Mapping Philanthropy: Dr. Lucia Gomez Teijeiro on Data Transparency, Computational Thinking & AI for Social Good
- Sorina I. Crisan, PhD
- Sep 27
- 19 min read
Updated: 4 days ago
What does it take to make the hidden world of giving more visible? In this captivating interview, Dr. Lucia Gomez Teijeiro—senior researcher at the University of Geneva and assistant professor at Bern University of Applied Sciences—explains how the Mapping Philanthropy project is transforming our understanding of philanthropy through data transparency and artificial intelligence. Launched in 2019, the initiative uses AI and natural language processing to map active philanthropic organizations across Switzerland and Europe, creating an open-source data commons that fosters collaboration and highlights their societal impact. What began as a research project has evolved into a university course, engaging students in real-world applications of computational thinking to serve social good. Dr. Gomez Teijeiro reflects on her journey from neuroscience to AI, driven by a passion for applied, project-based teaching that equips students to create tangible solutions. Central to her approach is persuasion, which she describes as “an art, part of the art of communication. When you communicate persuasively, it generates an intrinsic motivation cascade inside the listener”. She emphasizes the power of mindset, urging young professionals to believe in their unique path: “There is a place in the world for you, just go to the light”. Part of The Persuasive Discourse series, “Educators: Academic, Non-Academic & Hybrid,” this conversation reveals how AI, data transparency, and human connection can illuminate philanthropy’s vital role, inspiring a new generation to drive social impact with courage and computational insight.
Interview by Sorina I. Crisan – Matthey de l’Endroit, PhD
The Mapping Philanthropy Project
Q1: What is the Mapping Philanthropy project?
Answer: The Mapping Philanthropy project started in 2019 with the objective of tracing and describing all the philanthropic organizations (POs) that are active in Switzerland and beyond, at the European level.
The overall idea is to show what POs are doing across multiple countries and make the sector visible and searchable. To achieve this goal, we use artificial intelligence (AI) to derive insights from public information about these organizations.
We want to serve the philanthropic sector, so that organizations can find each other and unite forces. Moreover, we want to highlight and show its societal impact so that the general public can better understand what philanthropy is and does. There are many societal misconceptions when it comes to philanthropy, such as: it is only for a few, or that it is something marginal. In reality, philanthropy is a very large and diverse sector that is doing significant work in the world, and its actions cover what governments, companies, or educational institutions cannot or do not cover.
Philanthropy may be perceived as a net, connecting everything that nobody else sees. And what we want to do with our project is to visually map this hidden reality.
Q2: Why is the project based in Switzerland?
Answer: This project is taking place in Switzerland because Prof. Dr. Giuseppe Ugazio had the idea for it.
In 2019, he was appointed Chair in Behavioural Philanthropy and Finance, and he was also one of the lecturers of the Introduction to Neurofinance course I attended during my PhD studies. While taking that course, we got the chance to do a free research project, and I learned how to work with Natural Language Processing (NLP). When the course ended, he proposed to me to join forces to map the philanthropic sector using NLP and webscraping. I said “sure” and we started the work altruistically in our free time.
Q3: How is the Mapping Philanthropy project approach to data sharing different from what is already available on the market?
Answer: Our approach is academic. We believe that the knowledge that exists—or that humans generate and share publicly—should not be behind a paywall. As such, our approach is open source, based on the philosophy that together we build something sustainable and participative.
I understand that a company might identify and address a societal need—like mapping philanthropy—because it is necessary. And several businesses have built web applications that are essentially search engines for philanthropic organizations. That is great, but I believe companies should provide services on top of that functionality.
Currently, I support and collaborate with different companies so that together we may think about how to serve the entire philanthropic sector through marketable products, but the data itself, the search engine, and the way it is used and regulated—this is a decision in which philanthropy must be able to participate. It is not my decision alone as an academic, and it should not be the decision of companies alone either. Supervisory entities and philanthropic organisations also should have a say.
Q4: How did the Mapping Philanthropy project also become a course at the University of Geneva?
Answer: The transition to a course happened quite naturally. Dr. Ugazio and I believe in a different way of teaching. Already in 2019, he was in contact with someone at UNIGE who had received a prize for innovative teaching by proposing a course format called Institutional Project. This exists only in the Geneva School of Economics and Management, but I believe it should exist in every faculty of every university. The idea is that any bachelor-level student can engage in a research project, earn credits, and advance their studies by doing something with impact.
For us, that project was Mapping Philanthropy. At the beginning we were just two people, so we wanted to engage students and build a working team to make it happen. Already in 2020, we had the help of five students across the year. Thanks to them, we launched the first version of Mapping Philanthropy. Without them, it would have been impossible.
