Way back in April 2017, the Good Law Pro- ject announced that it was going to take on HMRC’s failure to assess Uber to VAT which corroded public trust, not only in HMRC, but in politics more generally. And it has turned out to be quite a battle for the not-for-profit membership organi- sation that uses the law to protect the interests of the public. There have been lows for the organisation, which challenges abuses of power, exploitation, inequality, and injustice; such as spending the money raised in a crowdfunder try- ing to get a protective costs order and failing. There have also been highs when it persuaded the High Court late last year that a fairly spineless HMRC was allowed to do what the legislation plainly allowed it to do and and then finally assess Uber. There have been further lows – as in recently when the Court of Appeal refused permission for the Good Law Project to bring a judi- cial review against HMRC. But ultimately it has succeeded as Uber’s US accounts now confirm that HMRC has assessed Uber to VAT on fares – both prospectively and retrospectively. It’s been a long, bumpy and expensive ride for the organisation but it has reached its destination and finally forced HMRC, belatedly, to act. Uber has now been asked to pay the £1.5bn of tax owed to the public purse.


Uber is set to change the way its drivers charge for trips. Many customers will be used to opening up the app, selecting their destination and being given an estimated price for their journey. But from 5 October, customers will no longer see an estimated price range. Instead a fixed price will be shown at the time of the request. Uber says the upfront price is based on the best available route between the pickup and drop off locations entered before requesting the trip. They add that the update will provide its customers with clearer, simpler and more transparent pricing for every trip. The upfront price will only not apply in four situations: • If the rider adds or deletes a stop in their app. • If the final destination is more than 1 mile away from the initially requested destination in a straight line (not distance travelled) – this can result in the actual fare being higher or lower than the upfront price.

• If a detour is taken and the trip is both further and slower than ini- tially estimated in the upfront price, this will result in the actual fare being higher than the upfront price.

• If the trip is at least 40% and ten minutes slower in duration than initially estimated in the upfront price (for eg. due to traffic or long stops), this will result in the actual fare being higher than the upfront price.

The upfront price also won’t apply if the journey changes due to extra stops being added or removed.



Uber is facing a new legal challenge as the App Drivers & Couriers Union filed a complaint on 26 October in the Amsterdam District Court, claiming that four drivers in the UK and Portugal were unfair- ly dismissed by the platform’s algorithm. According to Sifted, the drivers say they were wrongly accused of “fraudulent activity”, which was detected automatically by Uber’s systems, and were kicked off the platform without a right of appeal. All of the drivers deny engaging in fraud, while saying Uber has made no such complaint to local police forces. On Uber’s community guidelines page, fraudulent activities include “actions intended to disrupt or manipulate the normal functioning of the Uber apps”, and “abusing promotions and/or not using them for their intended purpose.” James Farrar, director of Worker Info Exchange, a non-profit organ- isation supporting workers in the digital economy, told Sifted he believes drivers are being penalised under these terms for declining rides and waiting for higher surge pricing times to log back in. “Uber, not ironically, calls such behaviour ‘gaming the surge’. Appar- ently, only Uber is allowed to ‘game the surge’,” he says. If true, penalising drivers for choosing when they wish to drive for Uber would seriously undermine the argument that gig economy workers benefit from the flexibility of choosing their own hours. Farrar believes this is the first case challenging the practice of so-called “robo-firing”, and the first to test Article 22 of the EU General Data Protection Regulation (GDPR) which states that individuals should be protected from automated decisions which have negative effects, and are carried out without human intervention. The App Drivers & Couriers Union describes the four reasons for supposed unfair dismissal as follows: Driver 1: “irregular trips associated with fraudulent activities” Driver 2: “the installation of and use of software which has the intention and effect of manipulating the Driver App”

Driver 3: “a continued pattern of improper use of the Uber applica- tion…..& this created a poor experience for all parties”

Driver 4: “the recurrent practice of irregular activities during use of the Uber App.”

Yaseen Aslam, president of the App Drivers & Couriers Union, announcing the legal challenge, says that the case is the latest exam- ple of Uber exploiting its fleet of riders. “Uber has been allowed to violate employment law with impunity for years and now we are see- ing a glimpse into an Orwellian world where workers have no rights and are managed by a machine. If Uber [is] not checked, this prac- tice will become the norm for everyone,” he argues. The union has launched a crowdfunding campaign to help fund the legal challenge. Uber has responded saying that these decisions “were not taken solely on the basis of automated processing of personal data”, as the drivers’ “irregular activities” were assessed by Uber employees. Anton Ekker, the attorney leading the case in the Netherlands, says that there is no evidence that an adequately trained employee was involved in the human assessment of the dismissals. The case will likely be decided on just how “meaningful” the human intervention from Uber’s side was in these dismissals; in short, whether it was really the algorithm responsible for the dismissal. Uber’s privacy notice includes the following text, suggesting that drivers can be fired automatically: “We use personal data to make automated decisions relating to use of our services. This includes: […]Deactivating users who are identified as having engaged in fraud or activities that may other- wise harm Uber, its users, and others. In some cases, such as when a user is determined to be abusing Uber’s referral programme, such behavior may result in automatic deactivation.”


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