In a new fact sheet the Tech Partnership reveals that UK cyber workforce has grown by 160% in the five years to 2016. 58,000 people now work in cyber security, up from 22,000 in 2011, and they command an average salary of over £57,000 a year – 15% higher than tech specialists as a whole, and up 7% on last year. Just under half of the cyber workforce is employed in the digital industries, while banking accounts for one in five, and the public sector for 12%.
There is a lot of speculation at the moment as to the jobs of the future. On the one hand, it is said that we are educating young people for jobs which do not yet exist; on the other hand there are dire predictions that up to of existing 55 per cent of jobs may disappear to automation in the next five years.
If it is hard as a researcher who works with labour market data to make sense of all this, imagine what it is like for young people trying to plan a career (and if doing a degree in the UK, running up major debt).
However, there is beginning to appear some more nuanced research on the future of jobs. Michael Chui, James Manyika, and Mehdi Miremadi have just published the initial report on a research project looking at how automation will affect future employment. The report, entitled ‘Where machines could replace humans—and where they can’t (yet)’, is based on detailed analysis of 2,000-plus work activities for more than 800 occupations. Using data from the US Bureau of Labor Statistics and O*Net, they have quantified both the amount of time spent on these activities across the economy of the United States and the technical feasibility of automating each of them.
Their overall finding is that while automation will eliminate very few occupations entirely in the next decade, it will affect portions of almost all jobs to a greater or lesser degree, depending on the type of work they entail.
Each whole occupation is made up of multiple types of activities, each with varying degrees of technical feasibility. In practice, they explain, automation will depend on more than just technical feasibility. Five factors are involved: technical feasibility, costs to automate, the relative scarcity, skills and costs of workers who might otherwise do the activity, benefits (e.g. superior performance) of automation beyond labour costs substitution and regulatory and social acceptance considerations.
The likelihood and ease of automation depends on the types of activities organised on a continuum of less susceptible to automation to more susceptible to automation: managing others, applying expertise, stakeholder interactions, unpredictable physical work, data collection, processing data, predictable physical work. Thus occupations like accommodation, food service and manufacturing which include a large amount of predictable physical work are likely to be automated, similarly work in finance and insurance which involves much processing of data. On the other hand jobs in construction and in agriculture which comprise predominantly unpredictable physical work are unlikely to be automated, at least at present. And there is good news for teachers: “the importance of human interaction is evident in two sectors that, so far, have a relatively low technical potential for automation: healthcare and education.”
Like very much this announcement in the Media, Communications and Cultural Studies Association (MeCCSA) list server:
Dr Ergin Bulut is an assistant professor at Koc University in Turkey. He will start his IAS fellowship on 1 June 2017. It will focus on the analysis of labour conditions in the video game industry. Dr Bulut comments on the importance of studying the digital game industry: “There is much hype regarding the potentials of creative economy and creative production. Young people tend to regard video game development as a dream job. Our society also preaches that young people should do what they love and be ready to work for free if they really want to have a job in the video game industry or other creative industries. An inquiry of the game industry enables us to understand both the pleasures and pains of game development and interrogate the politics of this ‘dream job’ discourse”.
It seems every event about start up businesses I go to focuses on computers and Information Technology as the golden answer for young people and work opportunities in the future. I don’t have the figures to hand but I read in an EU report that the average (mean, I think) wage for those developing mobile apps in the UK is something like £12,000 a year and it is little more in most EU countries.
There seems a fairly wide disjunction between young people’s perceptions and the reality of opportunities and employment in different jobs.About five years ago I ran a focus group in a careers centre in Kent in England. I asked the young people in the panel how they found out about possible careers. They looked at me as if I was stupid – its obvious sir, they said. We look it up on Google. Research suggests most people rarely go beyond the first page of listings on any Google search. And then, as now, queries about how much pay you can hope to make frequently push sites to the top which are merely trying to gather data and give wildly improbable results based on very little data. It was this experience which led us to become involved in the UKCES LMI for All project which seeks to provide access to a range of quality labour Market Information and can be used to develop a variety of different applications. But good though LMI for All is research like that outlined above in a range of different occupations would be invaluable in helping to understand why young (and not so young) people choose their careers. (And I love the title!).
