How Taiwan settled its Uber fight online
The Consensus Was Already There: How Taiwan Settled Its Fight Over Uber
In 2015, Taiwan was having the same fight over Uber that was breaking out everywhere. The ride-hailing app had arrived, drivers were signing up, and the established taxi trade was furious, with some drivers reporting they had lost as much as a third of their income. Passengers and regulators worried about safety, since an UberX driver needed no professional license. The government, for its part, wanted nothing to do with any of it. To the transport ministry, Uber's drivers looked like lawbreakers. The economic-affairs ministry did not consider the company to be e-commerce. Nobody was sure which rules applied, or whether any did. It was the sort of dispute that usually ends in a lawsuit, a deadlock, or a deal struck out of public view.
What Taiwan did instead grew out of something that had happened the year before. In 2014, a wave of protest known as the Sunflower Movement, which included a weeks-long occupation of the national legislature, ended with a demand that the government get better at listening to the people it claimed to represent. In response, officials turned to a community of civic-minded programmers called g0v, or gov-zero, and asked them to build a way to consult the public at scale on contested national questions. The result was a process called vTaiwan, which moves an issue through a sequence of online and offline stages toward what its designers, borrowing a phrase from engineering, call rough consensus. At the center of it sat a listening tool called Polis. The Uber question became its first real test.
Polis does not work like a comment thread, where the angriest posts rise and everyone hardens. Participants wrote short statements about ride-hailing and voted agree, disagree, or pass on each other's. The software sorted people according to how they voted and pushed forward the statements that drew support from across the different camps. Tens of thousands of votes came in. And as the picture filled out, the thing that keeps happening in these processes happened again. Underneath the noise, a broad agreement surfaced that had been there the whole time. Strip away the shouting and almost everyone wanted the same two things, that passengers be kept safe and that the field between Uber and the taxis be level. People even began to rewrite the questions. Rather than argue about whether drunk drivers should be punished more harshly, they started asking how to prevent drunk driving in the first place. The agreements that emerged were specific and unglamorous. Ride apps should not undercut existing minimum fares. App-based services should pick up only passengers who had booked through the app, rather than hailing them off the street like a cab.
The transport ministry committed to act on what came out of the process, and the government went on to write rules shaped by it. The same approach was then used again, on the online sale of alcohol, on short-term rentals, on a sandbox for small financial experiments. By 2018, vTaiwan's organizers could point to more than two dozen cases run this way, most of which had led to concrete government action.
It would be easy to take this as proof that the right software can dissolve a political fight, and that is not quite what happened. The platform did not create the agreement. It revealed an agreement that the public form of the argument had buried. That is a real and useful thing to be able to do, but it is a different thing, and the difference becomes obvious the moment you ask why the method sometimes led nowhere. vTaiwan has been criticized, including by people inside the Taiwanese government, as "a tiger without teeth." Where officials chose not to follow through, a beautifully mapped consensus simply sat there and did nothing. This is not a defect in the tool. It is a fact about how power works. A process that finds common ground is only ever as strong as the willingness of the people in charge to be bound by what it finds. The cleverness is in surfacing the agreement. The decision to act on it belongs to institutions, and no interface can make that decision for them.
That leaves a more honest lesson than the one about software saving democracy, and a more useful one. In most bitter disputes there is more common ground than the dispute lets anyone see, and it is now genuinely possible to go and find it. Whether finding it changes anything is a separate matter, and it turns on institutions rather than interfaces. Taiwan's experiment is worth studying because, often enough, the institutions chose to act.
For the same pattern at the scale of a single town, see what a divided Kentucky city found when it looked at itself.
Sources and further reading: MIT Technology Review, The simple but ingenious system Taiwan uses to crowdsource its laws (https://www.technologyreview.com/2018/08/21/240284/the-simple-but-ingenious-system-taiwan-uses-to-crowdsource-its-laws/); the Computational Democracy Project's vTaiwan case study (https://compdemocracy.org/case-studies/2014-vtaiwan/); Democracy Technologies, Lessons From Consensus Building in Taiwan (https://democracy-technologies.org/participation/consensus-building-in-taiwan/); and the vTaiwan project site (https://info.vtaiwan.tw/).