Innovation Monitor: Robotic Process Automation and Worker Displacement

Innovation Monitor: Robotic Process Automation and Worker Displacement

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Welcome to this week’s Innovation Monitor.

The message, theory, and warnings of technology takeovers and its impact on jobs is not new. In fact, it’s been news for at least 200 years, with headlines like the one below from 1928, and the economist John Maynard Keynes’ coining of the term ‘technological unemployment’ in the 1930s. Actually, according to this piece: “In 350 BCE, Aristotle worried that self-playing harps would make musicians obsolete.”

We’ve reached another inflection point in the conversation about automation, as it increasingly dominates public, political, and civic conversations. I recently came across the NYT’s Kevin Roose’s new book, Futureproof: 9 Rules for Humans in the Age of Automation, and it raises a major issue that is not commonly discussed around worker displacement.

The conventional notion of worker displacement includes, for example, advanced AI pushing forward self-driving cars, trucks, and logistics supply chains, and factories that replace the people with robots. Which is all valid and true. However, Futureproof explores another realm of automation — “so-so automation” — in white-collar industries.

Examples of this genre of automation include an Excel macro replacing someone doing data entry, or instead of an advanced natural language generation chatbot, a rule-based customer service phone-tree that tries to minimize as much human interaction as possible.

This field of Robotic Process Automation (RPA) has been rapidly advancing over the past decade, and even more so during the pandemic.

This week we’ll dive into how the debate over whether RPA will create or destroy jobs (or both), and how should business leaders think about these technologies in the future of work? On an optimistic note, Roose’s overall thesis is that, in a world of increasing “so-so automation,” the skills that will become more vital are the very things that make us human.

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Erica Matsumoto The productivity question Are we just overthinking things? Is the true price of automation overstated?

In December 2019 Future of Humanity Institute researcher Robin Hanson co-authored a paper titled Testing the Automation Revolution Hypothesis, which, in a nutshell, suggested the entire narrative is bunk:

“An automation revolution driven by a new kind of automation tech should induce changes in the total amount and rate of automation, and in which kinds of jobs get more automated. But looking at all U.S. jobs 1999–2019, we find no change whatsoever in the kinds of jobs more likely to be automated.”

The main change over the past two decades, Hanson says, might be that tasks have become more suitable for automation, “because nearby tasks have become automated.”

Hanson’s paper has now been published in the peer-reviewed Economics Letters, but he believes it will continue to fly under the media’s radar: “The patterns seems to be that hype gets covered, contradictory deflations of hype do not.” An inflection point It’s hard to argue that we’re not at an inflection point, however. 4IR technologies — from AI to 3D printing — have gone through their years of hype and disillusionment and have matured to a point where they are steadily being integrated into our lives.

“When powerful new technologies are introduced into the economy, productivity may flatten or even dip a bit as initial investments are made — the first part of the J [curve]. But once those technologies have been fully digested, productivity can swoop upwards — the second part of the J,” wrote Axios.

“That’s what we’ve seen in the past. Computers began to filter into the workplace in the 1970s and 80s, but it wasn’t until the 1990s that the productivity gains of all those PCs were finally felt.” The destroyer of jobs…? While the media mainly focuses on the sexy side of robot takeovers, like autonomous trucks leaving truckers out of a job or diagnostic AI replacing doctors, the more boring but realistic side of automation — robotic process automation, or RPA — has actually been shown to lead to layoffs:

“Independent experts say that major corporate R.P.A. initiatives have been followed by rounds of layoffs, and that cutting costs, not improving workplace conditions, is usually the driving factor behind the decision to automate.”

Forrester Research analyst Craig Le Clair says that “companies often rely on [RPA] to juice short-term profits, rather than embarking on more expensive tech upgrades that might take years to pay for themselves. It’s not a moonshot project like a lot of A.I., so companies are doing it like crazy.”

But some firms have managed to successfully integrate RPA without laying anyone off. Holly Uhl, a technology manager at State Auto Insurance Companies, said her firm used RPA to do 173k hours’ worth of work without layoffs, and says people were excited they didn’t have to do certain tasks anymore.

But there is something much more dangerous than widespread RPA: so-so automation. So-so automation So-so automation is “technology that is just barely good enough to replace human workers, but not good enough to create new jobs or make companies significantly more productive.”

One example is self-checkout machines at grocery stores. In a 2019 study, researchers wrote that “the real danger for labor may come not from highly productive but from ‘so-so’ automation technologies that are just productive enough to be adopted and cause displacement.”

MIT Sloan says airlines continue to invest in such services: “It doesn’t satisfy customers all that much. Customers are not saying ‘I want to use this company more because they have [automated] customer service.’ It’s cutting costs to some degree. But because of the [low] quality of the service, the cost cutting is not that powerful either.”

Why invest in something that is merely adequate and which has minor gains? It could be misjudgment: “There’s a lot of hype, and that hype means that companies are overstating or overestimating the benefits they’re going to get from some of these technologies,” says economics professor Daron Acemoglu. The human touch As Kevin Roose said in a recent Verge podcast on automation, “it’s not just Mad Libs anymore.” Machines are getting more convincing, more compelling. As white-collar jobs — and dangerous industrial work — become increasingly easier to automate, what will human jobs look like in the years to come?

The podcast host mentioned the idea that “it’s all software at the bottom and it’s just, you get to pay for various levels of people to help you use it in empathetic ways.” Roose supported this with a great example:

“One of the fascinating case studies I came across in the course of writing this book was Best Buy. Best Buy was supposed to die…. The big box was going away, Best Buy was largely dependent on new DVD and video game releases for profits, which went away… it turns out that they moved to a very high-touch customer service model. They started this in-home adviser program, where, for a fee, they would come to your house, a Best Buy rep would take a look at your stereo system and your speakers and tell you which upgrade you needed.”

It’s not that Best Buy got more low-tech — the underlying business software is always improving. But they added a human touch instead of directly competing with Amazon on price or logistics.

Whether RPA or more creative AI does cause gradual disruption, there will always be a market for that human element. This Week in Business History March 27th, 1860: The Wine Corkscrew is patented in the U.S.

An innovation you may likely be leveraging on this beautiful Spring Friday — the wine corkscrew is patented in the U.S. (you can see the original patent here!)

The need for a corkscrew began in the early 1700s, as glass-blowing techniques allowed for wine bottles to be built to be able to age wine directly within the bottle with an airtight corking system. The only problem was getting the cork out — and the corkscrew design was inspired by tools that hunters and soldiers used to clean out their rifles. The corkscrew was patented in England in 1795 and France in 1828, before its U.S. official arrival.

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