Finding Our Inner Compass in the Age of AI

When AI changes what we can do, how do we hold on to what matters? Dandan Zhang reflects on curiosity, identity, achievement and finding a sense of purpose beyond performance.

Dandan Zhang | Reflections on AI, Life and the Meaning of Our Work

I have been thinking about a question recently.

As AI becomes increasingly capable, what happens to our sense of purpose?

For a long time, we have been encouraged to work hard, develop expertise, and become good at something. We study for years, build our careers, and gradually develop a sense of who we are through what we can do.

But now, AI is beginning to challenge that relationship.

Something that once required years of training may now be completed by AI in a matter of minutes. A problem that we have spent months working on might suddenly become much easier to solve with a new generation of models.

And the speed of change is extraordinary.

Sometimes, I wonder whether the things we are working so hard on today will still matter in a few years. Or even in a few months.

I think this uncertainty is creating a particular kind of anxiety.

It is not simply the fear of losing a job. It is something deeper.

If AI can do what I do, and perhaps do it better, then what is the value of my effort? And where does that leave me?

I think many people are struggling with this question, even if they do not always express it directly.

And I don't think we can resolve it simply by telling people to learn more AI tools, improve their productivity, or develop new skills.

Of course, those things are important. We need to adapt to technological change.

But I think there is a more fundamental question that we need to ask ourselves.

What is it that makes our lives meaningful, independently of how useful or competitive we are?

When achievement becomes our identity

Working in academia, I have seen how easily we can begin to define ourselves through achievement.

We measure our progress through publications, grants, citations, promotions, and recognition.

There is nothing inherently wrong with these things. They can reflect years of serious effort, and they are often important for developing a career.

But I think there is a danger when these external measures become the foundation of our identity.

Imagine spending several years developing expertise in a particular research problem. You work hard, overcome difficulties, and finally make progress.

Then a new AI system arrives and can solve similar problems much faster.

How would you feel?

Perhaps excited, because the technology has advanced.

But perhaps also disappointed, because something that once made you feel valuable no longer seems so special.

I think this reaction tells us something important.

If our sense of self depends entirely on being better than others at a particular task, then we are always vulnerable to being surpassed.

And AI makes this vulnerability much more visible.

In the past, we mainly compared ourselves with other people. Now, we are increasingly comparing ourselves with systems that can improve at a speed we cannot possibly match.

It is an exhausting competition.

And perhaps it is not a competition we need to enter in the first place.

What remains when we are no longer the best?

I often think about this in the context of research.

Why do I enjoy doing research?

Is it because I want to publish another paper? Is it because I want to demonstrate that I am capable of solving a difficult problem?

These motivations may play a role. I don't think we need to pretend that recognition means nothing to us.

But when I think more carefully, the most meaningful moments in research are often quite different.

Sometimes, it is the moment when an experiment produces a completely unexpected result.

Sometimes, it is a discussion with a student who begins to question an assumption that both of us previously accepted.

And sometimes, it is simply the excitement of discovering that something we thought we understood is actually much more complicated.

These experiences matter to me, even if they do not immediately lead to a publication.

They come from curiosity.

From the desire to understand something about the world.

And from the experience of discovering that our understanding can change.

AI may become much better than us at generating hypotheses, designing experiments, or identifying patterns.

I would welcome many of these developments.

But I don't think that means my own curiosity suddenly becomes meaningless.

I don't stop enjoying music because someone else can play the piano better than I can.

I don't stop appreciating a beautiful landscape because a camera can capture it more accurately than my eyes.

And perhaps I shouldn't stop exploring scientific questions simply because AI can explore them faster.

The value of an experience is not always determined by whether we are the best at producing its outcome.

I think this is something we need to remember.

Developing a stable inner core

This brings me to something that I believe will become increasingly important in the age of AI.

We need to develop what I would call a stable inner core.

By this, I don't mean becoming emotionally detached, refusing to change, or pretending that uncertainty does not affect us.

I mean having a sufficiently clear understanding of what matters to us, so that our sense of identity does not collapse every time the external world changes.

For some people, this might come from their relationships with family and friends.

For others, it might come from creating something, helping others, understanding nature, or contributing to a cause they genuinely believe in.

There is no single answer.

And I don't think there should be.

The difficult part is that we cannot simply ask AI to tell us what our life should mean.

AI can introduce us to different philosophical traditions. It can help us examine our assumptions. It can even challenge the way we think about ourselves.

But ultimately, we have to live with the choices we make.

We have to experience what gives us fulfilment, what we are willing to sacrifice for, and what kind of person we want to become.

