Recently I attended a breakfast event on the future of work hosted by brand and innovation consultancy OgilvyRed. The event very much tapped into the Zeitgeist of the time, with the company's resident futurist Jess Kimball extolling the audience of the coming robot driven apocalypse.
Kimball referenced the infamous paper from Oxford academics Carl Benedikt Frey and Michael Osborne that forecast the automation of nearly 50% of our jobs within the next few years. The paper is infamous not only because it hasn't been subject to the scrutiny of peer review, but also because its findings are widely misrepresented. It looks at the likelihood that a part of a job might be automated, with the assumption that this will thus result in entire professions being automated something of a stretch.
Indeed, Professor Frey himself seems to be distancing himself from this overly simplistic conclusion.
“In many ways, robots could enhance careers rather than destroy them. The introduction of automation in the workplace will usher in a time where our jobs will become more creative and involve more social interaction. Although robots will render some occupations obsolete, as technology has in the past, humans and robots will also complement each other in many tasks, creating new types of jobs,” he said recently.
In Data We Trust
The thing is, we live in an age that we are told is one of constant disruption, that change is occurring at a pace never seen before. Indeed, it's relatively easy to find examples of just such deep disruption, but is that reflected across the economy?
If we analyze actual data, it would suggest perhaps not. If the labor market was one of constant flux, we would perhaps see evidence of this in the rate at which we change jobs. This isn't something we're actually seeing however. A U.K. study looking at the labor market found that we aren't moving from job to job with any greater frequency now than we were a generation ago. Indeed, our rate of job hopping is actually going down, with this rate especially low in the under-thirties. The same trend also appears when analyzing the U.S. market.
What's more, there is also a distinct lack of churn in the kind of jobs we do either. A recent longitudinal analysis of jobs by the Information Technology and Innovation Foundation found a distinct lack of disruption in the labor market. In other words, it found little evidence that we are seeing more jobs destroyed and new jobs created than we did at any time during the 165 years studied for the report.
Instead, just as with the British study into job-hopping, the report found that the rate of churn was actually at a record low. The conclusion is clear and suggests that rather than being in the midst of a storm of change and technology driven disruption in the labor market, we are actually in a historically benign period.
Of course, it's an argument that carries little water with those of a more pessimistic bent. Despite vast swathes of historical data showing the robustness of the labor market and adaptability of mankind to all previous technological shifts, we are told this time it is different. The pace, breadth and depth of change is unprecedented, they say.
An Uncertain Future
Suffice to say, whilst the past gives us a degree of comfort, none of us can really predict how the future will unfold, and a recent report by the National Academies off Sciences, Engineering and Medicine (NASEM) suggested policy makers are largely clueless about the current state of affairs, due in no small part to the lack of data many officials have on the labor market.
The report urges fresh investment not only in new data sources but also new methods and infrastructure to help support the kind of research required to better understand this complex topic.
"Governments must learn the lessons that industry has learned over the past decade, about how to take advantage of the exploding volume of online, real-time data to design more attractive products and more effective management policies,” they say.
Responding appropriately to new technology is undoubtedly crucial if we are to maximize the benefits whilst minimizing the risks, but to do this we need to collect the best data possible in order to conduct a more robust analysis than is often the case at the moment.
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