Uber has reported a number of issues recently, from its CEO Travis Kalanick beratingone of its drivers and another exec resigning due to differences in “beliefs and approaches to leadership,” to accusations of what appears to be institutional sexism.
Yesterday, it released a report on its workforce entitled “Measuring What Matters: Diversity at Uber,” which revealed that there’s no diversity at the company. Liane Hornsey, its HR chief, has been promised unlimited resources to fix a culture variously described as cutthroat, political, aggressive, and intensely masculine.
In other words, it has a people problem.
Isn’t that the one thing its app fixes?
Think about it. The rocket science behind Uber isn’t its technology — the platform is a glorified calendar program — but rather the problem it solves: Efficiently matching drivers with riders.
To accomplish it, the app takes the variability of supply, location, scheduling, routing, and payment out of the equation. Its technology determines the most efficient way to actualize the intent of the human beings it pushes from here to there, whether as suppliers or customers. Behaviors that were once the purview of people are accomplished by the push of a button instead.
In fact, it reportedly wants to take human beings out of its supply chain entirely, replacing them with automated cars.
That’s the sad promise of tech these days; since people are so biased and imperfect, we prefer to let technology make decisions (humanity’s control over its own fate, however demonstrably imperfect, is what’s getting disrupted). A smartphone chip already “knows” more than most voters in America, and the reason and reliability of big data analyses follows logic rules that folks would find inscrutable when compared with their irrational, desperately flawed thinking.
It’s easier to trust tech because it’s gotten so hard to trust one another.
So why not use it to do for Uber’s employees what it does for its drivers and riders?
The technology already exists, as many decisions in a wide variety of industries are already made by computer. Supply chains have been getting optimized via operational controls for decades, and software can now do it automatically. Marketing expenditures can be allocated via complex ROI models that require no human judgement. Investment decisions, legal actions, and other risky moves are regularly analyzed with deep probability models.
If big data can determine what brand of toothpaste a website visitor would prefer, couldn’t it run a company?
It would solve Uber’s problems in an instant.
The app could be coded based on the board’s requirements and priorities, each expectation reduced to a statistical expression of desirability and ranked by importance. Company functions, from overall activities to the specifics of individual employee performance, could also be digitized, providing a mechanism for allocating resources against needs. Heck, it already uses algorithms to calculate pricing, among other core company activities.
Want to employ a more diverse workforce? Let a neuter app judge applicants, and then skip relying on a potentially sexist staffer and let it identify the right people for any task (as well as schedule and manage projects, along with recognizing and rewarding performance). Don’t like the way a fellow worker behaves? Rate them, just like Uber drivers and riders do.
More broadly, every new company strategy could be measured against those baseline requirements and priorities, and the app could yield a dashboard’s worth of likely risks and benefits (in percentages expressed with digital clarity).
Somebody wants to run a ghost program to confound regulators and journalists? The app might reveal that the risks outweigh the benefits, so no. Should Uber expand service to a city with a few thousand residents, or buy automated vehicles from one manufacturer or another? The app could make those decisions, too.
Better yet, why not simply enter a desired a desired profit margin and time horizon, and trust a gaggle of algorithms to calculate the best management choices to get there; in this way, it could entirely replace the need for human leadership, so the founder wouldn’t have to figure out how to grow up, but simply learn to give up control to Colossus.
Once that was accomplished, Uber could replace its employees with programmable robots, just like it hopes to do to its drivers. Then it could run entirely without bias, imperfection, or pause.
All it needs is the app.