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AI

AI and the New Era of Science

Artificial Intelligence is advancing faster than any of us could have imagined. Every week, new tools and applications emerge, reshaping the way we think, work, and create. For today’s PhD students and researchers, this is a rare moment in history — a chance to accelerate projects, eliminate repetitive tasks, and devote more energy to the questions that truly matter.

That’s why I’ve embraced AI in my own PhD work. It’s not just about enhancing the science itself, but about organising my workflow more effectively, communicating ideas with greater clarity, and sharing them more widely. AI is not here to replace scientists; it’s here to sharpen our tools so we can focus on what matters most: discovery. My goal is to learn how to use it both efficiently and responsibly, turning it into a genuine partner in research rather than a novelty.

Of course, this new power comes with challenges. Ethical considerations, from fairness and bias to environmental impact, are real and pressing. But awareness of these issues doesn’t mean slowing down; it means applying AI where it truly matters, and doing so with care. In the past, I used AI inefficiently simply because I didn’t fully understand its capabilities. Now, with more experience, I not only work faster but also reduce my environmental footprint. The only way to have zero impact would be to avoid AI entirely, but in a few years, avoiding it will be almost impossible. The real task is to use it wisely.

The next generation of PhD students will work in ways that look nothing like today. They will grow up with AI as a natural extension of their scientific process, asking questions we can’t yet imagine. It’s an exciting era, and I feel fortunate to witness how far we may push the boundaries of knowledge. Part of my own learning is finding ways to connect with this new generation and collaborate with their brilliance.

Research as Living Apps: The Future of Scientific Collaboration

🌐 The Vision

Imagine a world where research isn’t locked away in static PDFs, but exists as interactive online applications.
Instead of reading a paper, other scientists — or even AI research agents — could run your method, tweak parameters, and explore new scenarios instantly.
Your work becomes not just a description of an idea, but a living, executable tool.


Name for the concept:

The Living Research Web — where every project is an app, every scientist is connected, and every idea can evolve.


🤖 Agents as Collaborators

In this ecosystem, AI agents act as active participants in the research process:
- They search for relevant research‑apps.
- They request permission to use your method.
- They experiment with variations, generating new results.
- They acknowledge your contribution automatically in their outputs.

This transforms the current “read → interpret → re‑implement” workflow into “discover → run → build upon”.


🔍 Why This Matters

Today, researchers must: 1. Find relevant papers.
2. Understand the methodology.
3. Recreate the code or experiment from scratch.

This is slow, error‑prone, and often discourages replication.
With research‑as‑apps:

  • Reproducibility is built‑in.
  • Collaboration happens in real time.
  • Impact is measurable — you can see exactly how and where your work is used.

🔒 Permission and Control

Not every researcher will want their work to be open by default.
This system could include: - Permission requests before an agent or human can run your app.
- Usage tracking so you know who used it and for what.
- Licensing options (open, restricted, commercial).

This ensures you retain control while still enabling collaboration.


📈 The Network Effect

As more research is uploaded in this format: - AI agents could map the global research landscape in real time.
- Scientists could find and combine methods instantly.
- Entire multi‑disciplinary experiments could be assembled from existing apps in minutes.

The result? A living web of science — where knowledge flows faster, connections form naturally, and innovation accelerates.


🚀 A New Era of Scientific Connection

This isn’t just about convenience — it’s about changing the culture of science.
From isolated silos to a real‑time, permission‑aware, AI‑enhanced network of researchers and tools.
Your work wouldn’t just be read — it would be used, extended, and kept alive.