AI & democracy
How can large language models support - rather than undermine - deliberation, participation and collective decision-making? This page documents my ongoing exploration of how AI reshapes the way we discuss, disagree, and govern ourselves, in institutions, organisations, and everyday democratic life.
Why this project?
I work in applied AI and have spent several years building real-world systems. In parallel, I am increasingly concerned by the impact of AI on democratic processes: who speaks, who is heard, how decisions are made, and what role automated systems play in all of this. My goal is simple: understand how we can use new language models (LLMs) to strengthen democratic practices instead of weakening them.
I approach this topic from three angles:
- Citizen (40%) — understanding and contributing to issues that affect us collectively.
- Intellectual (40%) — reading, structuring ideas, and connecting disciplines.
- Professional (20%) — reflecting on the future of AI practice and applied ethics.
My approach
1. Read and map the field
I conduct an exploratory but in-depth review of recent work on AI-mediated deliberation, collective intelligence, and democratic innovation - including systems like Polis, experiments in "AI-mediated deliberation", and the intersection of computer science and political theory.
2. Prototype and experiment
Theory is not enough. I apply my engineering background to build prototypes and Proofs of Concept (POCs). Testing how LLMs interact with real political arguments allows me to confront academic promises with technical reality (latency, hallucinations, bias).
3. Teach and share
I synthesized this research into a comprehensive module on AI & collective intelligence. It bridges the gap between technical constraints (transformers, bias) and democratic theory to explore concrete applications for organizations. This website gradually becomes the place where I publish notes, slides, and document my ongoing thinking.
4. Connect with the field
Democracy is a collective effort. I actively engage with researchers, civic tech builders, and institutions to ground these ideas in practice and avoid the "techno-solutionism" trap.
What you can explore here
This section gathers the resources I have created or relied upon in my own exploration - teaching materials, curated references, and ongoing notes.
Teaching module: AI & collective intelligence
A two-hour session exploring how LLMs interact with deliberation, participation, and large-scale decision processes.
View slides (PDF) →References & reading list
The knowledge base behind this project. Includes sources cited in the lecture and my active reading list on the topic.
Explore the library →Notes, ideas & open questions
I am particularly interested in questions such as:
- When do LLMs help people understand each other better - and when do they distort?
- How can we design deliberative processes that remain legitimate when AI is involved?
- What does "democratic alignment" of models mean in practice, beyond slogans?
As this project grows, I will publish short notes and reflections here.
Why share this publicly?
The democratic implications of AI should not remain confined to research labs, corporate roadmaps, or policy reports. They deserve open, accessible and informed discussion. This website is my way of contributing: through pedagogy, transparency, and a willingness to build understanding with others, not alone.
It is a small stone in a much larger democratic conversation.