<b>Devangshu Datta:</b> Mean machines

Anybody who has ever handled a horse and a car would testify that horse management is more difficult

The industrial revolution has been work in progress ever since the latter half of the 18th century. First, it was mechanised agricultural tools and textile machinery. Then it was mechanised transport. Each innovation brought vast economic changes and massive labour churn. Certain skills disappeared or became quaint anachronisms, while new ones became highly prized. For example, very few people can operate a handloom anymore. There are 150 qualified drivers for every person who has ever sat on a horse. 

Anybody who has ever handled a horse and a car (or a cow and a motorcycle) would testify that horse management is more difficult. It takes a year to produce a new horse and four years for the animal to reach maturity. It takes two more years to train that animal. 

Auto manufacturers churn out 10,000 vehicles a day. When it comes to repair and maintenance, vets also require far more time to train than mechanics. Most new cars are plug-and-play — the vehicle can diagnose and predict emerging problems. 

These changes happened relatively slowly. Labour could shift focus and re-skill as required. The pace of change intensified with the personal computer (PC). Allied to the communication revolution, the PC altered the services workplace. Side by side, advances in industrial robotics changed manufacturing. 

The smartphone put inexpensive, lightweight computing power into every pocket and let that be shared and pooled via fast mobile networks. Search engines got smarter and pools of digital information got larger. 

More skills are becoming obsolete at an increasing pace. Industrial tasks like cutting, welding, soldering, etc., are much more efficiently accomplished by machines. Power grids are managed by smart programs. Financial trading is done by algorithms.

The common householder doesn’t need to know how to repair and maintain an air conditioner, defrost a fridge, set up a home theatre system, change tyres, or engine oil, or hook up an inverter. You could look up any of these processes and watch a five-minute video for instant expertise. 

The pace of change is accelerating as I write. Location based on GPS is commonplace and apps built on that are proliferating. The Internet of Things is embedded into every sort of new artefact, from houses to kids’ toys. Soon, the smart house will repair itself and maintain the AC, home theatre, pay the bills, etc. 

Machine Learning, Artificial Intelligence, and Big Data are also cutting into high-end white-collar work. Machines sort spending patterns and predict what you will buy next. Health care is now delivered by smart machines rather than traditional paramedics. Insurance is calculated online by robots. Super computers are better at cancer diagnosis than human oncologists. Computers are better paralegals than law school graduates. Robots edit and translate most content better than traditional journalists. 

Smart driverless cars are already on the roads. Supertankers carrying two million barrels of crude oil have six-person crews, largely on board just to satisfy statutory insurer requirement. Smart drones and “big-dog” style robots wage war effectively by remote control. 

Professional drivers will experience obsolescence as smart cars take over. So will a vast number of mid-level white-collar workers with many different skill sets. Ditto for a large number of semi-skilled blue-collar workers. Some people will be reskilled to handle new machines. Some smart people will learn how to design even smarter machines and invent systems to control those. 

The social impact of a huge chunk of the global workforce being rendered redundant over the next decade is impossible to calculate. There have been periods of high unemployment before and there have been periods of churn. 

But, it has never happened in such a compressed time period and there has never been a time where such a large proportion of workforce became unemployable practically overnight. How does someone feel when he or she realises that a machine can do everything better? 

Will society suffer mass depression and psychological collapse as this truth sinks in? Coping with the social impact will be one of the biggest challenges of the next decade. In fact, coping with the social impact might itself be a source of employment. Unless, of course, the robot psychiatrists do it better!  

Twitter: @devangshudatta