The Future of Jobs – Automation Mimicking Human Intelligence

This is an excerpt from the book ‘The Fuzzy and the Techie – Why the Liberal Arts Will Rule the Digital World’ by Scott Hartley. Scott Hartley first heard the terms ‘fuzzy’ and ‘techie’ while studying political science at Stanford University. If you had majored in the humanities or social sciences, you were a fuzzy. If you had majored in the computer sciences, you were a techie. This informal division quietly found its way into a default assumption that has misled the business world for decades-that it’s the techies who drive innovation.
The prospect of earning big money—an average of over $160,000 per year—mining for iron ore and gold has attracted thousands of young men and women from across Australia for well over a hundred years. But during the past decade, mining companies have implemented machine automation to improve the safety and efficiency of their operations, becoming among the most automated of all industries. Self-driving Volvo trucks manufactured in Sweden are being pressed into service in large open-pit mines across Australia. Scania, another Swedish vehicle company, has pioneered trucks that use GPS and LIDAR (light detection and arranging) sensors to operate with optimal efficiency, minimizing fuel consumption. The trucks are said to have improved efficiency by 15 to 20 per cent. Mining conglomerate Rio Tinto reports a 12 per cent efficiency gain through its own automations, saving millions not only in oil and gas costs, but also in reduced rubber consumption.
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Before automated trucks, humans drove vehicles like the CAT 797, a bright yellow, 4000-horsepower truck capable of carrying 400 tons, or 800,000 pounds of load. Each CAT 797 truck costs around $5.5 million, and the tyres cost more than $40,000 each. If that sounds like a lot of money for a tyre, consider how massive and strong they must be. Each truck requires six Bridgestone 59/80R63 XDR tyres, which stand 13 feet tall and weigh nearly 12,000 pounds. Each tyre is supported by 2000 pounds of steel—enough to build two small cars—and wrapped in enough rubber to make 600 standard automobile tyres.
Future of Jobs
How has Rio Tinto been saving on the cost to procure that rubber? Humans driving at variable speeds up and down circular ramps break more than they need to, resulting in greater tyre turnover. In fact, one of the reasons Rio Tinto and others moved toward automated trucks was rubber savings—automated trucks apply brakes only when necessary, increasing the lifespan of those pricey tires.
In the remote north-eastern corner of Australia, in a thinly populated, arid region known as Pilbara, Rio Tinto has also been pioneering autonomous haulage and drilling systems since 2008. They operate over sixty autonomous trucks, and those trucks have covered 3.9 million kilometers since 2012, loading extracted iron ore on to their AutoHaul system, the world’s first fully autonomous, heavy-haul, long-distance railway. Rio Tinto calls this their ‘mine of the future.’ It is run from a location which is hundreds of miles away, in Perth, by a 400-people operations staff, who manage fifteen mines in total, as well as thirty-one iron ore mining pits, four port terminals, and 1600 kilometers of railroad. The remote operation is made possible by data visualization software that interprets masses of data coming in from sensors on the autonomous vehicles and installed at the mines, and produces easy-to-read displays for the pit controllers, geologists, drill-and-blast teams, and other personnel who supervise the activity. The automation technology allows machines to work autonomously, in the dangerous mining pits, so that humans don’t have to.
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Such triumphs of automation, which are being achieved in an increasing number of industries, have fueled the concerns about massive job losses that Martin Ford predicts in The Rise of the Robots. Academic research has also raised alarms. In the oft-cited 2013 study conducted by Oxford University economists Carl Frey and Michael Osborne, titled ‘The Future of Employment: How Susceptible Are Jobs to Computerization?’ the authors concluded that 47 per cent of US jobs are at a high risk of machine automation over the next one to two decades. What’s more, how so many jobs will be replaced by new jobs for humans to do is very much unclear.
Job displacement by machines is commonly referred to as ‘technological unemployment.’ The argument that masses of human workers would lose jobs, which would not be replaced by other kinds of work, has been made many times in the past, including the dawn of the Industrial Revolution and during the Great Depression in the early twentieth century. Economist John Maynard Keynes contended that job losses during the Depression due to technological advances were leading to ‘means of economizing the use of labor outrunning the pace at which we can find new uses for labor.’
But history contradicts that thesis: as prior waves of technological innovation led to great job displacement, thousands of new and different jobs eventually popped up and offset the losses. In the Industrial Revolution, the vast majority of farm jobs were replaced by factory jobs, so that when in 1900, approximately half of all American workers were employed on farms, today that number is just 2 per cent. Then, from the middle to later twentieth century, much of the new manufacturing work in the US and other developed nations was either automated—by the introduction of robotics technology to the factory floor—or shipped abroad to the less developed nations. But again plentiful new jobs in the service industry emerged.
Conceding this point, Martin Ford argues, however, that the current wave of technological innovation will lead to even more severe job displacement than what has occurred in the past. In other words, this time is different. Fewer new jobs will be created because machines are now able to perform not only many manual tasks as well as humans do, but can also perform some cognitive tasks, and they will be getting better at mimicking human intelligence. This is why he predicts that machines will take over many high-level, ‘white collar’ jobs as well as manual ones.
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The Fuzzy and The Techie‘ gives a particular importance in India where students are unduly pressurized to gain admission into institutes of technology in the hope that they will be at the forefront of change and innovation in the VUCA world. This is a brilliant book if you want to know why liberal arts are still important in our techie world.

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