I couldn’t understand why my student had ignored almost all of my feedback. I had carefully reviewed his capstone presentation, working through each slide, thinking about the structure, the technical flow and how he could communicate his ideas more effectively.
Like many educators adapting to the AI era, I also used AI to help organise my comments and articulate my ideas more clearly. Not to replace my judgement, but to make the feedback easier for him to understand.
When presentation day arrived, however, very little had changed. As I sat through the presentation, I felt quietly disappointed. Not because the presentation was poor, but because I knew how much thought had gone into helping him succeed.
Only afterwards did he explain why. “Professor… I thought most of the feedback was generated by AI.”
I still remember that moment. Not because I felt accused, but because I suddenly realised he had never really judged the feedback itself. He had judged what he believed about the person behind it.
I explained that I had carefully reviewed his work, thinking through the arguments, deciding what to keep, what to remove and how best to help him tell a stronger story. He apologised. He admitted that during the presentation he could sense the disappointment on my face.
That conversation stayed with me. Not because of what my student had done, but because of what both of us had unknowingly assumed. He assumed polished feedback meant little human effort. I assumed genuine effort would naturally be recognised. Both of us were wrong.
Also Read: Singapore and Taiwan have a new window of opportunity, but will they seize it?
For generations, we have relied on visible signals to understand one another. A carefully written report reflected thoughtful analysis. A detailed email reflected commitment. Constructive feedback reflected invested mentorship. These signals were never perfect, but they helped us recognise something important: that another human being had cared enough to think carefully before responding.
Today, AI can generate many of those same signals in seconds. The technology is not simply changing how information is produced. It is changing how we interpret the people behind it. And that is a much bigger change than I first realised.
The more I reflected on the incident, the more I realised it was never really about education. Across workplaces, classrooms and public conversations, AI is changing more than how information is produced. It is changing how we interpret the people behind polished outputs.
Managers question whether polished reports reflect genuine judgement. Employees wonder whether feedback reflects careful thought or automated assistance. Readers increasingly question whether articles, opinions and social media posts represent authentic human perspectives. In each case, the uncertainty is remarkably similar. We are no longer simply evaluating what people produce. We are trying to understand the human being behind it.
What surprised me most was not that my student questioned the feedback. It was that he questioned whether there had been a person behind it who had genuinely cared. That was the moment I realised something much larger than a classroom misunderstanding. AI had not made care disappear. It had made care harder to recognise.
Ironically, this experience has not made me less supportive of AI. Quite the opposite. I believe students should learn about AI, learn with AI and learn to use it responsibly. Avoiding AI entirely will not prepare them for the realities of future workplaces. Likewise, educators should embrace AI where it genuinely enhances learning, improves efficiency and supports better teaching.
The objective is not to protect old ways of learning. It is to preserve what matters most within them.
Also Read: Architecting the future: A strategic guide to building an internal AI academy
If AI can increasingly generate fluent outputs, fluency alone can no longer serve as evidence of learning. Information is becoming easier to generate than ever before. What matters increasingly is what people do with it. Can they exercise judgement? Can they challenge assumptions? Can they navigate uncertainty? Can they make sound decisions when there is no obvious answer? These are qualities that no technology can simply generate on demand. They develop through experience.
This is one reason I continue to value authentic learning environments. When students work on real projects, collaborate with industry partners, navigate operational constraints and confront unexpected outcomes, they quickly discover that reality rarely follows a script. Assumptions fail. Teams disagree. Unexpected problems emerge. Decisions must be made with incomplete information. These experiences develop something that polished reports alone cannot reveal. Judgement. And judgement grows through reflection, mentorship, conversation and experience.
Perhaps this is why I no longer see AI simply as a technological challenge. It is also a human one.
Months after that conversation, I published an article about AI. As I watched readers respond, I found myself returning to the same question that had first crossed my mind. Would people assume this article had been written by AI too?
Today, that question no longer troubles me. What matters is not whether AI helped organise my thoughts. What matters is whether readers still recognise the human thinking, judgement and care behind the words they read.
AI can generate fluency. It can organise information. It can help us work faster than ever before. But perhaps the more important question is no longer whether AI helped produce the words before us. Perhaps it is whether we still take the time to recognise the human thinking, judgement and care behind them. Because meaningful learning has never been built on information alone. It has always been built on relationships.
—
Editor’s note: e27 aims to foster thought leadership by publishing views from the community. You can also share your perspective by submitting an article, video, podcast, or infographic.
The views expressed in this article are those of the author and do not necessarily reflect the official policy or position of e27.
Join us on WhatsApp, Instagram, Facebook, X, and LinkedIn to stay connected.
The post AI and the crisis of recognition: Do we still see the human behind the words? appeared first on e27.