Since then, through the many phases of the project, we’ve reached the master’s course in philanthropy. What we are trying to do is transform these courses from the traditional model—where the speaker talks and students listen—into one where students do things. It becomes an institutional joint effort that translates into practice.
In this way, students not only learn but also gain professional experience and a track record of a real product they built as a team.
Q5: Which iteration of the Mapping Philanthropy project are you working on now?
Answer: This project will never end. That’s a nice question—which iteration is it? Let’s consider one iteration every two years. So maybe we’re in the third.
The first iteration was the version focused only on Switzerland, back then I was still a PhD student. After I defended my PhD and had more freedom to think and to start teaching, we began collaborating with Philea, an institution at the European level that represents philanthropic organizations, defends them, educates them, conducts research on trends, organizes events, and unites the sector.
With Philea, we prepared the first version of the web Data Commons for 2024. Right now, we are on the second version of the Data Commons with the students of this 2025 cohort, both bachelor’s and master’s. This version was presented in the ERNOP 2025 conference, in Germany.
For this semester, what Dr. Ugazio and I decided is that instead of continuing with data collection and analysis, the bachelor students will focus on a very necessary step we call the Critical Mass Project. In this project, each student group will select one philanthropic foundation anywhere in Europe—preferably from diverse countries to show variety—and highlight those foundations that made a transformation toward transparency. The idea is to bring visibility to organizations that can tell their story and show that being transparent actually brought them benefits. There are many benefits—trust, support for their causes, visibility.
A problem in philanthropy is that many organizations are afraid to say what they do. They fear backlash from society or being criticized, or to expose their beneficiaries. Often, they defend causes that are difficult by nature, so sometimes they stay behind the scenes and avoid making noise. But that also limits their impact, and it becomes a cycle. We want to show this critical mass and say: look, these philanthropic organizations saw the benefits of data collection, analysis and sharing—and those benefits are greater than any potential problems.
Q6: In hindsight, what has been the biggest struggle in pushing the Mapping Philanthropy project forward?
Answer: Everybody knows mapping philanthropy is needed and wants some form of a Data Commons. But there is this dynamic of both wanting it and fearing it at the same time.
So the struggle is this continuous go and stop—pushing it, believing in it, saying, “Yes, let’s do it.” But it’s for the moment a lonely fight. Whenever you go to a conference or a meeting with philanthropists, you perceive the fear.
Since 2019, we’ve been trying to move this project forward. We are not as alone as before, because now we have the support of Philea, ERNOP, and some other philanthropy infrastructure associations. So we have several voices saying, “We support you. Let’s try.”
What needs to happen—and what I wish for—is to start a process where a version is released without fear. Once that version is out and accepted by a few, the benefits will become clear. Then I hope more foundations will say, “That’s cool, let me join forces.” And then it’s not just me, Dr. Ugazio, our students, and Jack from Philea trying to make it happen. It will hopefully happen across Europe with the participation of POs.
Q7: And stepping back: What is the impact of Swiss philanthropy compared with other countries?
Answer: There are different indexes that track how impactful the philanthropic sector is in different countries. For example, there are Philea reports, Indiana University’s Lilly Family School of Philanthropy analyses, and there are world indexes and statistics of all sorts. All those are aggregates.
When you look at those, Switzerland is always in the top five of philanthropic activity. And this is due not necessarily because of assets, it is also about other numbers: the number of organizations that exist and the number of projects they do. Two years ago, Switzerland was in the top three, even above the U.S. This is impressive, given how small it is as a country, but the key is density: the density of organizations compared to the number of people. I believe it is the social plus governmental ecosystem that makes this possible, which is wonderful.
Defining Core Concepts
Q8: Before we talk about more details regarding your work, I’d like us to define three main concepts that you address in your field. First, what is philanthropy?
Answer: Philanthropy can be defined as the giving of private resources for the public good. The definition needs to be broad because the moment you try to constrain it, you’re no longer able to represent the diversity that is one of the main characteristics of philanthropy.
Philanthropy can be even a speech, and it is possible that I’m doing philanthropy right now by transmitting my thoughts.
For me personally, philanthropy is the act of giving without expecting any return. You feel good in exchange, and that’s good. And I believe the definition of altruism needs to be expanded. You should feel good for doing good and still be able to call it altruism.
In short, philanthropy is whenever you give and whatever you give, you don’t expect anything in return, though you feel good because you are giving.
Q9: What is NLP?
Answer: NLP stands for “natural language processing.” Basically, what most people think of when they hear AI is “natural language processing” (NLP).
