Work, Productivity & Pay
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Work, Productivity and Pay

Wanjiru Njoya, PhD (Cantab.) MA (Oxon.) LLM (Hull) LLB (Nairobi) PCAP (Exeter)
​Fellow of the UK Higher Education Academy

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Working with robots

8/5/2017

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In a few years the notion of human beings physically doing repetitive tasks will become inexplicable and even unimaginable. We will be so glad that the digital age and artificial intelligence have saved skilled workers from drudgery.
In my own profession countless hours spent in libraries poring through dusty tomes of law reports are a distant memory. Now we have online databases of cases and statutes, and increasingly it's all available for free on google. Any case or statute can be pulled up online in seconds. Such developments have increased our productivity and freed up time that would otherwise be spent doing large amounts of repetitive work so that we can focus their energies on being creative and innovative and having more fun at work, doing cool stuff.

But the way things are going, soon even the creative, innovative and fun stuff will be performed by robots. This is a problem because the first people to be replaced by robots will be those who are already in precarious work, like delivery drivers who are apparently being replaced by drones. 
As long as life goes on, there will be new ways of doing things that will replace the old ways.  Structural changes in the world of work are inevitable and many jobs are lost in the process.

The underlying cause of structural unemployment is heterogenous workers and heterogenous jobs. But it is called ‘structural’ because it is caused by so-called structural shifts – changes in demand for goods and services, technological change and changes in the location of people and industry.


Stephen A. Woodbury, ‘Unemployment’ in Labor and Employment Law and Economics, p. 481.
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​The thing about structural unemployment is that it comes along gradually, and by the time it hits it is far too late to do anything about it. It must be noticed early if there is to be any chance of survival. The time to start reacting is when it becomes increasingly clear that somewhere deep in the basement of a lab where they make robots, a mad scientist has figured out a way to make a machine that does essentially the function you perform in your job. Yes, at this stage the idea is still science fiction, but by the time it becomes reality and you are replaced by a robot it will be far too late to start retraining. 

It is very unlikely that governments will attempt to retrain anyone so that they can continue to work, by taking advantage of artificial intelligence rather than being replaced by it. Also, retraining doesn’t work for those who have multiple underlying problems:

They had dropped out of high school and in some cases had been in trouble with the law. These individuals had not done well in school and probably are not well suited to training, at least until they gain some maturity and direction.

‘Unemployment’, p. 509-10. 
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Oh dear. There are many things the government can do, but supplying individuals with a little maturity, a little direction, is beyond the power of any government. Some things can only be fixed by each individual on his own behalf.

It’s hard for the government to know who is worth training because they’re mature and disciplined, and who isn’t worth training because they’re unreliable and feckless, so it’s just easier for governments to shunt everybody onto the gravy train and be done with it. Also, the gravy train is far cheaper than trying to retrain all the unemployed folk, and the cost of giving everyone a basic income is lower and cheaper to administer than the cost of trying to retrain people in various random skills that might or might not prove useful. The tricky thing with retraining is that by the time the retraining is complete, and you have your shiny new credentials, new robots will have been invented and you have to start retraining all over again to get new useless credentials.

​What will be the implications for economic inequality, which is widely viewed as the greatest social challenge of our time? 
We’re supposed to be reducing inequality, not equipping the privileged to have nicer lives while pulverizing the underprivileged. The same applies to nation states. States that innovate (the wealthy countries) will get wealthier on the back of the effort put in by robots, and life will be more fun for their citizens. States that are not yet even on the starting line for innovation, because at the moment their citizens are starving due to basic food-production failures, will just have to die out or something. If starvation doesn’t get them, the Age of Robots will.

Tyler Cowen, an economist at George Mason University and a much-read blogger, writes in his most recent book, “Average is Over”, that rich economies seem to be bifurcating into a small group of workers with skills highly complementary with machine intelligence, for whom he has high hopes, and the rest, for whom not so much.

‘The future of jobs’ The Economist, January 18th 2014.

This sounds like Armageddon (for some... for the rest it will be more like Utopia), so what we can do to prepare for it? There is plenty of bad news; but there is some good news too. 

The good news is that ‘skilled’ no longer means ‘credentialed’. Being skilled means being a problem solver, which means being the sort of person who offers value that other people are prepared to pay for. Luckily, you don’t need to go to college to learn how to do this. You just need eyes to see, ears to listen with, and a brain to think with: just being a switched on human being.

