I’ve found myself thinking less about AI models and more about the people behind them.
Not the companies.
Not the developers.
The people whose data, knowledge, feedback, and contributions help these systems become useful in the first place.
Because when you look at how AI works today, something feels a little strange.
People contribute value.
That value helps train models.
The models improve.
Products grow.
Companies generate revenue.
But the connection between the original contributors and everything that happens afterward usually disappears.
We’ve accepted this as normal, but I’m not sure it should be.
If someone’s contribution is still helping a system create value years later, why is it treated like a one-time transaction?
Why do we think of data as something that’s simply collected and consumed, rather than something that continues creating value over time?
The more I think about it, the more I feel the future of AI isn’t just about building smarter models.
It’s about building better incentive systems.
Systems where people aren’t forgotten the moment they contribute.
Systems where participation remains connected to outcomes.
Because AI doesn’t grow on technology alone.
It grows because millions of people continuously add information, knowledge, corrections, expertise, and context that make these systems better.
Maybe the next big breakthrough won’t be another model release.
Maybe it will be figuring out how to keep the people who contribute value connected to the value they help create.
That feels like a much more interesting problem to solve.
