Designing AI-augmented collective decision-making
A teaching module for master's students at the intersection of AI research, deliberative theory, and process design.
Looking for the tech talk version?
View tech talk: Can LLMs improve collective decision-making?Most programs that address AI and society stop at the diagnosis: models are biased, platforms are polarizing, democracy is under pressure. This module goes further. It asks how collective decision-making processes can be deliberately designed to make good use of AI, rather than be distorted by a naive deployment of it.
Drawing on recent work in AI research, deliberative theory, and civic technology, the module gives students the conceptual tools to analyze, critique, and design socio-technical systems at the intersection of artificial intelligence and democratic participation.
Topics covered
- LLM architecture and limitations
- Democratic deliberation and collective intelligence
- Algorithmic bias and opinion aggregation
- Civic technology and digital democracy
- Collective decision-making process design
- Democratic values and algorithmic legitimacy
What your students will take away
- A clear-eyed understanding of how LLMs actually affect democratic deliberation, beyond the hype and the fear.
- The ability to distinguish naïve AI deployments from genuinely augmentative ones, and to articulate why that distinction matters.
- A conceptual framework they can apply to design or critically evaluate AI-assisted collective decision-making processes.
Format
2 hours. Suitable for master's programs in public policy, digital humanities, political science, engineering, or management with a tech & society component. Can be adapted as a seminar, workshop, or lecture depending on the pedagogical context.
About the speaker
Olivier Nguyen Quoc is an engineering manager with 9 years of experience building data and AI products. He developed this module from a sustained engagement with recent research at the intersection of AI, deliberative theory, and civic technology. His approach is that of a practitioner: technically grounded, intellectually rigorous, and attentive to the social consequences of the systems he builds.
Full profileInterested in this module?
If you're building a program around AI, democracy, or digital transformation and are looking for a rigorous, interdisciplinary teaching module, feel free to get in touch.
Get in touchPresentation Deck
Slides are being finalized and will be published soon.