Uber responds to vTaiwan’s coherent blended volition

On August 27, 2015, I served as a co-facilitator on the 7th vTaiwan e-Rulemaking public consultation meeting, alongside Minister Jaclyn Tsai.

Modeled after Cornell’s RegulationRoom, vTaiwan is a g0v (gov-zero) project run by volunteers that works with the Taiwan administration on crowdsourcing internet-related regulations.

This time, participants crowd-sourced our meeting agenda via 4 weeks of public survey on Pol.is, complete with Uber’s own analysis on the raw data.

1,875 online participants joined us during the two-hour live-streamed meeting with academics, industry experts, and representatives from four stakeholders:

• Association of Taxi Drivers in Taipei — the main city in which UberX operate;
• Taiwan Taxi — the country’s foremost taxi fleet;
• Uber Inc. — from which over USD$1M has been exacted in penalty for its illegal operations with unregistered cars;
• The Ministries of Transport, Economic Affairs, and Finance.

All stakeholders displayed a remarkable willingness to cooperate and work with each other, as evidenced by the transcript. Notably, they made the following concessions:

• Uber agreed to provide its international liability insurance policy to Minister Tsai and, if needed, release it for public review.
• Uber agreed to coach all drivers to register and obtain professional driver’s licenses.
• If legalized in some areas, Uber is willing to pay for UberX car permits, as well as transport taxes.
• The Taipei Taxi Association also expressed a willingness to work with the UberTAXI platform under mutually-agreeable terms.
• The Taiwan Taxi Fleet promised to offer better services, if taxi pricing can increase in response to market demands.

People from the Ministry of Transport also developed considerable empathy with stakeholders. When the Taipei High Administrative Court rejected Uber’s appeal on the fines and injunction order, two weeks after the vTaiwan meeting, the Ministry’s press release stated:

We are grieved for and pity them; we do not feel joy at our own ability.

(The quote is notable for its preceding text in the original Confucian Analects: The rulers have failed in their duties, and the people consequently have been disorganized, for a long time. When we have found out the truth from any accusation…)

While policymakers and supreme court justices continue to work with the deliberation results, let’s take a look at how Pol.is encouraged people to communicate their feelings effectively.

Focusing on Coherence

Designed for car drivers and passengers with mobile phones, the initial screen of our Pol.is survey shows just one statement, placing the participant among several groups of people:

As the participant clicks — Agree or Disagree, their avatar moves toward a group with similar feelings, and the next statement shows up; everyone can contribute any number of statements for others to vote on.

For the UberX survey, we asked everyone to begin their statements with “My feeling is…” — and everyone can respond to each other by sharing their feelings in return.

We sent all stakeholders the Pol.is survey’s URL at the same predetermined time, to ensure a balanced diversity of participants. Four broad groups of people soon emerged: Taxi drivers, Uber drivers, Uber passengers, and other passengers.

During the first few days, people shared strong feelings that appealed other groups close by. The four groups quickly merged into two, with Group 1 (45%) identifying with the following statement:

Since the Ministry has already rejected Uber’s administrative appeal, I think Taipei city government should cancel the company registration of “Taiwan Uber Inc.” [75%]

Group 2 took a completely different side:

When I am not in a hurry, I prefer to call Uber even if there are plenty of taxis in the street. [77%]

Note that 75% of Group 1 amounts to just 33% of total participants, meaning there were more people disagreeing with the two statements above than people who agreed.

Because Pol.is displays statements with the most support first, participants brainstormed on statements that appeal to more people. A week later, Group 1 toned down the original statement somewhat:

I think it is the responsibility of the Ministry to actively outlaw unlicensed passenger vehicles. [87%]

Group 2, meanwhile, gained a two percent increase from 54% to 56% under this statement, which garnered cross-group acceptance:

Currently, the only way for traditional taxis to survive is to join a taxi fleet. This is not due to a government policy, and UberX has subverted this unwritten rule. I think it is quite awesome! [93%]

Pol.is shows each group how much their shared sentiments are received by other groups, thereby encouraging participants to contribute ever more inclusive statements that show up in the “Majority Opinion” tab, such as this one by Irvin Chen:

The government should leverage this opportunity to challenge the taxi industry to improve their management & quality control system, so that drivers & riders would enjoy the same quality service as Uber. (95%, across all groups)

By the fourth week, participants have contributed a coherent set of reflections, expectations and suggestions, successfully forming a coherent agenda for stakeholders to respond to.

Blending Volition

Think of a blender filled with hard fruits — rockmelons and pineapples — but no water. Turn on the blender. The temperature will rise, and violent confrontations between solid surfaces may even start a fire! That is what may happen in a debate of stakeholders when interests are in conflict with each other.

Considering the risks involved, the vTaiwan rulemaking process aims for coherence (rough consensus), not convergence (coordinated consensus). Our thinking is based on the four-stage focused conversation model:

1. Objective: Facts — “What do we know?”
2. Reflective: Feelings — “What are our reactions?”
3. Interpretative: Ideas — “What insights do we get?”
4. Decisional: Actions — “What should we do?”

This model works best when a group fully explore all aspects of each stage, before moving on to the next. Therefore, we presented the objective facts with a Wikipedia timeline, followed by four weeks of an online Pol.is survey on the reflective stage — people’s feelings. The subsequent stakeholder meeting was then able to concentrate on interpretations, making the most of the face-to-face time.

We also took care to focus on the stakes — regulations and policies — instead of stakeholders themselves. Returning to the blender metaphor, this is like dicing each fruit to bite-sized pieces before putting them into a blender. For example, instead of deliberating on “Uber” as a whole, we focused on the practice of private passenger cars for-hire which reduced the surface friction.

Moreover, we can add some water, creating nonviolent medium to reduce friction, while maintaining the same transparency as before. This is akin to the reflective space that Pol.is offers, where people can see each other’s feelings, and change their positions by reacting to new statements.

As we can see from the result, Pol.is was indeed an effective blender of people’s feelings about Uber.

Following on this successful pilot, the crowd-sourced Pol.is agenda setting for Airbnb regulations and Internet liquor sales were both resounding successes, arriving at workable consensus that are upheld by all sides.

Postscript

On May 23, 2016, the Administration pledged to ratify all the Pol.is consensus items into a new regulation:

• Taxis no longer need to be painted yellow.
• High-end app-based Taxis are free to operate, as long as they don’t undercut existing meters.
• App-based dispatch systems must display car and driver identification, estimated fare, and customer rating.
• Per-ride taxation is required to report to the Ministry of Finance.

With this regulation, other Uber-like apps, some created by the civil society, are entering the market.