More specifically, NLP is the computer’s ability to understand and produce “natural” language. The NLP field has now existed for 20 or 30 years and has slowly evolved into what we have today. For example, ChatGPT is a “natural language processing” algorithm.
Q10: What does “natural” mean within the context of “natural language”?
Answer: “Natural language” means the way humans “naturally” communicate their own thoughts and ideas.
Natural language considers not only what we say, but how we say it, and with what intentions and in which semantic space. The objective of “natural language processing” is not only to capture what is verbal or written, but also how we communicate; therefore, going beyond the words themselves. That is what makes it “natural.”
Career Trajectory and Teaching
Q11: In hindsight and as we move on to try to unpack and learn from your career trajectory: How did your personal interest in philanthropy begin?
Answer: When I started, I wasn’t interested in philanthropy as a concept or as a research field in the way I am now, because I didn’t even understand its scope. I’ve always been a philanthropic person, but it just happened naturally, without really knowing it. I was always volunteering here and there because I want to do everything, and there are organizations and causes that speak to me everywhere.
For example, I currently teach Spanish at the Université Populaire du Canton de Genève. That also happened naturally. When I first arrived in Geneva, I started studying German, and six months later, I was already volunteering to teach Spanish. In Spain as well, I was always involved in philanthropy, but I didn’t realize that’s what it was conceptually. I didn’t understand the concept, in the same way in which I believe the general society doesn’t fully understand it either.
When Dr. Ugazio asked, “Do you want to do philanthropic research?” I thought, What does that mean? I didn’t understand. Entering this world was confusing at first. Now I see the beauty of philanthropy in a way I couldn’t before. It is the sector that takes care of the most important problems in the world—all of them—because the sector is so diverse. There are organizations dealing with problems you would never even imagine exist unless you look. It’s endless, it’s rich.
Q12: How did you end up studying neuroscience, and why did you choose to become a student at the University of Geneva?
Answer: I think the two questions—why neuroscience and why Geneva—are one, and it is not something that I decided. It wasn’t me, my psychologist says that when you find your dharma, that’s the mission you’re supposed to have, and I believe that.
The first inflection point happened back in Spain, when I wanted to be a psychologist. I was studying psychology, planning to be a therapist but it didn’t happen, because it’s not always about what you want, it’s about what life wants for you. I was maybe 23, and I wasn’t psychologically ready to be a therapist. Now I know why: I wasn’t patient. Maybe I’m still not. I’m more like: go, go, go. People have their own timing. To be a therapist, you need patience, and I didn’t have it.
I was lost because what I thought I wanted in life wasn’t for me. And I wondered: what is for me? I thought about doing a master’s—just because it seemed the obvious next step. At the same time, the political and economic situation in Spain didn’t fit with my values. So I said, it’s time to leave and I sent my CV and motivation letters to master’s programs across Europe, including Switzerland. Out of all the people I contacted, only one replied and that was the second inflection point.
The person who replied to me was Prof. Dr. Alexandre Dayer. I want to make a special mention of him in this interview as he’s no longer with us, but he was my professional father. He trusted in me, he replied to that email I sent as he got curious about my atypical profile and invited me to an interview for the master’s program. He realized I had no knowledge his research proposal for the master’s—it was in molecular neuroscience, as that master’s is an interdisciplinary research-oriented program. I got accepted but I didn’t know the language of the region (French), and I didn’t know molecular biology, but Alex was the kind of person who could see and appreciate intrinsic motivation. One month after that interview, I was in Switzerland, starting a radically new life and career path. Alex allowed me to do whatever I wanted in molecular biology, even supported my transition to computational approaches, as he valued my motivation more than my knowledge.
By the end of the master’s, I wanted to minimize lab experiments, because the chemicals aren’t healthy, the work is slow, and it involves using animal tissue. I didn’t feel aligned with that type of work but I still loved molecular biology, so the second inflection point arrived: to study it computationally. At the time, only one person in the Department of Neuroscience at the University of Geneva was doing computational neuroscience for transcriptomics: Dr. Julien Prados, and he was working in Alex’s lab. Now, he works at the bioinformatics platform. Alex agreed for me to learn from and work with Julien. At first, I didn’t know how to write a line of code, I just had the will, both Alex and Julien supported me.
That’s how I ended up doing what I do—AI. I believe that any question, from any discipline in the world, can be modeled with a computer, so AI makes me feel free and aligned.
Q13: For some clarification: What is your role at the University of Geneva today?
Answer: At the University of Geneva, my position is called senior researcher and lecturer. It means that I teach and do research.
