We now have the chance to scale and improve such deliberative processes exponentially so that citizens’ voices, in all their richness and diversity, can make a difference. Taiwan Province of China exemplifies this transition.
Following the 2014 Sunflower Revolution there, which brought tech-savvy politicians to power, an online open-source platform called pol.is was introduced. This platform allows people to express elaborate opinions about any topic, from Uber regulation to COVID policies, and vote on the opinions submitted by others. It also uses these votes to map the opinion landscape, helping contributors understand which proposals would garner consensus while clearly identifying minority and dissenting opinions and even groups of lobbyists with an obvious party line. This helps people understand each other better and reduces polarization. Politicians then use the resulting information to shape public policy responses that take into account all viewpoints.
Over the past few months pol.is has evolved to integrate machine learning with some of its functions to render the experience of the platform more deliberative. Contributors to the platform can now engage with a large language model, or LLM (a type of AI), that speaks on behalf of different opinion clusters and helps individuals figure out the position of their allies, opponents, and everyone in between. This makes the experience on the platform more truly deliberative and further helps depolarization. Today, this tool is frequently used to consult with residents, engaging 12 million people, or nearly half the population.
Corporations, which face their own governance challenges, also see the potential of large-scale AI-augmented consultations. After launching its more classically technocratic Oversight Board, staffed with lawyers and experts to make decisions on content, Meta (formerly Facebook) began experimenting in 2022 with Meta Community Forums—where randomly selected groups of users from several countries could deliberate on climate content regulation. An even more ambitious effort, in December 2022, involved 6,000 users from 32 countries in 19 languages to discuss cyberbullying in the metaverse over several days. Deliberations in the Meta experiment were facilitated on a proprietary Stanford University platform by (still basic) AI, which assigned speaking times, helped the group decide on topics, and advised on when to put them aside.
For now there is no evidence that AI facilitators do a better job than humans, but that may soon change. And when it does, the AI facilitators will have the distinct advantage of being much cheaper, which matters if we are ever to scale deep deliberative processes among humans (rather than between humans and LLM impersonators, as in the Taiwanese experience) from 6,000 to millions of people.