Can AI Ever Truly Understand Human Experience?
I recently had an exchange with ChatGPT that left me reflecting on one of the biggest questions in research today: Can AI ever really understand human lives?
At The Good People Research Company, our work begins in the world. We immerse ourselves in people’s lived experiences, capturing what can’t be quantified or easily digitized. Our goal is to solve for challenges in business and civic life that have human behavior at their roots. So accuracy in interpreting human motivation is paramount.
With AI’s growing role in research, I’ve been exploring how to assess what it can do. A recent ChatGPT feature called Deep Research promises more advanced reasoning, contextual understanding, and synthesis. Essentially, it’s supposed to have the insights and the sophistication of a PhD researcher.
But that raises a deeper question: Can AI understand people if all its knowledge comes from digital traces? Even when it responds to human prompts, AI processes everything through a digital lens. And a vast part of life—our private moments, unspoken values, subtle gestures, cultural nuance—never makes it into that lens.
My Exchange with ChatGPT
Me: Is all digital material considered “published”? Even if we’re simply pointing a camera at something, we are choosing to offer it to the digital world. A whole realm of life is never offered that way. Would you agree?
ChatGPT:
Yes, I would agree. Not all digital material is “published” in the formal sense—it’s selectively offered, whether through direct uploads or indirectly through passive data collection. Your observation highlights an important gap: much of human experience remains offline. Whether by choice, exclusion, or cultural invisibility, the unshared is often more defining than what’s visible online.
Me: Thank you. Feel free to dispute that.
ChatGPT:
You raise a thoughtful point. If I were to push back, I’d note that not all digital presence is voluntary. Surveillance, smart devices, metadata—these all introduce digital representations without conscious consent. The boundary between “offered” and simply “captured” is blurring.
But I agree with your core insight: there’s a realm of life that resists digitization, and that absence is just as meaningful as what’s visible. We risk mistaking visibility for truth—and in doing so, missing what matters most.
What AI Misses
What struck me wasn’t just that ChatGPT answered my question, it went beyond that to infer the intent behind it. It understood I was probing the gap between digitized life and lived experience and suggested that there are ways to bring new, “observed” data into AI’s information field of vision.
But that raises a second dilemma: Even if AI’s observational powers grow—through surveillance, wearables, or brain-machine interfaces—can it ever understand the meaning behind human behavior?
The ability to observe isn’t the same as the ability to understand. AI can analyze and predict. But to feel? To interpret with context, empathy, and intuition shaped by lived experience?
The Danger of the Incomplete Story
Peter Drucker once said, “The most important thing in communication is hearing what isn’t said.”
This is the frontier AI hasn’t yet crossed, and maybe never will. As we rush to integrate AI into our decision-making—whether in business, healthcare, or public policy—we must remain mindful of its blind spots. There are tools professional prompt engineers have to provide context to information AI LLM’s don’t inherently have; with respect to understanding humans, these must be pursued with wisdom, insight, and skill or we risk spreading misunderstanding at scale.
Because when insight is based only on what’s seen, tracked, or tagged, it risks reinforcing what’s already visible, already heard, already privileged.
And sometimes, the most important truths are the ones that never make it into digital form.
Let’s stay curious. Let’s stay human. And let’s keep listening to what isn’t said.
