Almost a year ago, I stumbled upon an Instagram post from ETH Zurich about an internship offer for the United Nations Office in Bangkok, more precisely at UNDRR (Disaster Risk Reduction). The 21-year-old, applied Maths master’s student I was at the time, with close to no professional experience, did not think for a minute I had a chance. For some reason I decided to I read the offer and noticed met all the requirements, so I gave it a shot.

I applied internally with the ETH Studios, passed this first screen, then with the UN, got the interview, did the interview, got the position, each step being a complete surprise for me and I still was a bit baffled (and jet-lagged) on my first day in office in September. Everything was new (and a bit scary) to me and the onboarding process was a lot to assimilate.

I would describe this internship as a double way learning and teaching experience: I learned from my supervisors and my team (the Tech & Design team of UNDRR) how a big international agency works, and what current technologies are used in disaster mitigation. In turn, I got to teach them a bit about I learned at ETH: neural networks, LLMs, reinforcement learning… and how these tools can be used in the organisation.

As I was the first ever data and AI intern, I had to build from scratch with minimal resources and no pre-existing workflows. We figured out a lot of things on the go. The arrival of two other new interns at the same position as me, one of whom is also an ETH student, helped to speed up our work.

I primarily worked on two projects: a machine learning based catastrophic model for fragility assessment during seismic events, which I did alone, and a RAG chatbot based on UNDRR, with 3 other people. We were able to deliver working Proof Of Concepts for both, which was a big success given our modest beginnings. I was also the first presenter of a series of webinars about AI related topics, which are still delivered weekly to the entire UNDRR staff to this day. 

This goes in hands with what I would consider as my biggest accomplishment during this internship: planting the seeds of a proper machine and deep learning service at UNDRR (which was the vision our team’s boss had in mind when creating the internship offers). By the end of my six months, the proof of concept opened up opportunities for potential partnerships and funding to continue the work. A new ETH student is also starting her internship right when I finish and I personally see a real potential in a closer ETH/UNDRR partnership.

On a personal level, those past 6 months were an amazing adventure, full of new people from all over the world and travels around Thailand and Asia in general. Bangkok ended up feeling like home and coming back to Switzerland and its 9 million people (half of the population of metropolitan Bangkok) will certainly be quite the change; that and the price of groceries!

It feels like I took off for BKK airport only two weeks ago but in the meantime, the person I am now is fundamentally different from the student who arrived a bit late to work with his brand-new suit in September. I guess this is how growing up feels like.

ETH Studios

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Contact eth-studios@ethz.ch if you are interested in more information on and about the ETH Studios.

Few places make the tension between technological promise and ethical responsibility as tangible as Davos during the World Economic Forum (WEF). On Wednesday, January 21, I had the pleasure of experiencing the WEF in Davos, with a particular focus on artificial intelligence and the role of science in diplomacy. 

At the Rosenberg House, high school students presented their thoughts on the responsible use of AI and the necessity of addressing this rapidly advancing technology as early as possible in education. It was wonderful to see young minds beginning to tackle prominent societal issues, such as the rifts that can emerge when powerful tools are not accessible to all. During an informal lunch, I greatly enjoyed probing their planned projects and discussing current scientific limitations. 

The WEF is fundamentally about dialogue. Meeting new people, being introduced to new perspectives, and gaining access to a deep pool of expertise from professionals across disciplines are among the highlights of the experience. Together with newly made friends from the Australian Council on Foreign Relations, a unique ‘do-tank’ and a forum for corporate diplomacy, we headed to the House of Switzerland for a panel on foresight and strategy in the age of AI. On the way, Air Force One’s helicopter was just arriving, and the panel was later overshadowed by a harrowing speech by the President of the United States of America. That day, many heads were shaken in disbelief—not only in Davos, but around the globe. 

A particularly memorable takeaway from the panel was the harsh reality that foresight, whether corporate or governmental, must always account for even the unthinkable. Especially in today’s turbulent times, in which it seems that every “piece of ice” is fair game in the geopolitical landscape. 

