Read Case Study 3-1 Uber's Use of Technology-Mediated Control in the book and answer the question posed below:

List two Pros and Cons of Uber using technology-mediated control of its drivers through its mobile app.

Uber Technologies, founded in 2009, is a ridehailing company that leverages the cars and time of millions of drivers who are independent contractors in countries around the globe. One recent estimate by Uber Group Manager, Yuhki Yamashita, is that Uber drivers globally spend 8.5 million hours on the roaddaily. As independent contractors, Uber tells its drivers \"you can be your own boss" and set your own hours. Yet, Uber wants to control how they behave. Uber exerts this control not through human managers, but through a \"ridehail platform on a system of algorithms that serves as a virtual 'automated manager.m Drivers' work experiences are entirely mediated through a mobile app. Uber's mobile app collects data and guides the behavior of the drivers in such a way that in reality they aren't as much their own boss as they might like to be. For example, while they can work when they want, Uber's surge fare structure of charging riders more during highvolume periods motivates them to work during times that they might not otherwise choose. The app even sends algorithmically derived push notications like: \"Are you sure you want to go offline? Demand is very high in your area. Make more money, don't stop now!\" Hence, Uber uses technology to exert \"soft control" over its drivers. Uber employs a host of social scientists and data scientists to devise ways to encourage the driv ers to work longer and harder, even when it isn't financially benecial for them to do so. Using its mobile app, it has experimented with video game techniques, graphics and badges and other noncash rewards of little monetary value. The mobile app employs psychologically inuenced interventions to encourage various driver behaviors. For example, the mobile app will alert drivers that they are close to achieving an algorithmically generated income target when they try to log off. Like Netflix does when it automatically loads the next program in order to encourage bingewatching, Uber sends drivers their next fare opportunity before their current ride is over. New drivers are enticed with signing bonuses when they meet initial ride targets {e.g., completing 25 rides). To motivate drivers to complete enough rides to earn bonuses, the app periodically sends them words of encourage ment (\"You're almost halfway there, congratulations!\"). The mobile app also monitors their rides to ensure that they accept a minimum percentage of ride requests, complete a minimum number of trips, and are available for a minimum period of time in order to qualify to earn profitable hourly rates during specied periods. Uber has a blind acceptance rate policy, where drivers do not get information about the destination and pay rate for calls until after they accept them. This can mean that drivers might end up accepting rates that are unprotable for them. On the other hand, drivers risk being \"deactivated" (i.e., be suspended or removed permanently from the system) should they cancel unprotable fares. The system keeps track of the routes taken to ensure that the driver selected the most efficient route. The mobile app also captures passenger ratings of the driver on a scale of one to ve stars. Since the drivers don't have human managers per se, the passenger satisfaction ratings serve as their most signicant performance metric, along with various \"excellentservice" and \"greatconversation" badges. But how satised are the drivers themselves? Uber's driver turnover rate is highreport edly closing in on 50% within the rst year that the drivers sign up. One senior Uber official said: \"We've under-invested in the driver experience. We are now reexamining everything we do in order to rebuild that love.\