The Tech > Participatory democracy > Engagement tech > Digital twins (of the public) - (11)

Love it or hate it, more projects are building synthetic versions of the public. They're used to consult (a proxy for) public opinion in real-time for a fraction of the cost.

As Matt Stempeck wrote in People Powered's Guide to Digital Participation Platforms (2025):

"AI's ability to synthetically represent complex systems has inspired research to use it to create synthetic agents as proxies for engaging actual people. Google Deepmind's AI lab teamed up with Stanford and other researchers to create AI agents that, the authors claim, can reliably predict what the people themselves reported after 2 hours of upfront training. The accuracy of the synthetic person-agents suffered in other situations, such as in economics games.

Future research will likely improve upon these results, but the entire direction of this work represents an existential decision point for participatory democracy. Do we want to cede our involvement to AI proxies that may (or may not) represent what we would say or do in a given situation? Even if they proved accurate, what do we lose from people not personally engaging with one another, within communities and between the elected and the governed? If decisionmakers can only consult AI avatars, will it be possible to heed the thoughts and lived experiences expressed by AI with the same care that comes when speaking with human constituents?

Should we celebrate a near future where "politicians can talk to these avatars and get to know members of the public in a really granular way"? What do we lose when public officials can skip some of the few remaining opportunities for engaging their constituents, and vice versa? Is it another dangerous step towards disenfranchised citizenry? 

Much of the value in democratic systems lies in the interactions we have with one another. Participation and engagement with political systems drive benefits well beyond the specifics of a given policy outcome. AI increasingly tempts us to automate ourselves out of our involvement with an ever-expanding range of activities, with all of the associated promises and risks discussed in this report. But is automating away the active role of the people in democracy a step too far?"

Showing 11 Results

Improving Cross-Cultural Survey Simulation with Calibrated Value Personas

Researchers developed a value-based method for prompting LLMs that uses culturally grounded survey-derived value profiles instead of demographic proxies, significantly improving the models’ ability to predict and reproduce diverse population opinions across countries, especially in underrepresented cultures.

PoliSim

PoliSim

Polisim

PoliSim is open-source civic infrastructure that connects official public data — 71 million census observations, open electoral records, verified polling — with transparent AI to help NGOs, civic bodies, and political consultants communicate more effectively. Before investing in a campaign. On publicly auditable data. With declared limitations.

'Simulacrum of Stories': Examining Large Language Models as Qualitative Research Participants

We argue that the use of LLMs as proxies for participants enacts the surrogate effect, raising ethical and epistemological concerns that extend beyond the technical limitations of current models to the core of whether LLMs fit within qualitative ways of knowing.

Delphi

Delphi

San Francisco

Turn your knowledge into an interactive profile people can talk to.

Electric Twin

We build synthetic audiences that simulate how your customers will behave.

AI can help humans find common ground in democratic deliberation (Habermas Machine)

Google DeepMind and Stanford researchers built the "Habermas Machine" and found that AI mediators generated more palatable summary statements of the discussions, as rated by participants, than human-written summaries, while still representing minority views in the final version.

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