Q14: Your online profile reveals that you are also working with the Bern University of Applied Sciences. What is your role there? And, thinking of teaching as a craft: How does this university’s teaching approach differ from other academic institutions?
Answer: I’m an applied scientist, which means a researcher that develops research with clear applications outside academia. That’s why the perfect job and place for me is at an applied-oriented institution such as Bern University of Applied Sciences (BFH). There, I teach data science and AI as well, interdisciplinary topics, but adding a focus on finance and business—the for-profit side of things. I am the person who brings the philanthropy angle to Bern, and I’m sure it will slowly grow into something more.
I joined BFH in 2024 as an assistant professor. My closest colleague there is Prof. Dr. Branka Hadji Misheva. She’s wonderful, her teaching approach is similar to mine and we are very aligned overall. We prepare students as if tomorrow they would be data scientists in a company—we teach how to do things. We talk very little, and students do a lot.. We do not evaluate with exams, I don’t think exams test understanding or knowledge well. Instead, we run project-based courses where, for example, students create data science products that bring business value, whatever the business field is.
For example, last year we proposed a project comparing Disney parks around the world by analyzing customer reviews to understand what works and what doesn’t in each park.
Q15: You were asked to design an AI specialization program at the Bern University of Applied Sciences. How did that come about and what does it involve?
Answer: Last year BFH considered me as the right person to design the AI specialization program for digital business bachelor students.
Students in this program spend two years learning basic knowledge in business administration or digital business and then they choose a specialization program to complete the degree. The AI specialization program has three modules. One is about learning the basics of programming, another about innovation and ethics in AI, and .the module I’m teaching, together with Branca and Julius Kooistra, is called AI Applications in Industry. We, as a team of teachers, joined forces with the Start Hub at BFH, which is a subunit inside the university that coaches students and staff in entrepreneurship. Together, we offer a 360-degree perspective on how to go from an idea with business value and involving AI, to the industry. The objective is for students, working in teams, to create a minimum viable product of a startup using AI during the length of one semester.
Specifically, the module starts with a hackathon where groups are formed and ideas about societal needs are brainstormed and shaped. Then, over three weeks, we show them how the AI solutions of existing startups can be built technically. After that, they have the rest of the semester to work on their product, and they can access to both business and technical support. The final evaluation is like a Shark Tank, where teachers, the Start Hub, and people from AI companies judge the students’ minimum viable product. If they wish, they can keep having the support of the Start Hub to actually launch their startup, and maybe even become successful entrepreneurs.
Persuasion and Communication
Q16: What does persuasion mean to you?
Answer: Some people understand persuasion as negative, others as positive. I see it as a positive thing, as an art, part of the art of communication. When you communicate persuasively, it generates an intrinsic motivation cascade inside the listener, it is a natural way of connecting and engaging.
Q17: Can you share an example of how persuasion has helped you in your life?
Answer: I am Spanish and therefore I am lucky because we Spanish people communicate generally in a passionate way, with strength, an ingredient of persuasive communication that has helped navigate life. When you share an idea with the emotional weight it carries—with your real passion—the other person may immediately connect. And when you connect with someone, in any context, collective action initiates.
An example, I remember when I found the apartment where I live now. Tired of getting rejected, apartment after apartment, with only two months until contract expiration, I read an ad on Facebook and visited the apartment the next day. I communicated with the renter with all naturalness, with all my emotions and no filters, and I did the same with the company handling the rental. We connected as humans, and they all agreed to assign the apartment to me without looking for additional candidates (of course upon the approval of the owner). I think that’s an example of persuasive communication and how it can help in life. Persuasion happens when intentions and emotions are genuine, and the communication is charged with naturalness. I am not afraid of showing my vulnerability. For me, persuasion is about communicating and connecting through passion, with authenticity, and from the heart.
Q18: How do you adapt your narrative so that different audiences can understand your complex work? Does persuasion play a role in that—and how do you make science and data engaging for the public?
Answer: In Spain, we say that you know something, and you can truly transmit that knowledge to someone else, when you’re able to explain it to your grandma.
The more you know about something, the harder it gets to explain it simply, because you get too technical and far removed from the world’s general understanding of that topic. Dry science that does not reach societies is useless. Almost nobody reads super peer-reviewed, high-impact papers, and that’s unfortunately the game of prestige in science. What matters to me is letting people know what’s happening in science, what the questions are, what we are discovering, and why it matters. I like engaging audiences and transmitting knowledge to the public. I believe scientists should do this more often.
