Supporting Self-Presentation of Rideshare Workers

Supporting ride-share drivers' self-presentation to riders through an automobile interface to communicate their personnel and needs.

Rideshare companies are re-shaping the form of work for millions of on-demand drivers. Many in public media and academia have discussed the impact of ridesharing in the future of work practice. One of the challenge increasingly facing rideshare drivers are the visibility of their personnel beyond just a driver. The source of some of these challenges (at least in the case of the two largest ridesharing companies, Uber and Lyft) are in how they employ and leverage algorithmic management to mediate the interactions between drivers and riders (Lee, 2015). In large part, working on these platforms requires drivers to navigate the various barriers of information asymmetries (Rosenblat, 2016), opaque algorithmic management (Wagenknecht, 2016), and emotional labor (Raval, 2016). In addition, drivers are often perceived as the “service provider”, which is not incongruent with the legal classification of “independent contractor”. Given these challenges, we see rideshare workers are facing a crisis in work visibility and relationship management between workers and consumers.

During a face-to-face interaction in a ride, riders play an important role in shaping the sharing experience of drivers which riders might not fully understand. Even for some riders who realize their potential in brightening a driver's day and tend to care about driver's experience, they don't necessarily express their compassion due to various reasons (e.g. social fear that drivers misunderstand their intention). This barrier of understanding between drivers and riders prevent the latter from practicing their good deeds and for the driver to understand and communicate their own representation while working. As a result, this may lead drivers unintentionally going extensive level to make sure riders are happy (e.g. emotional labor). Therefore, we see the opportunity in designing an automobile display interface to support drivers to actively manage and communicate their expertise (of local places), self presentation(interest, bio, prior rider testimonials etc.), and expectations of riders’ activity (being polite, keep the car clean etc.) during an interaction. This design will also help us understand how drivers' perceive and communicate their self-presentation. Through this design in allowing drivers to control and manage the content on the display, we open a space for drivers to express their needs and expertise to support drivers’ equity in the current stakeholder structure,  where private companies (such as Uber and Lyft) and riders’ interest have been designed at a higher priority (Rosenblat, 2015).

Enabled by algorithmic management, platform economy is expanding into various work sectors beyond rideshare. As increasing amount of jobs are getting mediated by matching algorithms between consumers and workers, the relationship between the two of the main stakeholder is getting much more invisible (Martin, 2014). Such invisibility and the need for worker/consumer relationship management is widely reported in many other on-demand platforms, such as Amazon Mechanical Turk (Martin, 2014) and Airbnb (Edelman, 2014). Therefore, the display interface can be widely adopted to support these platform workers, where they can effectively express and communicate their self-presentation and needs, in order to provide quality services with dignity.  

A stand alone ambient display (supported by tablet interface) within rideshare drivers' automobile is a brand new technology. We design a whole new interface based on field study of rideshare workers' work practice, personal interest and interaction experience with riders. Although rideshare apps include some drivers' information within riders' app, we deploy a physical display that's injected among the sphere of the interaction, which may passively impact the current power dynamic between drivers and riders. 

We take a human centered design approach, aiming at providing equity for workers in the work space. To accomplish this, we develop the iOS interface using xCode and deploy the tool with iPad in drivers' vehicles. From this tool, we will also capture drivers' usage data, where we learn how drivers interact with the tool, the content creation and the efficacy in providing feedback from riders.

Now - August 10th: finish development of the tool. 

Auguest 31st - September 30th: We will ask a few colleagues to pilot the tool for its usability. 

October 1st - Dec. 31st: recruit Uber/Lyft drivers and deploy the tool in their actual rides. 

Jan. 1st - Feb. 15th: We will conduct longitudinal analysis on their usage data, as well as interviewing drivers and riders who experienced the tool. 

Feb. 16th - March 15th: Based on the result, we will iterate on our design and update on the tool accordingly.

Thereafter: marketing and mass deployment.

Workers inherently have the need to present themselves, especially for service workers. In our prior interview with rideshare workers, riders would consider drivers who drives Uber because they've made bad decisions in their life. This mentality is not unique towards rideshare workers, but for many who work in an unequal power dynamic with their consumers. This tool can be adopted by other platform workers and traditional service industry with minor adjustments in fitting work practice and work setting. 

I will be recruiting drivers to use the tool from Facebook driver groups, driver forums.

The app is still in early development stage.

In 12 months, I look to serve thousands of customers, based on the marketing effort. Uber and Lyft's driver base is my target user in the long run.

We are academic researchers, through years of working with platform workers (Amazon Mechanical Turk and rideshare drivers), we gained thorough understanding of their work practice, motivation and experiences of being a gig worker. My team and I are equipped with strong social science and computer science expertise in developing tools that aim to make positive social impact.

We design a tool primarily in consideration of making a positive impact in gig workers' life without a specific revenue model in mind. We hope to develop the tool that will benefit workers, and it will be adopted by a wide audience at the end.

I believe in our tool in  making a positive impact for millions of workers and change the dynamic of future of work. Solve could be a great place for me to gain more knowledge and get feedback on my design. I would love to be part of the solve class and get in touch with more talented designers and practitioners to strengthen my design.

A good design never comes with one or two geniuses, Solve is a platform where many talented people could provide meaningful feedback in order to gain insight for design iteration. I would also love to get in touch with more people that's concerned with future of work, especially gatekeepers of worker community.