You don’t need to have a credential in order to meet a human need.
“Love thy neighbor as thyself” was not prefaced with “if you have the proper certification.”
You don’t have to go through an audition, an application process, or an adjudication committee to find problems that need solutions.
Generosity is a permissionless enterprise.
You may not have a degree, but you always have something to offer.

T.K. Coleman, Generosity is a permissionless enterprise


​In that sense the new economy is a great leveller. It has opened up a whole new way of understanding the world of work and what we contribute to it. It has completely changed the traditional emphasis on formal education and university qualifications. Instead, creativity and initiative are the new priority:

When Catalyst DevWorks evaluated hundreds of thousands of IT systems managers, it found no correlation between college degrees and professional success. Digitization and automation seem to be placing a premium on not just technical skills but also creativity and initiative—which, recent research suggests, are becoming less correlated with formal education, even a STEM one.

From educational credentials to intrinsics, in 'Rethinking Work in the Digital Age' McKinsey Quarterly, October 2016.​
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More good news is that people who watch these developments have seen this coming for a long time. There is plenty of information on the emerging trends, and on the industries most at risk of automation. The Luddites were in an unfortunate position because nobody warned them about the coming first age of the machine. There was no google for them to go on for free, to find out what the heck was going on. All they could do was smash up the machines and hope for the best. It didn't really end well for them.

Today there are public libraries donated by the generous taxpayer, which have free computers and free wifi. Everyone can find out what's going on and get free advice on how to position themselves. So, for example, you can discover that office administration is a higher risk career choice than health care. Nursing may be more secure than copy-typing.  When you’re in hospital lying in bed with a fever, you want an actual soft nurse with a soothing voice to kiss your brow, not a stiff robot with a metallic voice.

Today we have really detailed studies of how automation is likely to affect jobs in the future:

According to our estimate, 47 percent of total US employment is in the high risk category, meaning that associated occupations are potentially automatable over some unspecified number of years, perhaps a decade or two.

As computerised cars are already being developed and the declining cost of sensors makes augmenting vehicles with advanced sensors increasingly cost-effective, the automation of transportation and logistics occupations is in line with the technological developments documented in the literature.


As industrial robots are becoming more advanced, with enhanced senses and dexterity, they will be able to perform a wider scope of non-routine manual tasks. From a technological capabilities point of view, the vast remainder of employment in production occupations is thus likely to diminish over the next decades.

Frey and Osborne, ‘The Future of Employment’ (2013)

​Nor is it just traditional industries that are under threat.

Text-mining programs will displace professional jobs in legal services. Biopsies will be analysed more efficiently by image-processing software than lab technicians. Accountants may follow travel agents and tellers into the unemployment line as tax software improves. Machines are already turning basic sports results and financial data into good-enough news stories.

‘The future of jobs’ The Economist, January 18th 2014.
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As more people get left behind by technological change, the more we can expect inequality to be a huge social concern, and the more people will see the welfare state as the best safety net for displaced workers. Your options are: either embrace the Age of the Robot, or else sit at home and wait for your welfare cheques which will be supported through progressive taxes and a bigger role for social security.

​The welfare state, funded by all the rich people who are making money off the robots (that's until the robots wise up and take over the galaxy), will be the dominant player in the brave new world of artificial intelligence. We will see the welfare state being rolled out as the catch all for anyone who has opted out (or been shunted out) of joining the new economy. 

Today, because of measures introduced in response to, and to some extent on the proceeds of, industrialisation, people in the developed world are provided with unemployment benefits, disability allowances and other forms of welfare. They are also much more likely than a bygone peasant to have savings.

​This means that the “reservation wage”—the wage below which a worker will not accept a job—is now high in historical terms. If governments refuse to allow jobless workers to fall too far below the average standard of living, then this reservation wage will rise steadily, and ever more workers may find work unattractive. And the higher it rises, the greater the incentive to invest in capital that replaces labour.


​‘The future of jobs’ The Economist, January 18th 2014.
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The only missing piece in this puzzle is the person caught between a rock and a hard place because they are not robot-ready (rock) but they would rather die than go on welfare (hard place). This is the person who must work for existential reasons, who finds meaning in work because it is simply human nature to be productive, to stand on your own two feet, and to be the author of your own life. 

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    Wanjiru Njoya

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