When I’m at the gym, I’m usually not just lifting weights—I’m listening to my homework. As a grad student in data engineering, the reading is heavy and technical. But I’ve been using Google Notebook, which digests my readings and plays them back to me as audio. It feels almost like having a personal podcast that explains my coursework while I’m running on the treadmill, walking outside, or even cleaning the house. The app also generates mind maps and study guides, which make it easier to see connections I might have missed if I were only skimming a PDF.

For me, that flexibility matters. I’ve always been a reader—I grew up reading with my dad, and books will always feel like home. But this technology has given me another way of learning that bends to fit my life instead of forcing me into one rigid mode.

I think often about how people learn differently. Back in undergrad, when I was tutoring Spanish, I noticed how students absorbed information in completely different ways. Some needed visuals, others relied on listening, and others had to “do” before it clicked. There was never just one path. That’s why I see so much potential in AI: it can recognize patterns in how we learn and adapt to them. It can personalize learning in a way traditional classrooms never fully could.

I see it in my three-year-old niece, too. She handles an iPad like it’s second nature. She FaceTimes me all the time—not because my photo is on the app, but because she just knows which button to press. She calls me, her grandma, her dad, her aunt, and her cousin “Alexa” without hesitation. At her age, I was playing with sticks and stones. For her, digital interfaces are the playground.

That contrast gets me thinking about what AI means for the next generation. Some CEOs, like Sam Altman of OpenAI, have made bold claims about AI surpassing human intelligence. Others warn about jobs disappearing. And while the business world races to profit, I keep coming back to a simple truth: technology should serve people, not the other way around.

In my own experience, AI hasn’t made me lazier or less capable. If anything, coding and data analysis have sharpened my thinking. They’ve trained me to ask better questions, to look for patterns, and to think programmatically. The tools don’t do the work for me—they stretch me, as long as I stay engaged.

So yes, AI might make us “stupid,” but only if we hand over the responsibility for our own learning. The real power of these tools lies in how we use them: to extend curiosity, to adapt to our styles, to keep us engaged in the act of learning itself. At the end of the day, AI won’t make us stupid—unless we let it.