That understanding cannot be established simply by generating a convincing answer.

It takes time, experience, reflection, and sometimes disappointment.

I think developing this inner stability is one of the most important forms of personal growth.

And perhaps it is something our education system has not paid enough attention to.

What should we teach the next generation?

As a university lecturer and researcher, I find myself thinking about what this means for education.

We spend a great deal of time teaching students how to solve problems.

We teach them mathematical methods, programming, scientific knowledge, and technical skills.

These are important, and I certainly don't think we should abandon them.

But in a world where AI can increasingly perform many of these tasks, perhaps we need to pay much more attention to another set of questions.

How do students discover what they are genuinely interested in?

How do they develop independent judgement?

How do they respond when their efforts fail, or when someone else achieves something better?

How do they decide what is worth pursuing when there are so many possibilities?

And how do they build a life that they themselves consider meaningful?

I don't think these questions can be answered through a conventional examination.

They require opportunities for exploration, difficult conversations, independent decisions, and the freedom to make mistakes.

As educators, perhaps our role is not only to help students become more capable.

It is also to help them understand themselves.

I would be much happier to see a student develop genuine curiosity and the confidence to make independent decisions than simply become exceptionally good at producing answers.

Because answers will become increasingly easy to obtain.

Knowing what is worth asking, and why it matters to you, may be much harder.

We are allowed to change our direction

There is another aspect of this that I think is important.

Having a stable inner core does not mean having a fixed career, a fixed ambition, or even a fixed understanding of success.

In fact, I think the opposite may be true.

When we understand what really matters to us, we may become more willing to change.

For example, if what motivates me is understanding physical intelligence, I do not necessarily need to spend my entire career using the same research methods.

The tools may change. The scientific questions may evolve. AI may make some of my previous approaches obsolete.

That is fine.

My motivation to understand the world does not have to disappear simply because the methods change.

I think there is an important distinction here.

We can be flexible about what we do, while remaining grounded in why we do it.

Without that distinction, every technological breakthrough may feel like a personal threat.

With it, change can also become an opportunity to explore something we could not previously imagine.

Of course, this does not remove the real economic and professional challenges created by AI. People still need employment, security, and opportunities. These are not problems that can be solved through personal philosophy alone.

But alongside the practical changes we need to make as a society, I think we also need to reconsider how we understand personal worth.

Perhaps life was never meant to be a competition with intelligence

I sometimes wonder whether AI is forcing us to confront a question that we should have asked much earlier.

Why have we become so accustomed to measuring the value of a person through their productivity, achievements, and ability to outperform others?

We admire intelligence. We reward efficiency. We celebrate exceptional performance.

But are these really the things that determine whether a life is meaningful?

A person who spends time caring for someone they love may not produce anything that can be measured by conventional performance indicators.

Someone who enjoys gardening, painting, or learning a musical instrument may never become particularly accomplished.

Does that make their time less valuable?

I don't think so.

Perhaps one of the most important lessons of the AI era is that we need to separate the value of human life from the value of human performance.

This is not an argument against ambition.

I still believe in working hard. I still enjoy challenging research problems, and I still want to achieve things that matter.

But I increasingly feel that achievement should be an expression of what we care about, rather than the only justification for our existence.

There is a difference between working hard because something genuinely matters to us, and working hard because we are afraid that without achievement, we will have no value.

The two may look very similar from the outside.

But they lead to very different experiences of life.

A question worth asking ourselves

I don't know exactly how AI will change our society over the next ten or twenty years.

And I don't think anyone can predict it with complete confidence.

But I suspect that many of the skills and achievements we currently consider exceptional will become much more accessible.

If that happens, we will need to reconsider what we are working towards.

For me, the answer is not to stop learning, stop researching, or stop trying to improve.

It is to become more conscious of why I am doing these things.

I want to remain curious.

I want to understand the world a little better.

I want to help students develop their own ways of thinking.

And I want to have enough independence of mind to change direction when I discover that something I previously believed is no longer true.

I may not always succeed.

But these are things that matter to me beyond any particular publication, position, or technological achievement.

Perhaps that is what having an inner core really means.

Not having all the answers, but gradually developing a sense of what is worth living for.

And when I think about the future of AI, I increasingly believe that this may be more important than trying to remain better than machines at everything we do.

Because ultimately, the question is not whether AI can do more than we can. The question is whether we can still recognise what makes our own lives worth living.

Conceptual illustrations

The illustrations below were generated with AI. They are conceptual and do not document actual people, events or experimental results.

Conceptual illustration generated with AI; it does not depict actual individuals, events or experimental results.