The evening concluded with more food for thought at RETHINKING Science Diplomacy at the Physical Meteorological Observatory. Professor Mesot opened the event with an anecdote from the COVID-19 pandemic, highlighting how crucial it is for scientific institutions and governments to come together and collaborate more closely than ever in times of crisis. The discussion emphasized the push and pull surrounding scientific facts, underlining that the supply of research is only meaningful when there is an equivalent demand from the public. One of the major challenges of our time is reinvigorating an appetite for tested and proven facts over populist headlines that feed on ever-increasing angst. 

There is clearly much work ahead. I fully agree that the scientific community has a responsibility to actively engage in outreach to broader society. While there are many worrying developments, there are just as many positive efforts aimed at addressing challenges constructively and maintaining lasting trust. 

What does it take for organisations and individuals to keep innovating when technology cycles speed up, hype multiplies, and AI can generate “answers” in seconds?

Those were the questions at the heart of the ETH Global Lecture “Empowering Innovation: Thriving in the Age of AI”, where ETH alumna and executive Petra Ehmann and ETH Professor Stefano Brusoni explored how innovation actually happens in practice, and what changes when AI enters the picture. The conversation was moderated by Chris Luebkeman, Head of ETH Zurich’s Strategic Foresight Hub.

Innovation is not a vibe. It’s staying power.

Petra Ehmann offered a definition that cuts through the buzzwords: innovation is not about novelty for its own sake — it’s about longevity.

“To me, innovation is giving longevity to a company, making it invincible so that it will thrive in the future.”

She also dismantled a few familiar myths:

“Innovation is not a bunch of geniuses who sit in the room and they tinker something crazy… Innovation is not a fun, colourful park with nice cushions… It’s hard work.”

The subtext is important: real innovation is less about theatre and more about customer value, iteration, and the discipline to keep going when outcomes are uncertain.

The winners aren’t occasional innovators, they’re systematic ones.

Stefano Brusoni highlighted a difference many organisations underestimate: the gap between having one good idea and building the capability to innovate repeatedly.

“Very few companies are really good at becoming systematic innovators.” 

And he described the unglamorous reality of how that capability is built:

“It’s this process of trial and error and then error and then again an error where you stay persistent… that really set apart the occasional innovators from the systematic innovators.” 

Petra echoed this, adding that innovation is fundamentally a learning process — and learning is rarely “efficient” in the short term because it involves mistakes.

Culture change starts at the top.

One of the most concrete practical lessons came through in the discussion about culture: if leaders demand innovation but punish missteps, experimentation dies.

“Permission to fail… is super important and it has to come from… the board.” 

This matters even more in the age of AI, when output is cheap and prototypes appear instantly. Evidence becomes the antidote to building impressive things nobody wants.

AI won’t change the fundamentals, but it will change the speed.

Both speakers agreed: innovation still depends on building something people need, but AI changes the velocity.

“What will change is the velocity, how fast you’re getting to that point.”

Petra also predicted a shift towards hyper-personalisation, to which Stefano added a thoughtful distinction: unlike older tools (such as calculators), generative AI works best when humans share the why, not just the what, which turns problem-solving into a dialogue.

“Suddenly we are engaged in a conversation… that is actually shaping the problem.” 

But with speed comes risk: the internet can fill with “cringe” content at scale, and organisations can confuse quantity with impact. Petra put it bluntly:

“The big question is not how much you do, but what is the impact of it.”

The real competitive edge: skills, critical thinking, and the courage to upskill.

A recurring theme was that thriving in AI-era organisations requires more than familiarity with the latest tools. Petra’s advice: cultivate depth and judgement.

“The most important one is having some very deep knowledge that AI cannot have… [and] critical thinking.”

Stefano broadened that into a challenge for universities:

“Our job is… making sure that… our students have more opportunities than at the beginning of their studies.” 

In the end, the lecture made one thing feel refreshingly clear: AI can help you move faster, but it can’t tell you where to go. Direction still comes from a North Star, from critical thinking, and from teams that have the permission and the desire to be curious and continue to learn.

