Why Robot takeover of economy is proceeding slowly
The economy’s growth potential will be higher if smart machines could turbocharge how humans go about their tasks
Vik Singh’s company has powerful artificial intelligence software that helps firms hunt down the best sales leads. Getting somebody to use it -- well, that’s a story that says a lot about the US expansion.
US businesses have every incentive to adopt labor-saving technologies, replacing factory workers with robots and desk jobs with smart software. In some areas, such as finance, machine decision-making is advancing quickly. In others, there are obstacles. Overall, while the penetration of automation in the economy is happening, it is taking place at a slower pace than futurists expected.
Singh tells customers how his system can help trim sales prospecting staff and boost revenue. Managers are intrigued but sometimes reluctant to entrust a high-touch business such as sales to a black box.
“They just don’t understand it,” says the co-founder and chief executive officer of Infer Inc in Mountain View, California. “And they don’t believe it.”
Hundreds of companies are trying to disrupt the way we consume, work, or move. The economy’s growth potential could be higher if smart machines could turbocharge how humans go about their tasks. Higher productivity, or output per hour, would boost corporate profits and may help US workers finally get a pay rise. That economic nirvana just isn’t happening yet.
Productivity in the US rose only 1.1 per cent last year and rather than being replaced by technology, more workers are being hired. Employers have added an average 159,000 new jobs a month so far in this expansion compared with 99,000 in the previous upswing. Over the same period, investment in intellectual property products, such as software, has barely edged up as a share of GDP versus the last cycle.
“Low labour productivity is the biggest problem with the story that I tell,” said Andrew McAfee, co-director at the Massachusetts Institute of Technology’s Initiative on the Digital Economy and co-author of “The Second Machine Age,” a book about the next wave of technology. “Some of these pretty profound innovations are going to take time to diffuse.”

There isn’t a single story that explains why second-wave technologies are trickling rather than flooding into the economy. Bloomberg News spoke with several to find out how the pace of technological adoption is proceeding. Here are some of the themes that emerged:
Robots can handle highly repetitive tasks in manufacturing, but at BMW AG’s largest plant in the world, located in Spartanburg, South Carolina, the talk is about complexity and customisation —tasks that need human input.
Extracting data from highly-automated manufacturing operations is harder than it sounds, executives from Cisco Systems Inc explain. Finally, when it comes to turning any critical operation over to a computer, there is this one big sticking point: trust. Here are some of their stories.
Social Tables helps companies with event space sell it to planners who need it, while also providing collaborative tools. The Washington-based company started using Infer about three years ago after launching a mobile app that gave it about 12,000 new sales leads.
The event space and planning market is large and varied. Sorting through those leads to find potential subscribers would have been a gigantic human task, said Trevor Lynn, the chief marketing officer. The company also turns up about 3,000 new leads a month.
Social Tables had a couple of choices: Hire an expensive database engineer or many more salespeople to sift the data. Instead, they use Infer, which sorts, queries, and offers up live feedback on how the leads are performing. This kind of big-data hunting and vision would be difficult for any human to replicate in real time.

From baggage carousels to shifting stages at a rock concert, a motor made by SEW-Eurodrive Inc is probably the workhorse making things move.
Some of the most efficient manufacturing of precision casing and gearing this German company produces happens in a bustling plant on Old Spartanburg Highway in Lyman, South Carolina. Eighty per cent of the plant’s production is exported. In 2000, there were no robots on the factory floor. Now there is one robot for every human, most made by Japan’s Fanuc Corp.
The plant is so lean that the humans are having a difficult time keeping track of all that robots need and do. Call it a robot saturation point. The next big boost in productivity is likely to come from an unexpected place —digital information, managers here said. SEW Eurodrive is looking for a system to feed data from its production machinery into a computer dashboard that gives operators a real-time look at plant performance rather than scurrying around with clipboards.

This plant in Spartanburg —the largest BMW factory in the world by volume that sprawls over 6 million square feet — is the highly-automated car maker that technologists talk about.
The hype around robotics suggests a world where humans have little input in manufacturing. Talk to BMW managers, however, and it’s all about getting the right mix of humans and machines in a world where customisation and complexity are big challenges.
Almost every one of the 1,400 X-series SUVs rolling off the line here each day has been custom ordered by somebody. While about 1,600 robots weld, drill and paint auto bodies in steel cages, further down the line the cars are surrounded by humans adding this audio system or that trim. Humans are paying close attention to look, feel, smell, and even the sound of these cars to ensure BMW authenticity. If there is one lesson from the team here, it’s that robots move processes while humans improve them, according to Richard Morris, vice president of product integration, who has been with BMW in Spartanburg since 1993.
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