On September 3rd, 2025, I was with Giuseppe Ugazio and Jack O’Neill at Kursaal in Bern, invited by SwissFoundations to give a workshop on Transforming Philanthropy Together. I remember two years ago, during Swiss Philanthropy Day, we gave a workshop in the same place. The audience was full of philanthropists, not academics. We turned the session into something playful, almost like a show. At one point, we had a lot of philanthropists shouting together, “We want data! High-quality data!
I think science divulgation must be made playful. You need to explain things in a way your grandma would enjoy and understand. It is potentially more important to transmit motivation than information, the latter of which can be read online. But when you speak with people, to an audience, you want them to remember the feeling that: This is important.
Future Outlook and Career Advice
Q19: Do you think coding is still an essential skill for the future?
Answer: Absolutely, but with a nuance. Coding is a skill of the future but not in the way it was done and taught until two years ago.
My students all know that I don’t want them to memorize code or to learn to write code, because AI can do that for you now. What I want them to learn is computational thinking. That’s the real skill. Programming opens your brain to a new dimension of reality that you wouldn’t otherwise develop. It’s like being a musician or not. If you’re a musician, you decode a new part of your brain, a new thinking mechanism that sparks creativity to everything else you do.
AI can write code, so you don’t need to memorize it, but you still need to understand it and also how to communicate with a computer. Computational thinking is the way you transform an abstract idea into a set of instructions to an AI coding agent that produces a piece of code doing what you want, and then you make sure it is correctly doing so, the way you wanted, and without risks or biases.
Let me give a visual example. I studied architecture for one semester, and I loved drawing back then. But the hardest part of drawing is transforming a vivid image in your head to an image on paper. When you try to materialize a mental image, it vanishes. To be a painter, you must train to keep that image in your mind and turn it into a product. That’s what computational thinking is: holding the idea, keeping it alive, expressing it and transforming it into something functional and real.
Maybe in ten years, robots will be everywhere. And, if by then you master computational thinking, you can tweak the robot to make a macchiato, not just a standard coffee. If you don’t, you’ll just accept whatever default cup of coffee that the machine gives you.
Q20: Do you see philanthropy and AI as a field for the future?
Answer: It’s very needed, but I cannot promise that philanthropy and AI is the profession of the future, because philanthropy is a traditional sector, with many barriers, so it’s not the field where AI will flourish the fastest or with the greatest demand. Need and supply are not the same.
Philanthropy is a sector that moves slowly, and I think that’s also why it needs AI so much. Philanthropic organizations are usually just a handful of people fighting for something with vision, conviction, and passion, but with almost no resources. AI can automate processes, freeing time for these people to take care of their causes.
So my advice for those wanting to follow a career path in AI and philanthropy is this: first, find your own security zone, a field of work that gives you food, healthcare, and a roof. And, once you have that, then you can dedicate some of your time to the field of AI and philanthropy if you wish.
Everyone chooses their own direction. For me, AI and philanthropy is a field to pursue forever, because there are very few people in it, and it’s necessary to empower those small groups with big causes, who don’t have resources.
Q21: What advice would you give to young professionals and students starting their careers today and are interested to follow in your footsteps?
Answer: If I had to choose one thing to give as advice, it is mindset, mindset, mindset. The way you think largely defines how your career will develop, because thinking shapes behavior, and also how you present yourself to the world.
Here is a metaphor: when a plant is growing and emerging from the soil, it naturally knows how to find where the sun is and that it’s a good idea to grow towards the light. Humans have similar intuition, but at some point in evolution, we stopped listening to it. The key is to learn how to silence the mind and the ego.
Try to be yourself, because you are unique. There is a place in the world for you, just go to the light. And along the way, life will tell you “no” sometimes, or you’ll face difficulties. When I wanted to be a therapist, I suffered. It was difficult. But that just meant it wasn’t my dharma, it wasn’t my path.
So believe—mindset is belief—believe there is a place for you. And when you arrive at the place that is for you, you will feel so connected to it, so aligned, that you’ll know: this is it. But this only happens when you let go of the ego, listen to your intuition, and tell yourself: I believe. I can. Nothing stops me.
And when someone offers you an opportunity, unless there’s a real reason you cannot do it, say yes, because opportunities are hidden in the smallest details of life. Maybe one day you just go to the supermarket to buy rice, and your path is maybe there, in that supermarket, your future is waiting. You never know.
Thank you for reading.
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Assistant Professor at Bern University of Applied Sciences
Lecturer and Researcher at the University of Geneva | Switzerland
*Note: This This interview was recorded on August 29, 2025, and has been edited for clarity, ease of readability, and length.
**Illustrations: The profile and main article photos shown in this interview were made available by Dr. Lucia Gomez Teijeiro.
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