Even as The Economist paints a very bleak future for professionals in its latest issue, speaking of how advances in technology are creating substitutes for the white-collar workforce, machine replacing labour is getting all too common at the blue-collar level. Mining giant Rio Tinto has rolled out fully automated truck fleets at two of its mines in Western Australia. Apart from the driverless trucks, the company, reports the Financial Times, is running trials of driverless trains and autonomous drills, to cut costs—with the global commodities slump, automation is proving quite fruitful for Rio Tinto. The company says the autonomous trucks outperform its manned fleet by almost 12%. With such productivity gains, there is no reason why companies wouldn’t push for greater automation.
From car manufacturing to medicine, machines, software and even artificial intelligence are taking up functions carried out by humans. Already, bits of software are beating experienced legal personnel at predicting the outcome of patent cases in the US Supreme Court. Knowledge Integration Toolkit (KniT), a collaboration between a US-based med school and IBM, is generating research hypotheses scanning a medical literature database that could put varsity libraries to shame. That means increasingly there would be less work available and, whatever will be, could require highly specialised knowledge or skills. That is where the challenge lies—creating such high-level skilling and training infrastructure and then finding gainful employment for those skilled.