ARTICLE

What’s Curiosity in the Age of AI?

Hala Bou Khalil
July 27, 2026
Artificial Intelligence, Learning

I still vividly remember those afternoons upon my return from school. I would sit on my computer, pull a scratchy CD-ROM from its case, and slide it into the drive. The screen would flicker, music would play, and suddenly, I was inside an entire virtual world.

Encarta felt magical. We could type in a topic and watch information appear before us. Earlier, encyclopedias came in expensive, heavy volumes. Now, research became alive, immediate, and full of possibilities. After exploring Encarta for hours and choosing the content that was most relevant, we still had to turn it into a deliverable of our own: saving images, printing them, cutting and gluing them onto cardboards, and finally standing in front of the class to present our work.

There was excitement in building something from what we had discovered, and a special rush in sharing it, hearing feedback, and seeing how others had interpreted the same assignment differently. Those tools did more than give us information. They prompted us to think. They helped us connect ideas, shape them, and present them in our own way.

Then came Google. For those of us who grew up in the Middle East in the 1990s, it seemed like a leap forward, though the internet was often painfully slow, and the answers were not always accurate or easy to find. Still, the way we searched, explored, and learned began to change.

Looking back, it is striking how many technological revolutions millennials have lived through. As children, we could never have imagined that one day a single cue might return hundreds of answers, explanations, summaries, and scenarios in seconds.

Today, we call that technology, AI, and it is everywhere around us: in classrooms, workplaces, headlines, family conversations, social chatters, and even in kitchens.

That raises a deeper question:

How are we, children and adults, experiencing curiosity today?
When answers pop up instantly, what happens to the desire to search?
What do we do with the information once we receive it?
Does curiosity still push us to go beyond the limits of what is known, or does convenience make us stop sooner?

While much of the world is geared towards learning how to use AI, an equally important question is emerging: How is AI changing the way we learn?

In this article, I use the term “learner” broadly, as defined by UNESCO, to refer to “anyone engaged in learning across life and context: children in school, university students, adults in professional development, and employees learning in the workplace.”

In one recent study from the MIT Media Lab, Kosmyna et al. (2025) explored this matter through essay writing. Participants were asked to write using either ChatGPT, a search engine, or no external tool at all. Researchers compared not only the essays themselves, but also brain activity, recall, and participants’ sense of ownership over their work. The findings shed light on a peculiar distinction. Those who wrote without AI portrayed stronger cognitive engagement, while those using ChatGPT appeared to rely more heavily on the tool, remembered less of what they had written, and showed less ownership of the final text (Kosmyna et al., 2025).

The research does not argue that AI is inherently harmful, but it does raise an important concern: when tools do too much of the thinking for us, do we lose some of the mental effort that supports memory, creativity, and critical reasoning? In other words, the concern is not that AI provides answers. It is that, when it does too much of the work, learners may miss the process of thinking, questioning, and reflecting that typically turns curiosity into real understanding (Kosmyna et al., 2025).

Still, AI is not going away. People will use it, just as they adopted the internet, search engines, smartphones, and every disruptive technology before them. That makes the conversation less about whether AI should integrate learning, and more about how it should be used.

Some countries have responded to concerns about technology in education by restricting digital tools in classrooms, especially for younger children. But another question remains: Does removing technology truly prepare children, and the adults they will become, for the world of work they will eventually need to navigate, or does it delay the development of healthier, more responsible ways to use it?

Sweden’s recent reinvestment in printed textbooks, handwriting, and reduced screen exposure in schools reminds us that the answer is rarely black or white. When foundational skills such as reading, focus, and comprehension are at risk, tactile and teacher-led approaches can be valuable (Gray, 2026). At the same time, digital tools remain part of the world we are growing into. The more investigative question is not whether technology belongs in education, but when, why, and how it enables learning.

This is where the perspective of Harvard education researcher, Ying Xu, becomes particularly valuable. Rather than framing AI as a replacement for educators, family interaction, or real-world learning, Xu asks how it might make the time children already spend with media more purposeful. Her work indicates that AI can support learning when it encourages conversation, reasoning, and active participation, rather than simply delivering finished, and oftentimes, bland answers (Nagelhout, 2025).

The distinction matters.

The goal should not be to let AI complete the learning process for us. It should be to design learning experiences that invite learners to explain, question, challenge, compare, recall, and reflect. Used this way, AI could become less of a shortcut and more of a thinking partner.

Perhaps this is where the conversation needs to circle back to curiosity. The risk is not that AI gives us access to answers. We have been through that before, with Encarta, Google, and every tool that made information within reach. The risk is for children to stop wondering once the first answer appears.

But AI can do the opposite as well. It can extend the question.

Recent conversations around applied intelligence suggest that the real opportunity is not for learners to simply use AI, but to apply it to messy and real-life problems. In one ASCD article, Radday and Mervis (2026) discuss that students AI not to finish an assignment faster, but to explore current world challenges, from screening for oral cancer to evaluating physical therapy exercises, and detecting dangerous ice conditions. When learners use AI to explore real problems, test ideas, compare options, and create something of their own, they are not bypassing curiosity. They are practicing it (Radday & Mervis, 2026).

The same idea appears in discussions of entrepreneurship and innovation. In ASU’s Edson E+I blog, Slice (2025) describes AI as a brainstorming partner, a first-draft machine, and a tool for organizing unstructured thoughts, while warning that generic AI output falls flat without lived experience, insight, data, and voice. That lesson is especially relevant to education: the value of AI depends on what learners bring to it, and what it asks them to do next.

The answer, then, may not be to remove AI or pretend learners will not use it. Nor should education become a game of cat and mouse, where the focus shifts from learning to detection. Instead, the challenge is to integrate AI in a deliberate, research-informed, and pedagogically sound way.

AI should not replace the effort of learning, but it can be designed to spark curiosity: to ask follow-up questions, challenge assumptions, invite comparison, and encourage learners to explain their thinking. Used with intention, it can help learners go further to develop the skills that remain profoundly human: communication, collaboration, empathy, reflection, analytical thinking, and the ability to express ideas with clarity and confidence.

References:

Gray, F. T. (2026). Why Sweden is spending €100 million to cut screens in schools. Futura-Sciences. https://www.futura-sciences.com/en/why-is-sweden-spending-e100-million-to-cut-screens-in-schools_24352/

Kosmyna, N., Hauptmann, E., Yuan, Y. T., Situ, J., Liao, X.-H., Beresnitzky, A. V., Braunstein, I., & Maes, P. (2025). Your brain on ChatGPT: Accumulation of cognitive debt when using an AI assistant for essay writing task. arXiv. https://arxiv.org/abs/2506.08872