65% of future jobs, which doesn’t exist, 70% of jobs automated, just not yet

The future of work is the work of imagination. We are, repeatedly, and have been for a while, bombarded with (pseudo-)facts about what the future of work will bring. These are, of course, part of well-known, long-standing, narratives about ‘innovation’, ‘growth’, technological advance and, of course, ‘automation’.

Martin shared a good post by , on his site Long View on Education, about some persistent kinds of story around the nature of work our schools are preparing children for, or not. Here’s  an abridged, and selective, version of the story…

“The top 10 in demand jobs in 2010 did not exist in 2004. We are currently preparing students for jobs that don’t exist yet, using technologies that haven’t been invented, in order to solve problems we don’t even know are problems yet.”

Shift Happens videos (2007).

People repeat the claim again and again, but in slightly different forms. Sometimes they remove the dates and change the numbers; 65% is now in fashion. Respected academics who study education, such as Linda Darling-Hammond (1:30), have picked up and continue to repeat a mutated form of the factoid, as has the World Economic Forum and the OECD.


“By one popular estimate 65% of children entering primary schools  today will ultimately work in new job types and  functions that currently don’t yet exist. Technological  trends such as the Fourth Industrial Revolution will  create many new cross-functional roles for which  employees will need both technical and social and analytical skills. Most existing education systems at all levels provide highly siloed training and continue a  number of 20th century practices that are hindering  progress on today’s talent and labour market issues.  …  Businesses should work closely with governments,  education providers and others to imagine what a true 21st century curriculum might look like.”

The WeF Future of Jobs report


Cathy Davidson (May 2017) explains up how she came to the factoid:

“I first read this figure in futurist Jim Carroll’s book, Ready, Set, Done (2007). I tracked his citation down to an Australian website where the “65%” figure was quoted with some visuals and categories of new jobs that hadn’t existed before. “Genetic counseling” was the one I cited in the book.

After Now You See It appeared, that 65% figure kept being quoted so I attempted to contact the authors of the study to be able to learn more about their findings but with no luck.  By then, the site was down and even the Innovation Council of Australia had been closed by a new government.”

The BBC radio programme More or Less picks up the story from here, demonstrating how it most likely has no factual basis derived from any identifiable source (there never was an Innovation Council of Australia, for example).

Davidson sort of defends this through dissimulation, in an interview for More or Less, by saying she believes that 100% of jobs have been affected by ‘the digital era we now live in’.

As Audrey Watters has highlighted, statistics like this and the appeal for a ‘disruption’ of education by the tech sector to teach ‘the skills of the future’ etc. can be reasonably interpreted as a marketing smoke screen – ‘the best way to predict the future is to issue a press release’.

An allied claim, that fall within the same oeuvre as the “65%” of not-existing jobs (or should that be non-existent?), is the various statistics for the automation of job roles, with varying timescales. A canonical example, from another “thought leader” (excuse me while I just puke in this bin), is from WIRED maven Kevin Kelly:

There are an awful lot of variations on this theme, focusing on particular countries, especially the USA, or particular sectors, or calculating likelihoods for particular kinds of jobs and so on and so on. This is, of course, big business in and of itself – firms like Deloitte, McKinsey and others sell this bullshit to anyone willing to pay.

What should we make of all this..?

There are a few interpretations we can make of this genre of ‘foresight’. Alongside several other academics I have written about particular ways of communicating possible futures, making them malleable-yet-certain in some way, as a ‘politics of anticipation‘. This politics has various implications, some banal some perhaps more troubling.

First, you might say it’s a perfectly understandable tendency, of pretty much all of us, to try and lend some certainty to the future. So, in our adolescent know-it-all way, we are all wont to lend our speculations some authority, and statistics, however spurious, is a key tool for such a task.

Second, and perhaps allied to the first, is the sense in which methods for speculation become formalised and normative – they’re integrated into various parts of institutional life. So, it becomes normal to talk about speculative (spurious?!) statistics about a future of work, education etc. in the same tone, with the same seriousness, and the same confidence as statistics about a firm’s current inventory, or last year’s GDP trends. Of course, all statistics, all facts, have conditions and degrees of error and so if the calculation of trends for past events is open to change, the rationale might be, perhaps future trends are just as reliable (there’s all sorts of critique available here but I’m not going to delve into that). In this way, consultancies can package up ‘foresight’ as a product/service that can be sold to others. “Futures” are, of course, readily commodified.

Third, an ideological critique might be that it is precisely these forms of storytelling about the redundancy or insufficiency of the labour force that allows those with the large concentrations of capital to accrue more by demeaning the nature of work itself and privatising profits upwards. If we are repeatedly told that the work that generates the good and services that move through our economy is worth less – because it can be automated, because it is ‘out-dated’, because there are other kinds of superior ‘skilled’ work – then it perhaps becomes easier to suppress wage growth, to chip away at labour rights and render work more precarious. Gloomy I know. However, some data (oh no! statistics!) Doxtdator has in his blogpost (and the kinds of data David Harvey uses in his books, such as The Engima of Captial) could be seen as backing up such arguments. For example (source):

These sorts of graphs, tell a different story about yesterday’s future – which didn’t lead to families reaping the rewards of automation and increased productivity by profiting from a share in increased leisure time (following JM Keynes), but rather delivered the profits of these trends to the “1%” (or even the “0.1%”) by massively increasing top executive salaries while keeping wider wage growth comparatively low, if not stagnant. I’m not an economist, so I don’t want to push my luck arguing this point but there are folk out there who argue such points pretty convincingly, such as David Harvey (though see also economic critiques of the ‘zombie’ automation type of argument).

Ultimately, I am, personally, less interested in the numbers themselves – who knows if 65% of today’s school children will be doing new jobs that represent only 70% of the total work we currently undertake?!  I’m more interested in the kinds of (speculative) truth-making or arguing practices they illustrate. The forms of speculative discourse/practice/norms about technology and work we’re all involved in reproducing. It seems to me that if we can’t fathom those things, we’re less able to care for those of us materially affected by what such speculation does, because, of course, sometimes speculation is self-fulfilling.

To try to advance some discussions about the kinds of technological and economic future that get proposed, gain momentum and become something like “truths”, I’ve been puzzling over the various ways we might see the creation of these economic statistics, the narrating of technological ‘innovation’ in particular ways, and the kinds of stories ‘critical’ academics then tell in analysing these things as making up collectively some form of collective imagination. I started out with ‘algorithms’ but I think that’s merely one aspect of a wider set of discourses about automation that I increasingly feel need to be addressed. My placeholder term for the moment is an “automative imaginary” ~ a collective set of discourses and practices by which particular versions of automation, in the present and the future, are brought into being.

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