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2018 | OriginalPaper | Chapter

6. Assessment by Feedback in the On-demand Era

Author : Alessandra Ingrao

Published in: Working in Digital and Smart Organizations

Publisher: Springer International Publishing

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Abstract

Feedback systems are software algorithms used by “gig economy platforms” to collect and process personal data of workers. The data track allows platforms not only to optimize human jobs but also to monitor and evaluate the performance of each worker. This chapter explores how ridesharing platform services, such as Uber, control the way of execution of drivers’ work. The implications of use of feedback system involve not only the issue of qualification of workers as employees but also the new measures of protection which could be implemented to enhance the requirements of European General Data Protection Regulation in the field of “Automated individual decision making, including profiling” and the “right to data portability”.

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Footnotes
1
The first judicial cases were American. Many administrative bodies have concluded for the existence of form of employment, using the right to control test and the economic reality test: US Labor Commissioner of the State of California, O’Connor v. Uber Technologies Inc., n. C-13-3826, EMC, 2015; Id., Berwick v. Uber Technologies, Inc., C-11-46,739 EK, 2015; Bureau of Labour and Industries of Oregon, Advisory Opinion, 14 Oct. 2015; the Department of Labour and Workforce Development, Alaska, 3 Sept. 2015, with which Uber is obliged to pay employee contributions to the State; United States District Court for the District of Columbia, Erik Search v. Uber Technologies Inc., Defendants Civil Action n. 15–257 (JEB), in a case of civil liability. After that, two Brazilian courts reached the conclusion that Uber drivers are employees because they receive by Uber detailed instruction and are subjected to algorithmic control: Tribunal Regional do Trabalho da 03a Região, 33a Vara do Trabalho de Belo Horizonte, Brazil, 13 Feb. 2017, n. 2534b89 and Tribunal Regional do Trabalho da 2ª Região, 13a Vara do Trabalho de São Paulo, 20 April 2017, n. e852624; contra Tribunal Regional do Trabalho da 03a Região, 09a Turma, Minas Gerais, Brazil, 23 May 2017, n.75181a9. After that, in Switzerland, the National Institute of Social Security, Suva (http://​www.​cdt.​ch/​svizzera/​cronaca/​169480/​uber-deve-pagare-i-contributi-sociali, 5 Jan. 2017) stated that Uber drivers are employees because the platform is not a simple tool that connects customers seeking driving services, but it acts like an employer. Finally, it is crucial to mention the decision of the London Employment Tribunal, 28 Oct. 2016, Aslam, Farrar e a. v Uber, c. 2,202,551, Dir. rel. Ind., 2017, 2, commented by D. Cabrelli. The judge stated that Uber riders are “workers” and not employees, and so they have right to minimum wage and working time, because they aren’t under any obligation to switch on the Application or, even if logged on, to accept any driving assignment that may be offered to them and stated that “these freedoms” are incompatible with the existence of an employment relationship.
 
2
General condition of Uber contract stated: “Star Ratings. After every trip, drivers and riders rate each other on a five-star scale and give feedback on how the trip went. This two-way system holds everyone accountable for their own behaviour. Accountability helps create a respectful, safe environment for riders and drivers. Drivers can see their current rating in the Ratings tab of the Uber Partner app.
How is my rating as a driver calculated? Your rating is based on an average of the number of post-trip stars riders gave you (from 1 to 5 stars). In the Partner app, you’ll see your rating as an average of the last 500 rated trips, or the total number of rated trips you’ve taken if less than 500.
The easiest way to keep your average rating high is to provide good service on every trip. Drivers on the Uber platform provide excellent service, so most trips run smoothly. But we know that sometimes a trip doesn’t go well, which is why we only ever consider an average of many ratings when calculating your rating instead of individual trips.
What leads to deactivation? There is a minimum average rating in each city. This is because there are cultural differences in the way people in different cities rate each other. We will alert you by email and text message if your rating is approaching this limit.
We check your rating after every 50 rated trips, so that we can let you know as early as possible if you are approaching this limit and provide you with any support you might need to improve your rating, like tips from our top-rated partner-drivers.
If you are a new driver and your rating falls below the minimum in your first 50 trips, we will invite you to participate in a quality session for further support, either online or in person at the Uber office.
If your average rating still falls below the minimum after multiple notifications after a 50 trip period, your account will be reviewed and may in some cases be deactivated”.
 