Check out the pictures from the event here: Meet ETH Flickr

And in case you missed it, watch the talk here:

At the latest ETH Zurich Global Lecture, Liisa-Ly Pakosta, Estonia’s Minister of Justice and Digital Affairs, and incoming Vice President for Knowledge Transfer and Corporate Relations and digital ethicist Professor Effy Vayena, joined Chris Luebkeman to discuss how trust, transparency, and practical regulation are shaping the future of AI governance in Europe. Drawing on Estonia’s digital transformation and Switzerland’s sectoral approach, the panel explored the challenges and opportunities of implementing the EU AI Act.

How do we govern artificial intelligence in a world where technology evolves faster than regulation? This was the central question at the recent Global Lecture, “The EU AI Act in Practice: Cross-Border Perspectives on AI Governance,” hosted by Chris Luebkeman, Head of the Strategic Foresight Hub at ETH Zurich. At the start of the event the room was packed, making it one of the most well-attended lectures of the year, with a strong Estonian delegation and Estonian students keen to show support for their country’s inspiring representative, in addition to a curious ETH audience.

Liisa shared Estonia’s journey as a digital pioneer, explaining, “After regaining independence in 1991, we had to build an efficient state with limited resources. We chose a digital path, making transparency central to our approach.” Estonia’s investment in universal internet access and digital literacy laid the groundwork for a government where citizens own their data and can see exactly who accesses it—a model that has fostered deep public trust. “Trust is fundamental. People own their data and control who accesses it. This transparency builds trust and security,” she emphasised.

Effy reflected on the broader European context, noting that while many countries have the technical capacity for digital transformation, “regulatory and citizen engagement challenges remain.” She highlighted that transparency and clear benefits are key to building trust, regardless of a country’s starting point.

As AI systems become more embedded in daily life, the question of trust extends beyond government to technology itself. “We typically trust people, not machines,” Effy observed. “For AI, we seek reliability, safety, accountability, and transparency. Citizens want assurance that systems are safe and that someone is accountable.”

Liisa described Estonia’s evolving AI strategy: “We realised the need for full government control over sensitive data. We oppose backdoors in systems, even for law enforcement, to maintain trust and security.” She also stressed the importance of defining what AI should not do: “Declaring what is off-limits is crucial for maintaining trust.”

The EU AI Act aims to regulate AI in line with European values, but its complexity and the challenge of keeping pace with technological change were recurring themes. “The Act is complex, and simplification efforts are already underway,” Effy explained. In contrast, Switzerland, not an EU member, has opted for sectoral rather than horizontal regulation.

Liisa added, “Estonia advocated for more sectoral rules and a better balance between innovation and regulation. While rules are necessary for trust and clarity, the Act’s implementation is unclear, especially regarding prohibited and high-risk areas. Regulatory burdens often fall hardest on small and medium enterprises.” To address this, Estonia is developing a law to guarantee compliance for companies, shifting the burden from businesses to the state, and offering a compliance sandbox and state guarantees for AI products.

To close the discussion, Chris invited the speakers to a series of rapid-fire questions, offering concise insights on some of the other pressing dilemmas in AI governance:

• What builds trust faster: strong regulation or strong transparency?
  “Transparency,” said Liisa.
• How do you manage security and backdoor access?
  “Use separate, secure architectures like X-Road.”
• How will Estonia navigate differences with the EU?
  “With courage.”
• Why is there a discrepancy between attitudes toward pharma and AI regulation?
  “Pharma regulation has a longer history. We’re still defining our goals in AI,” Effy noted.
• Do we need a UN convention on AI?
  “Statements exist, but implementation and enforcement are key.”

Looking Ahead

The Global Lecture made clear that responsible AI governance is not just about rules—it’s about building systems that earn and deserve public trust. As Liisa concluded, “Despite technological possibilities, regulation must enable innovation while protecting individual freedom and imperfection. Estonia welcomes collaboration and research in this area.”

The conversation underscored that while the EU AI Act is a significant step, the journey toward trustworthy AI is ongoing—and will require courage, transparency, and a willingness to learn across borders.

Chris closed the event by thanking the panel for their “clarity, depth, and inspiration,” adding, “It’s been a joy, and I’ve learned a lot.” His words captured the spirit of the session: open dialogue, shared learning, and a commitment to shaping a trustworthy digital future.

Check out the pictures from the event here: Meet ETH Flickr

And in case you missed it, watch the talk here: