But the system benefits drivers at the passengers’ expense. The drivers’ incentive is to take people to the places offering the biggest kickbacks, but those businesses are often the least desirable. Indeed, the amount a club pays on the Kickback app seems to have an inverse relationship to its Yelp ratings: Sapphire Gentleman’s Club offers among the highest kickbacks ($80 for male taxi riders), but has many one-star reviews, whose complaints range from watered down drinks to drugging and robbery. On top of that, some clubs present customers who arrive in a cab with high cover charges to make up for the driver’s kickback.

Will replacing the human driver with an autonomous car shift the equation in the passenger’s favor? Not necessarily. It will depend on how the systems are designed, who is designing them, and how aware the users are of the potential for manipulation.

How we get from point A to point B is a process determined by numerous and often-competing interests. Some of these tensions can be seen today in the rise of algorithmic navigation apps such as Waze and Google Maps. These apps are ad-supported, so their incentive is to retain the human drivers who want to get to their destinations as easily as possible. Thus the apps reroute, for instance, from congested highways onto obscure side streets. While this speeds the users along, it also disrupts life in areas intended to be quiet, residential neighborhoods. Currently, neither the irate neighbors nor city planners have much recourse: The roads are public and the cars driven by individuals, making intricate congestion pricing and driving zones infeasible.

Cities may have more control once these algorithms are routing autonomous cars. The “driver” would now be the algorithm—or more accurately, the company that controls the algorithm. At this scale, planners could create zones of permissions and pricing for traveling on different roads, regulations that the algorithmic “driver” must obey to continue to be licensed to drive these streets. Ideally, their goal would be to fairly balance the competing needs of rich and poor, people and businesses, passengers and residents. The question of what is fair, however, is likely to be contentious. Wealthy neighborhoods could be made off-limits to all cars without resident or guest permits. Speedy scenic routes would become the business class of car travel, and the slow routes, lined with McDonald’s, dry cleaners, and other strip-mall stalwarts, the urban economy class.

The relationship among businesses, passengers, and drivers is different. Payments (whether kickbacks or sponsorships) from a business to a driver (whether human or algorithmic) in return for redirecting people are a way for businesses to align the drivers’ incentives with their own. In the case of the Las Vegas taxis, the passengers still have recourse: The drivers operate independently, and passengers are capable of directing them to a preferred location. But once independent drivers are replaced with autonomous vehicles under the control of a monolithic routing algorithm, if the company that controls the algorithm has special relationships with businesses, it can wield far more influence on where people shop and eat, on what they see—and where they do not go.