DiDi Ridesharing CTO Emphasizes a Balance of Technology and Human Values
During a conversation with Pandaily’s DecodeChina cohort, Didi Chuxing’s CTO of their ride-hailing business, Tiger Qie, spoke about the company’s commitment to infusing human values into what is inherently a technology company.
While Didi’s success and the key competencies rely on extremely robust fundamental technologies, every transaction on the platform involves real human beings and has real world implications.
Qie began by explaining many of the ways in which Didi optimizes their ride-hailing platforms both for drivers and riders. One of the highlights was the importance of the recommended pick-up points, represented by green dots on the map when a user opens the app and requests a ride. Rendezvousing with the driver was identified as one of the main pain points for riders using Didi, and the recommended pick-up points are meant to solve this inconvenience. Over 70% of rides on the platform originate from one of these recommended pick-up points.
Qie also talked about the various factors around the efficient repositioning of Didi drivers in between completing trips. Didi uses an incentive-based model combined with a heat map to try to position drivers in areas that will allow them to efficiently complete more trips per day, and these efforts have increased the total trips completed on the platform by 5%.
SEE ALSO: Didi Chuxing Is Moving Forward With Autonomous Driving
Even though Didi’s repositioning prediction algorithms are extremely efficient, the company understands that they are not perfect, and offers drivers compensation for their cooperation with the system. For example, if the system directs a driver to a given location to increase the chances of securing a trip, but 10 minutes after arriving the driver has not found a rider, the platform will compensate him for his time spent following the systems directive. This is a humane way of blending the power of technology with conscious compassion for employees.
In addition, Qie talked about some of the ethical and moral questions the company faces. For example, should a driver have the right to refuse service to a visibly and excessively drunk passenger? Many would say yes, but what if it were very late on a really cold night? Refusing to service the passenger could result in potentially them freezing to death.
Alternatively accepting a passenger who is incapacitated and not even aware of the correct destination, or nauseous, would cause major inconvenience to the driver. This situation serves as a reminder that Didi is an application that ultimately occurs in reality and as safety is paramount, sometimes even the most robust technology requires human decision making.
Consider the amount of lost items that Didi has returned to its riders. DiDi returns nearly 100,000 items to passengers per month. Recently the platform stipulated that passengers must compensate drivers for the time required to return lost items.
This is another recognition of driver’s time as a valued resource not only to the platform but for the driver’s themselves. Instead of expecting an unwavering altruistic attitude from drivers, the platform supports the drivers to increase rider satisfaction in a way that benefits the company’s stakeholders and riders.
SEE ALSO: What Does Uber’s IPO Mean for Didi? The War for Global Mobility Dominance
This refreshingly humanist take from one of China’s most successful and exciting technology companies, displays an ability to take a step back and acknowledge the human element of technology that certain technology firms can be oblivious to ignore.
For example, considering Facebook’s recent controversies concerning real world events in Myanmar that were triggered via their social platform, Didi deserves significant plaudits for acknowledging the human aspect of their business.
Following passenger safety concerns after murder incidents in 2018, Didi has responded by significantly bolstering the safety protocols on their app, including in-trip audio recording, itinerary sharing, and abnormal route behavior detection.
