Tag: structural unemployment

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The AI revolution

Artificial intelligence is having a profound effect on economies and society. From production, to services, to healthcare, to pharmaceuticals; to education, to research, to data analysis; to software, to search engines; to planning, to communication, to legal services, to social media – to our everyday lives, AI is transforming the way humans interact. And that transformation is likely to accelerate. But what will be the effects on GDP, on consumption, on jobs, on the distribution of income, and human welfare in general? These are profound questions and ones that economists and other social scientists are pondering. Here we look at some of the issues and possible scenarios.

According to the Merrill/Bank of America article linked below, when asked about the potential for AI, ChatGPT replied:

AI holds immense potential to drive innovation, improve decision-making processes and tackle complex problems across various fields, positively impacting society.

But the magnitude and distribution of the effects on society and economic activity are hard to predict. Perhaps the easiest is the effect on GDP. AI can analyse and interpret data to meet economic goals. It can do this much more extensively and much quicker than using pre-AI software. This will enable higher productivity across a range of manufacturing and service industries. According to the Merrill/Bank of America article, ‘global revenue associated with AI software, hardware, service and sales will likely grow at 19% per year’. With productivity languishing in many countries as they struggle to recover from the pandemic, high inflation and high debt, this massive boost to productivity will be welcome.

But whilst AI may lead to productivity growth, its magnitude is very hard to predict. Both the ‘low-productivity future’ and the ‘high-productivity future’ described in the IMF article linked below are plausible. Productivity growth from AI may be confined to a few sectors, with many workers displaced into jobs where they are less productive. Or, the growth in productivity may affect many sectors, with ‘AI applied to a substantial share of the tasks done by most workers’.

Growing inequality?

Even if AI does massively boost the growth in world GDP, the distribution is likely to be highly uneven, both between countries and within countries. This could widen the gap between rich and poor and create a range of social tensions.

In terms of countries, the main beneficiaries will be developed countries in North America, Europe and Asia and rapidly developing countries, largely in Asia, such as China and India. Poorer developing countries’ access to the fruits of AI will be more limited and they could lose competitive advantage in a number of labour-intensive industries.

Then there is growing inequality between the companies controlling AI systems and other economic actors. Just as companies such as Microsoft, Apple, Google and Meta grew rich as computing, the Internet and social media grew and developed, so these and other companies at the forefront of AI development and supply will grow rich, along with their senior executives. The question then is how much will other companies and individuals benefit. Partly, it will depend on how much production can be adapted and developed in light of the possibilities that AI presents. Partly, it will depend on competition within the AI software market. There is, and will continue to be, a rush to develop and patent software so as to deliver and maintain monopoly profits. It is likely that only a few companies will emerge dominant – a natural oligopoly.

Then there is the likely growth of inequality between individuals. The reason is that AI will have different effects in different parts of the labour market.

The labour market

In some industries, AI will enhance labour productivity. It will be a tool that will be used by workers to improve the service they offer or the items they produce. In other cases, it will replace labour. It will not simply be a tool used by labour, but will do the job itself. Workers will be displaced and structural unemployment is likely to rise. The quicker the displacement process, the more will such unemployment rise. People may be forced to take more menial jobs in the service sector. This, in turn, will drive down the wages in such jobs and employers may find it more convenient to use gig workers than employ workers on full- or part-time contracts with holidays and other rights and benefits.

But the development of AI may also lead to the creation of other high-productivity jobs. As the Goldman Sachs article linked below states:

Jobs displaced by automation have historically been offset by the creation of new jobs, and the emergence of new occupations following technological innovations accounts for the vast majority of long-run employment growth… For example, information-technology innovations introduced new occupations such as webpage designers, software developers and digital marketing professionals. There were also follow-on effects of that job creation, as the boost to aggregate income indirectly drove demand for service sector workers in industries like healthcare, education and food services.

Nevertheless, people could still lose their jobs before being re-employed elsewhere.

The possible rise in structural unemployment raises the question of retraining provision and its funding and whether workers would be required to undertake such retraining. It also raises the question of whether there should be a universal basic income so that the additional income from AI can be spread more widely. This income would be paid in addition to any wages that people earn. But a universal basic income would require finance. How could AI be taxed? What would be the effects on incentives and investment in the AI industry? The Guardian article, linked below, explores some of these issues.

The increased GDP from AI will lead to higher levels of consumption. The resulting increase in demand for labour will go some way to offsetting the effects of workers being displaced by AI. There may be new employment opportunities in the service sector in areas such as sport and recreation, where there is an emphasis on human interaction and where, therefore, humans have an advantage over AI.

