Another day, another news headline screaming about robots and AI – usually, how they’ll take our jobs.
Here’s why this is wrong.
Imagine waking up to find 7 out of 10 jobs had gone. Lost forever. Would you be alarmed? Probably.
Yet this is what happened in the Industrial Revolution. Many old jobs were “lost” – but many more new jobs were created.
The fascinating thing is that these jobs could never have been envisioned before. As futurist Kevin Kelly notes:
“While the displacement of formerly human jobs gets all the headlines, the greatest benefits bestowed by robots and automation come from their occupation of jobs we are unable to do. We don’t have the attention span to inspect every square millimetre of every CAT scan looking for cancer cells. We don’t have the millisecond reflexes needed to inflate molten glass into the shape of a bottle. We aren’t giving “good jobs” to robots. Most of the time we are giving them jobs we could never do. Without them, these jobs would remain undone.”
How AI and robotics can save the Australian economy $6.6 billion each year
The other major advantage in bots doing these “undone” jobs is that they do them more safely. This isn’t some warm and fuzzy statement, it’s a hard metric with a massive effect on Australia’s economic bottom line.
Studies byAlphaBeta/O*Net/ABS show that workplace injuries will fall by a huge 11 per cent as automation eliminates some of the most dangerous physical tasks in the Australian economy. Given workplace injuries cost us over $60 billion each year, bots can save lives, and huge social costs as well.
There are hundreds of new frontiers opening up as we harness our bots, chips, algorithms and newly minted insights.
A good example is the digital twin concept pioneered by General Electric. For a jet engine, a gas turbine or a windmill, data is gathered on the machine’s attributes (heat, vibration, noise and the like). This data is collected in the cloud and organised into a model “twin” that allows analysis that replicates the machine’s performance. The digital twin model can then be used to diagnose faults and predict the need for maintenance, ultimately reducing or eliminating unplanned downtime in that machine. The digital twin concept can be extended to aggregations of machines — a plant or fleet can be digitally twinned as well.”
Once the digital twin is created, real people with real skills need to monitor and, where necessary, fix the real engine. This is a new job category we couldn’t have even dreamed of in 1960, or even 1990. Chief Digital Twin Monitor Officer! Plus their team of support people with new skills requiring new education and training resources.
Overseeing and guiding new technology
So, as David Trilling from the Harvard Kennedy School’s Shorenstein Center observes, “are we living in an era so different than past periods of change? Industrialisation gutted the skilled artisan class of the 19th century by automating processes like textile and candle making. The conversion generated so many new jobs that rural people crowded into cities to take factory positions. Over the 20th century, the ratio of farm jobs fell from 40 percent to 2 percent, yet farm productivity swelled. The technical revolution moved workers from factories to new service-industry jobs.”
Increased employment as a result of higher productivity through AI and robotics is already having a practical effect. Smart Steel Systems, an innovative steel fabrication operation in Brisbane, is bringing jobs back “onshore” according to CEO Chris Brugeaud. Implementing robotics has directly lifted employment across his organisation. It has more than halved the time to produce a tonne of fabricated steel…and the number of employees has risen from three to nine. The payroll now includes software, mechatronics and robotics engineers. Welders and boilermakers have moved into the office and now work alongside computer scientists and artificial intelligence experts. “We’ve gone from marking material out on your hands and knees by hand and cutting it by hand, to profile cutting out by computer technology,” Mr Robinson said.
The more we use AI and other tech to do things for us, the more jobs we dream up for them to do. Like analysing 22 million emails and discovering previously unseen insights and business opportunities, which can dramatically increase profitability.
Are we creating smart machines? Yes, we are. But they need to be trained, maintained and applied to relevant tasks by intelligent people.