Prevailing thinking seems to indicate that email-shuffling middle managers, who do little but route work to underlings and suck up to the layer above, will soon be without a job. Super-efficient queuing-theory based algorithms such as those used by web-based businesses such as Uber, Lyft, Ola and restaurant delivery/courier websites will soon take over the function of efficiently allocating work in many other services-based organizations.

For instance, in a company that plots employees on a bell curve in terms of performance and weeds out stragglers, an algorithm can now handle the emotionally difficult aspects of the task.

I have written earlier in this column about how a firm is a nexus of contracts and that this nexus now runs the risk of being made obsolete in many businesses such as IT and back-office services. Until now, we have seen the rise of a marketplace-oriented business culture only among the bottom end of service workers such as cab drivers and couriers. Still, they provide an interesting sociological test bed for the future, as these marketplace forms of organization begin to replace the current dynamic of employer-to-employee relationships.

Let’s examine taxi scheduling and courier services. Drivers for taxi-scheduling apps are small business owners who choose when they come to work, but once they are working, are subject to strict algorithm-driven control. They are only given a few seconds to respond to a ride request routed by the app, and are not told the customer’s final destination until they have picked them up. If the drivers miss a certain number of requests, they are automatically logged out of their smartphones for a set amount of time, much like a penalty box where they are unable to see and respond to ride requests. They are subject to an instant feedback mechanism where the passenger rates the driver and his or her vehicle. These ratings are monitored and taxi-scheduling apps can deactivate drivers should their ratings fall below a certain threshold.

In cases like these, the small business owners (the hundreds of thousands of drivers all over the world who drive for Uber, Lyft, Ola and others) never actually see a human being from the company for which they work. Their entire contact with the firm is limited to the app on their smartphones that links them to the taxi-hailing business. They are, in effect, working for a robot—or an algorithm. This algorithm is ruthlessly efficient, and is devoid of feelings. If the numbers don’t add up, you are out.

In the new-age marketplaces, none of this is considered an employee-to-employer relationship. The drivers, who are small business owners, simply contract with the computer program at the taxi-hailing firm. As Joseph Campbell said: “Computers are like Old Testament Gods; lots of rules and no mercy." And therein lies the rub. If a worker is not an employee, then how does one fault a marketplace organization for predatory practices?

We might see trade unions soon at a variety of services enterprises, in an attempt to ‘humanize’ the relentless algorithm.

Uber, for instance, is in talks with drivers in the US over a dispute on whether they are to be considered employees. And there are cases being brought by unions against firms such as Uber at employment tribunals in the UK.

As a student, I had often wondered how auto-rickshaw drivers in Bengaluru had extremely strong unions and could call a wildcat strike and bring life to a halt in the city. This was even more wondrous given that the drivers were themselves not employees of any firm—the vast majority of them rented their auto-rickshaws for a set fee every day, and ran their own small businesses.

The sociological impact of working for an algorithm will follow history originally established by middle management for efficient production at factories, by workers, in terms of organization, and politicians, in terms of interference. Algorithms will allocate and manage, workers will organize, and politicians, interfere. Meanwhile, muddled middle managers will be mechanized, and will go off to either be retrained or to retire.

Siddharth Pai is a management and technology consultant.

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