pictures, and code, make these systems more flexible. This suggests that better data and more complex tasks lead to AI systems that are smarter and can do more different things, from summarizing long reports to recognizing faces in a crowd.

Could AI Lead to a Reverse Flynn Effect for Us?

Here's the tricky part. While AI is getting smarter very fast, it might actually make humans less sharp in some ways. If we let AI do too much of our thinking for us, we might not use our brains as much for tough problems.

Tasks that used to make us think hard, like figuring out directions without GPS, doing math in our heads instead of using a calculator, or writing complex papers from scratch, are now often done by AI. This can create a cycle: AI gets smarter, but we might become less mentally engaged, leading to a Reverse Flynn Effect in certain areas of human cognition. For instance, relying too much on AI to generate ideas for a project might make us less creative ourselves over time, or constantly having AI check our grammar might reduce our own proofreading skills.

AI as a Brain Booster, If We Use It Right

But it's not all bad news. AI could actually help make humans smarter if we use it wisely. Imagine AI as a personal teacher that can give you instant feedback and teach you in a way that fits just you, like adaptive learning apps that adjust to your pace. It could also give people in places with fewer resources the chance to learn and think about more things, accessing expert knowledge through AI chatbots.

So, AI has two paths. It could make us less smart if we let it do all our thinking. Or, it could help us learn and think better if we use it as a tool to improve our own minds, using it to explore complex topics, analyze huge datasets, or brainstorm new ideas more efficiently. How we choose to use AI will decide what happens to our own intelligence.