One of the best things about Twitter is the ability to follow links to all kinds of things you probably would never have been to without it. And so I find in my notes somewhere the link to an article in Quartz – an online magazine (?) about which I know nothing. The link is to a loosely researched article about entrepreneurism – making the point that there is not much thing as an entrepreneurial gene but rather propensity to take risk and to set up new businesses is more like to be related to access to money – in other words to class.
The article, attributed to REUTERS/Allison Joyce, quotes University of California, Berkeley economists Ross Levine and Rona Rubinstein who “analyzed the shared traits of entrepreneurs in a 2013 paper, and found that most were white, male, and highly educated. “If one does not have money in the form of a family with money, the chances of becoming an entrepreneur drop quite a bit,” Levine tells Quartz.”
Entrepreneurship is all the trend in Europe at the moment, especially in the recession and austerity hit southern countries, where setting up a business is seen as one of the few ways of getting a job. However the rhetoric seems to overplay the potential of technology (everyone can be the next Steve Jobs!), whilst ignoring sectors of the economy such as tourism which probably represent better opportunities within the existing labour market.
At the same time programmes such as the EU Youth Guarantee fund are being used to set up support agencies for young people wishing to set ups their own business and we are seeing the increasing emergence of co-working spaces for new enterprises. But anecdotal evidence – and some reports although I cannot find them at the moment – suggest that many of these businesses are struggling to survive beyond the first one or two years. In austerity Europe bank capital remains hard to come by and most young people do not have access to their own funds to consolidate and explained their business. Although initiatives like the EU SME programme are very welcome, access to such funding is not simple and anyway the amount of grants on offer are simply insufficient. As European politicians slowly wake up to the disaster austerity policies have wrought, then establishing better support for new businesses should be a priority, tied to easy access to small business start up capital.
Many of my friends from outside the UK have asked me however could people have voted for Brexit. And I have read countless newspaper columnists and analysts asking the smae question (with usually not very profound answers). The best explanation I have come across was posted by Ron Johnston, Kelvyn Jones and Davidn in an article entitled Predicting the Brexit vote: getting the geography right (more or less) on the London School of Economics Politics and Policy blog. Using a large body of polling data collected by YouGov they had earlier this year pointed to “clear evidence suggesting that young people and those with higher-level educational qualifications were much more likely to support Remain, whereas older voters and those with few or no qualifications were much more likely to support Leave.”-And despite they misread the likely outcome of the referendum, their findings largely tie up with a post referendum analysis of the results. Following a detailed analysis they find that:
There are substantial parts of the country where large numbers of people have lost out from the deindustrialisation and globalisation of the last few decades of neo-liberal economic policies, and where the educational system has not helped large proportions of the young to equip themselves for the new labour market. Increasing numbers in these disadvantaged groups were won over during the last few decades by the campaigns in parts of the print media, taken up by UKIP since the 1990s, linking their situations to the impact of immigration – uncontrollable because of the EU freedom of movement of labour principle.
From this they conclude that “class, as expressed through educational achievements, delivered Brexit.”
Linking austerity (which has done nothing good for the vast majority of people in the UK) to the growing inequalities in the education system is important to understanding the Brexit vote. Of course the vote can be seen as an attempt to kick the ruling Tory party toffs. Yet it is very hard to argue for the EU, given that they have been one of the major transnational proponents of austerity.
However, I have some reservations about the idea that “the educational system has not helped large proportions of the young to equip themselves for the new labour market”. On the one hand this is obviously true. But the problem is that the new labour market is largely comprised of low paid and insecure jobs, mainly in the service sector. Many of those who have been able to pay for an increasingly expensive university degree are working in what are classified as non degree jobs. Education and the labour market have to be understood as parts of a symbiotic system. Education alone will not change the reality of lack of opportunity in deindustrialised areas of the UK. Lack of opportunity for meaningful and adequately paid employment and lack of educational opportunity are two sides of the same coin in a currency called austerity.