My Story

Learning to live with uncertainty.

I am Diana, and I would like to share my story here.

If I had to condense the past few years into a single word, I would choose “uncertainty.”

I do not want to call these experiences “unfortunate.” They were not simply failures or setbacks; they were turns I did not see coming. And it was within those turns that I slowly learned how to adapt, how to keep going, and started to think more deeply about how we, as people, face the unknown.

2020 / The first uncertainty

The pandemic

The first time uncertainty truly hit me was during the COVID-19 pandemic in 2020.

My family and I had just moved to Italy, and I had enrolled in a local international school. Everything felt full of possibility. Then the pandemic broke out, and within weeks, I was back in China, stuck under strict quarantine rules that kept me from returning to school for over a year. No classes. No teachers. No clear path forward.

So I started figuring things out on my own. I taught myself Python. I read philosophy, not because I had to, but because I was searching for something to hold onto. I worked on my English, and slowly learned how to structure my own learning without anyone telling me what to do next. That period taught me something I had not expected: growth does not always need a stable foundation. Sometimes it grows out of the cracks.

High school / The second uncertainty

Finding my own path

The second wave of uncertainty came in high school.

At the end of tenth grade, our only computer science teacher left. Just like that, I lost the one person who could guide me further into the field I loved. For a while, I felt lost. My interest in computing and AI had always needed direction, or so I thought.

But then I realized: if no one is there to show you the way, you can still walk forward. You just have to find your own path.

So I started doing independent research, and over time, that grew into a long-term project I named LogosAI. At the same time, I saw that younger students no longer had any CS classes available. So a few friends and I started a computer science club, a space where we could teach each other, share ideas, and keep the spark alive. That club became more than just an extracurricular. It reminded me that knowledge grows best when it is shared.

Recovery / The third uncertainty

Reconnecting with the world

The third uncertainty hit the hardest.

Right before my IB exams, I got seriously ill and could not sit for them. That was a real blow, not just academically but emotionally. It took me months to recover, and even longer to rethink what I wanted to do with my life.

Then, on my mother's encouragement, I started doing community service. At first I thought I was the one giving help. But somewhere along the way, I found that I was the one being helped, finding joy again, rebuilding confidence, and reconnecting with the world outside my own head.

Now I am back in AI research, still refining LogosAI, still learning. I am working on a paper and hoping to submit it to a solid journal. But for me, publishing is not really the point. What matters is the process: learning through review, through feedback, through conversations with people who see things differently than I do.

Uncertainty & Knowledge

These experiences have shaped not just who I am, but how I think.

In TOK class, I began to see that uncertainty is not just personal; it runs through the whole enterprise of knowledge. Whether in physics or history, every claim carries some degree of unknowability. The real question is not how to get rid of uncertainty, but how to recognize it, work with it, and keep building knowledge that is honest about its own limits.

That idea echoes in my AI work too.

When I interact with large language models, I often notice contradictions. They give different answers to the same question, or shift their stance without warning. That is not a bug to be fixed; it is a feature of the territory. And it pushed me to start researching uncertainty in AI systems, which became a turning point in the LogosAI project.

I keep coming back to the same question: in a world where even machines cannot be certain, how do we design AI that is not just smarter, but more reasonable?

That question has become the thread running through my research and my thesis.

Looking back, I see now that uncertainty is everywhere. In life. In science. In the AI systems.

We cannot escape it. And we should not try to.

What we can do is learn to live with it, to understand it, manage it, and keep moving forward, not despite it, but alongside it.