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If you have ever been gripped with the desire to make a macroeconomist chuckle, quote the title of this piece while telling them of your latest forecast. Many of the biggest follies in forecasting have been founded on the belief that the usual rules have been repealed—that the normal constraint on asset values, growth rates, or whatever projection don’t apply this time. If you believe in the words of Erasmus, however, a certain degree of folly must be borne for a happy life. It is thus with eyes wide open that I claim that “this time is different” when it comes to the future of work.

First, this phase of globalisation and robotics, (or “globotics”), will mostly be about the service sector, not just the manufacturing, mining and agricultural sectors as in past decades. This matters in many ways—not the least of which is that 80 to 90% of people in advanced economies now work in the service sector.

Globotics is governed by a different physics. Past globalisation and automation were mostly about goods, and thus the manufacturing sector and related infrastructure. They were restrained by the laws of physics that apply to matter. Globalisation and automation of the service sector are all about information: processing and transmitting it.

It would be physically impossible to double world trade flows in 18 months. The infrastructure could not handle it, and building infrastructure takes years, not months, for reasons that have to do with the physics as well as the economics of it. World information flows, by contrast, have doubled every couple of years for decades. They will continue to do so for years to come.

The technological impulses behind the coming globotics transformation are profoundly different from those that triggered previous waves of automation and globalisation. The disordering of service sector jobs will come faster than most believe.

We live in a time when the future of work is changing rapidly, but also in a time when it is particularly difficult to sort out the main lines. The baseline argument is that the world we are in is witnessing two distinct types of growth processes, expected and explosive:

• The first is the normal or “expected” pace of post-WWII growth, where 5 to 10% per year is a really fast rate for just about anything ranging from GDP and sales to wages and productivity. The doubling times for these growth processes are measured in decades.
• The second is the “explosive” pace of almost anything to do with digital technology—which means the collection, transmission, storage and processing of information. The doubling time for these growth processes is measured in months.

The tricky part is that most things—say job displacement, or reorganisation of work practices—are affected by a blend of the two processes. The difficulty lies in sorting out which parts are subject to expected change and which to explosive change.

More generally, artificial intelligence (AI) software robots are making service sector workers and professionals more productive by automating some tasks—but not all. That means that some aspects of the future are governed by the expected pace of progress; others by the explosive pace of digitech. The big pay-off in insight comes from thinking hard about which tasks are subject to the explosive progress and how this will affect the new jobs and those that survive it.

One particularly common line of thinking takes AI-trained “robots” as humans who haven’t quite grown into fully capable human-replacements. The inevitable question arises: how long will it take before AI completely replaces lawyers? There is, perhaps, a more accurate way of framing the issue. Think of AI akin to a tractor. A tractor is not a “baby farmer” that will grow into a full replacement farmer. A tractor is a very useful tool; it changed the occupation of farming and allowed fewer farmers to grow the same amount of food—but it will never replace farmers entirely. AI should be thought of thus for the foreseeable future.

The future of globalisation is changing rapidly, and in ways few expected. The term I like to use is “telemigration”—people sitting in one nation and working in offices in another.

The first and most obvious linkage between digital technology and globalisation is automatic language translation—what experts call “machine translation”.

According to Google research, which uses humans to score machine translations on a scale from zero (complete nonsense) to six (perfect), in 2015 Google Translate got a grade of 3.6—far worse than the average human translator, who gets scores like 5.1. After a massive upgrade in 2016, Google Translate now hits numbers like 5.

Machine translation is not lurking in computer laboratories: it is on your smart phone, your laptop. Free apps like Google Translate, and iTranslate Voice are now quite good across the major language pairs. The capabilities are advancing in leaps and bounds.

Another key change is the rise of freelancing platforms like Upwork, with companies and individuals in rich nations finding, hiring, managing and paying talented, low-cost service workers sitting abroad.

This piece is intended to call for more nuanced thinking about the future of work. Two of my favourite sayings encapsulate the pace of change. The first is the adage I used to end my 2016 book, The Great Convergence: Information technology and the New Globalisation: “Things have changed so much that not even the future is what it used to be”. The second is a quote from a social media marketer, Graeme Wood: “Change has never happened this fast before, and it will never be this slow again”. There is still time to prepare, but now is the time to wake up and realise that the future really will be very different.

As part of an OECD Forum series, the virtual event The New Geography of Work: From home, near home and beyond took place on 8 December 2021.

This event has now ended and registration is closed – but don't worry, you can still watch the replay!

And learn more in the OECD policy paper: Productivity gains from teleworking in the post COVID-19 era: How can public policies make it happen?