Transportation and HCI #chi4good, CHI 2016, San Jose, CA, USA Peer-to-peer in the Workplace: A View from the Road Syed Ishtiaque Ahmed Nicola J. Bidwell Himanshu Zade Srihari H. Muralid- Cornell University U. of Namibia U. of Pretoria Microsoft har Ithaca, USA Windhoek, Namibia South Africa Bangalore, India IIT Madras [email protected] [email protected] [email protected] Tamil Nadu, India [email protected] Anupama Dhareshwar Baneen Karachiwala Tandong N. Cedrick Jacki O’Neill P.E.S.I.T Independent Consultant, Three Wheels United Microsoft Bangalore, India Bangalore, India Bangalore, India Bangalore, India [email protected] [email protected] [email protected] [email protected] ABSTRACT economy [2,38,58]. Whilst all use P2P architectures, these This paper contributes to the growing literature on peer-to- groups include diverse sets of practices involving ex- peer (P2P) applications through an ethnographic study of changing varied resources, for monetary or non-monetary auto-rickshaw drivers in Bengaluru, India. We describe gain, and for employment or not. We are interested in the how the adoption of a P2P application, Ola, which connects use of peer services in the workplace and in this paper ex- passengers to rickshaws, changes drivers work practices. amine Ola Auto, an implementation to connect customers Ola is part of the ‘peer services’ phenomenon which enable and auto-rickshaw (auto) drivers. Olacabs, an Indian start- new types of ad-hoc trade in labour, skills and goods. Auto- up, added Ola Auto (or Ola) to its taxi-booking services in rickshaw drivers present an interesting case because prior to November 2014. Like Uber its closest competitor, Olacabs Ola few had used Smartphones or the Internet. Furthermore, does not own taxis or autos but links customers to owner- as financially vulnerable workers in the informal sector, drivers for specific trips with P2P technology, similar to concerns about driver welfare become prominent. Whilst apps that enable ride-sharing. technologies may promise to improve livelihoods, they do not necessarily deliver [57]. We describe how Ola does lit- We conducted an ethnographic study of auto drivers in tle to change the uncertainty which characterizes an auto Bengaluru, India. By focusing on their adoption of Ola, we drivers’ day. This leads us to consider how a more equitable aim to understand where and how the app impacts auto- and inclusive system might be designed. driving for the purposes of design. HCI has long been inter- ested in the impact of new technologies on work-practices Author Keywords [7,8,25,54]. Introducing technology changes existing prac- Workplace studies; ethnography; P2P technology; auto- tices and typically brings both benefits and disruptions [e.g. rickshaws; peer services; peer economy; ridesharing, ICTD 7,10,25]. By examining in detail how the work is achieved ACM Classification Keywords in, and through, people’s actions and interactions with tech- H.5.m. Information interfaces and presentation (e.g., HCI), nology and one another, workplace studies draw attention H.5.3 Group and Organization Interfaces, Collaborative to the knowledge and skills of workers [49,50,55]. Such Computing, K.4.3 Organizational Impacts studies open up spaces for (re)designing technology to bet- ter support that work [9,5,15,45]. INTRODUCTION The recent proliferation of ‘peer services’ has enabled new We focus on how drivers use P2P technology as part of types of ad-hoc trade in labour, skills, knowledge and mate- their work. What makes this setting unique is that auto- rial goods [e.g. 26,53,31,2] using web and mobile rickshaw drivers in India have had little exposure to com- technologies with peer-to-peer (P2P) architectures. Services puting technologies, such as the smartphones on which Ola range from hospitality [26] to lending a helping hand [53] runs. For most drivers using Ola was their first use of to transportation [34,32] and are often, collectively, called smartphones and the first and only way they accessed the the ‘gig’, ‘alternative’, ‘collaborative’, ‘peer’ or ‘sharing’ Internet. Furthermore drivers are classified as urban poor [40], working in the informal sector [13], which means their Permission to make digital or hard copies of all or part of this work for personal welfare is an important concern when introducing new or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice technologies. Autos provide 13% of the city’s total trips and the full citation on the first page. Copyrights for components of this work [59], and auto-driving is the source of livelihood for ap- owned by others than the author(s) must be honored. Abstracting with credit is proximately 125,000 drivers and their families in Bengaluru permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions alone. Many people who travel by auto also do not