3
London Employment Tribunal, 28 Oct. 2016, cit. The judge makes a very detailed analysis of the operation of feedback system in the chapter called “Instruction, management and control or preserving the integrity of the platform?”. He describes the way in which Uber instructs drivers to ensure a satisfactory “rider experience” to the customers. Uber gives a “Welcome packet” to each driver containing material, including “5 Star tips” that explain “What riders like” and “What Uber Looks For”. Then Uber uses the rating system as a tool to exercise control over drivers and their behaviour.
 
4
Tribunal Regional do Trabalho da 03a Região, 33a Vara do Trabalho de Belo Horizonte, in which Judge Filipe de Souza Sickert explains that technological power of the gig economy platform has been dramatically exaggerated.
 
5
O’Connor v. Uber Technologies, Inc. et al., C13–3826 EMC.
 
6
Compare, College van Berop voor het bedrijfsleven (Paesi Bassi), 8 Dec. 2014, AWB 14/726, ECLI:NL:CBB:2014:450; Trib. Milano, 2 July 2015, n. 35,445 e 36,491, Riv. it. dir. Lav., 2016, II, commented by A. Donini; London Employment Tribunal, 28 Oct. 2016, cit.; Audiencia Provincial de Madrid, 23 Jan. 2017, n. 15, Trib. Torino, sez. I civ., 24 March 2017 n. 1553, Trib. Roma, sez. IX, 7 April 2017, n. 76,465; Juzgado de lo Mercantil di Barcellona, 7 Aug. 2015 n. 3;
 
7
ECJ, c-434/2015, Asociación Profesional Elite Taxi/Uber Systems Spain.
 
8
Working Party ex art. 29, opinion no. 4/2007;
 
9
It’s very interesting the Italian case law about the civil liability of intermediaries like TripAdvisor that comes from fake reviews: Trib. Rimini, 7 May 2013, Dir. informazione e informatica, 3, 2013, 382–389. See also decision of Authority for Communications Guarantees, 22 Dec. 2014, proc. PS9345 “TripAdvisor—false recensioni online”, with which the Authority impose a fine of 500,000 euros to the Platform because it hasn’t an appropriate control system against “fake reviews”. The sanction has been cancelled by the Administrative Court, Tar Lazio, sez. I, 13 July 2015 no. 9355, because TripAdvisor cannot be held responsible for a misleading business practice because the deceit is not relevant enough.
 
10
Italian Data Protection Authority, decision no. 488 del, 24 Nov. 2016, [doc. Web n. 5,796,783], “Piattaforma web per l’elaborazione di profili reputazionali”. Compare also Italian Data Protection Authority, Newsletter no. 423 del, 28 Dec. 2016, “No all’algoritmo della reputazione, viola la dignità della persona”.
 
11
Compare, Article 29 Data Protection Working Party, Guideline on the right to data portability, adopted on 13 Dec. 2016.
 
12
Article 29 Data Protection Working Party, Guideline, cit. 7. They provide the example of telephone records which may include details of other people, especially parties involved in incoming and outgoing calls. In this case pursuant to Opinion of Article 29, the data subject has the right to transmit data from one controller to another one.
 
13
Compare Article 29 Data Protection Working Party, Guideline, cit. 8, which states “For example a credit score or the outcome of an assessment regarding the health of a user is a typical example of inferred data”.
 
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Metadata
Title
Assessment by Feedback in the On-demand Era
Author
Alessandra Ingrao
Copyright Year
2018
DOI
https://doi.org/10.1007/978-3-319-77329-2_6