“The Simple but Ingenious System Taiwan Uses to Crowdsource Its Laws: VTaiwan Is a Promising Experiment in Participatory Governance. But Politics Is Blocking It from Getting Greater Traction”, 2018-08-21 (; backlinks):
[Paper: et al 2021] That was when a group of government officials and activists decided to take the question to a new online discussion platform called vTaiwan. Starting in early March 2016, about 450 citizens went to
vtaiwan.tw, proposed solutions, and voted on them…Three years after its founding, vTaiwan hasn’t exactly taken Taiwanese politics by storm. It has been used to debate only a couple of dozen bills, and the government isn’t required to heed the outcomes of those debates (though it may be if a new law passes later this year). But the system has proved useful in finding consensus on deadlocked issues such as the alcohol sales law, and its methods are now being applied to a larger consultation platform, called Join, that’s being tried out in some local government settings.…vTaiwan relies on a hodgepodge of open-source tools for soliciting proposals, sharing information, and holding polls, but one of the key parts is Pol.is, created by Megill and a couple of friends in Seattle after the events of Occupy Wall Street and the Arab Spring in 2011. On Pol.is, a topic is put up for debate. Anyone who creates an account can post comments on the topic, and can also upvote or downvote other people’s comments.
That may sound much like any other online forum, but 2 things make Pol.is unusual. The first is that you cannot reply to comments. “If people can propose their ideas and comments but they cannot reply to each other, then it drastically reduces the motivation for trolls to troll”, Tang says. “The opposing sides had never had a chance to actually interact with each other’s ideas.”
The second is that it uses the upvotes and downvotes to generate a kind of map [using PCA/UMAP for dimensionality reduction clustering] of all the participants in the debate, clustering together people who have voted similarly. Although there may be hundreds or thousands of separate comments, like-minded groups rapidly emerge in this voting map, showing where there are divides and where there is consensus. People then naturally try to draft comments that will win votes from both sides of a divide, gradually eliminating the gaps.
“The visualization is very, very helpful”, Tang says. “If you show people the face of the crowd, and if you take away the reply button, then people stop wasting time on the divisive statements.”
In one of the platform’s early successes, for example, the topic at issue was how to regulate the ride-hailing company Uber, which had—as in many places around the world—run into fierce opposition from local taxi drivers. As new people joined the online debate, they were shown and asked to vote on comments that ranged from calls to ban Uber or subject it to strict regulation, to calls to let the market decide, to more general statements such as “I think that Uber is a business model that can create flexible jobs.”
Within a few days, the voting had coalesced to define 2 groups, one pro-Uber and one, about twice as large, anti-Uber. But then the magic happened: as the groups sought to attract more supporters, their members started posting comments on matters that everyone could agree were important, such as rider safety and liability insurance. Gradually, they refined them to garner more votes. The end result was a set of 7 comments that enjoyed almost universal approval, containing such recommendations as “The government should set up a fair regulatory regime”, “Private passenger vehicles should be registered”, and “It should be permissible for a for-hire driver to join multiple fleets and platforms.” The divide between pro-Uber and anti-Uber camps had been replaced by consensus on how to create a level playing field for Uber and the taxi firms, protect consumers, and create more competition. Tang herself took those suggestions into face-to-face talks with Uber, the taxi drivers, and experts, which led the government to adopt new regulations along the lines vTaiwan had produced.
Jason Hsu, a former activist, and now an opposition legislator, helped bring the vTaiwan platform into being. He says its big flaw is that the government is not required to heed the discussions taking place there. vTaiwan’s website boasts that as of August 2018, it had been used in 26 cases, with 80% resulting in “decisive government action.” As well as inspiring regulations for Uber and for online alcohol sales, it has led to an act that creates a “fintech sandbox”, a space for small-scale technological experiments within Taiwan’s otherwise tightly regulated financial system.
“It’s all solving the same problem: essentially saying, ‘What if we’re talking about things that are emergent, [for which] there are only a handful of early adopters?’” Tang says. “That’s the basic problem we were solving at the very beginning with vTaiwan.”