use from [email protected]. smartphones, that is the technology is not yet pervasive CHI'16, May 07 - 12, 2016, San Jose, CA, USA among drivers or their passengers. In this study we ob- Copyright is held by the owner/author(s). Publication rights licensed to ACM. ACM 978-1-4503-3362-7/16/05 $15.00 served both drivers who had and had not adopted Ola to DOI: http://dx.doi.org/10.1145/2858036.2858393 understand how Ola was changing existing practice. As far 5063 Transportation and HCI #chi4good, CHI 2016, San Jose, CA, USA as we are aware this is the first study of this type of peer [24], technologies can induce various innovative practices service for work outside of the Global North. amongst drivers. Drivers in Barcelona, for instance, ac- quired a “Satnav literacy” in mastering skills to interpret, Olacabs, like Uber, acts as a ‘Digital Middleman’ [28] to assess and tackle the varying accuracy of GPS information connect customers and drivers through the algorithms, net- [22]. GPS modified only part of drivers’ practices and, works and data they control. They set fares, receive ride while transforming practices in learning, lost usefulness requests, offer and assign rides to drivers, and use real-time when drivers were familiar with areas [22]. Indeed, in New and historical data to manage assignment and, possibly, York drivers tuned their use of Uber and Lyft’s ridesharing payment rates. The distribution of computing at the driver apps to accommodate their local knowledge [32]. Mean- and customer ends of the P2P architecture is limited to re- while, in Singapore, a GPS-enabled taxi-dispatch system questing, accepting, paying for and rating rides. Whilst the obliged drivers to move beyond their former geographic introduction of new technology into such a setting might haunts and gain new temporal and spatial knowledge [24]. offer hope in improving livelihoods, it also brings concerns. This enabled some to reach places unknown to other driv- New technology can create new poorly paid and unregulat- ers, and some to gain insights about precise ‘hot-spots’ to ed markets [20,27,6,11] and various ICTD studies show ‘capture’, not wait for, customers. that technology deployments in developing countries often fail to produce sustained positive changes in the life of vul- Just as GPS-enabled systems change, rather than eliminate, nerable populations (see [57] for an extensive list). Our wayfinding skills, they can change social skills [22,33]. Not study enables examining the impact of a P2P transportation needing to ask for route information can limit drivers’ con- platform on the auto drivers’ work. We found that drivers versations with passengers, colleagues and locals [22]. On use Ola alongside their usual methods to find passengers the other hand, drivers used GPS-enabled systems as guides and, despite incentives, do not prioritize Ola over traditional to places where there are interesting customers to talk with passengers. Ola introduces new elements of competition [24] and to propose alternate routes for customers to choose and evaluation, but does little to change the uncertainty from to avoid complaints [22]. Meanwhile, Lyft and Uber’s characterizing an auto drivers’ day. These insights prompt- ridesharing apps provoked social interactions, online and in ed us to consider redesign of the system, to better support streets, to reduce the effects of algorithmic ‘errors’ [32]. drivers’ expertise, literacies and skills, and how P2P archi- Technologies for the workers tectures might be used in optimal mediation to benefit all Designing workplace technologies to be inclusive is not actors - drivers, customers and digital middlemen. We are simple. Consider how Uber or Lyft drivers with more tech- motivated by a view, held by the original P2P movement, nical expertise and social capital often benefited most from that superior solutions involving diverse peers can be collaboratively tackling issues arising due to the ridesharing achieved provided there is a sense of fairness in distributing app’s algorithms [32]. Consider also how drivers with most resources [41]. Here, we orient our in-depth understanding knowledge about a dispatch systems’ functionality earned of work practices, with and without Ola, towards new de- highest incomes and had lower costs and those with less sign ideas for a more equitable and inclusive system. knowledge worked longer hours or maintained only a basic RELATED WORK income [24]. Indeed, the competitive pressure that the sys- tem induced constrained some drivers, who were older, Workplace technologies in the transportation sector Peer services that link passengers to drivers join a range of could not read the system’s texts easily, were disturbed by computer technologies in the transport industry, and add to it, and only used the system in a perfunctory way.