Another issue raised is whether people need to work so many hours. Is there an argument for a four-day or even three-day week? We explored these issues in a recent blog in the context of low productivity growth. The arguments become more compelling when productivity growth is high.

Other issues

AI users are not all benign. As we are beginning to see, AI opens the possibility for sophisticated crime, including cyberattacks, fraud and extortion as the technology makes the acquisition and misuse of data, and the development of malware and phishing much easier.

Another set of issues arises in education. What knowledge should students be expected to acquire? Should the focus of education continue to shift towards analytical skills and understanding away from the simple acquisition of knowledge and techniques. This has been a development in recent years and could accelerate. Then there is the question of assessment. Generative AI creates a range of possibilities for plagiarism and other forms of cheating. How should modes of assessment change to reflect this problem? Should there be a greater shift towards exams or towards project work that encourages the use of AI?

Finally, there is the issue of the sort of society we want to achieve. Work is not just about producing goods and services for us as consumers – work is an important part of life. To the extent that AI can enhance working life and take away a lot of routine and boring tasks, then society gains. To the extent, however, that it replaces work that involved judgement and human interaction, then society might lose. More might be produced, but we might be less fulfilled.

Articles

Questions

  1. Which industries are most likely to benefit from the development of AI?
  2. Distinguish between labour-replacing and labour-augmenting technological progress in the context of AI.
  3. How could AI reduce the amount of labour per unit of output and yet result in an increase in employment?
  4. What people are most likely to (a) gain, (b) lose from the increasing use of AI?
  5. Is the distribution of income likely to become more equal or less equal with the development and adoption of AI? Explain.
  6. What policies could governments adopt to spread the gains from AI more equally?
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A Keynesian route to recovery in output and employment?

Boris Johnson gave a speech on 30 June outlining his government’s approach to recovery from the sharpest recession on record. With the slogan ‘Build, build, build’, he said that infrastructure projects were the key to stimulating the economy. Infrastructure spending is a classic Keynesian response to recession as it stimulates aggregate demand allowing slack to be taken up, while also boosting aggregate supply, thereby allowing recovery in output while increasing potential national income.

A new ‘New deal’

He likened his approach to that of President Franklin D Roosevelt’s New Deal. This was a huge stimulus between 1933 and 1939 in an attempt to lift the US economy out of the Great Depression. There was a massive programme of government spending on construction projects, such as hospitals, schools, roads, bridges and dams, including the Hoover Dam and completing the 113-mile Overseas Highway connecting mainland Florida to the Florida Keys. Altogether, there were 34 599 projects, many large-scale. In addition, support was provided for people on low incomes, the unemployed, the elderly and farmers. Money supply was expanded, made possible by leaving the Gold Standard in 1934.

There was some debate as to whether the New Deal could be classed as ‘Keynesian’. Officially, the administration was concerned to achieve a balanced budget. However, it had a separate ’emergency budget’, from which New Deal spending was financed. According to estimates by the Federal Reserve Bank of St Louis, the total extra spending amounted to nearly 40% of US GDP as it was in 1929.

By comparison with the New Deal, the proposals of the Johnson government are extremely modest. Mostly it amounts to bringing forward spending already committed. The total of £5 billion is just 0.2% of current UK GDP.

Focusing on jobs

A recent report published by the Resolution Foundation, titled ‘The Full Monty‘, argues that as the Job Retention Scheme, under which people have been furloughed on 80% pay, is withdrawn, so unemployment is set to rise dramatically. The claimant count has already risen from 1.2m to 2.8m between March and May with the furlough scheme in place.

Policy should thus focus on job creation, especially in those sectors likely to experience the largest rise in unemployment. Such sectors include non-food retail, hospitality (pubs, restaurants, hotels, etc.), public transport, the arts, entertainment and leisure and a range of industries servicing these sectors. What is more, many of the people working in these sectors are young and low paid. Many will find it difficult to move to jobs elsewhere – partly because of a lack of qualifications and partly because of a lack of alternative jobs. The rising unemployment will raise inequality.

The Resolution Foundation report argues that policy should be focused specifically on job creation.

Policy makers should act now to minimise outflows from the hard-hit sectors – a wage subsidy scheme or a National Insurance cut in those sectors would reduce labour costs and discourage redundancies. Alongside this, the Government must pursue radical action to create jobs across the country, such as in social care and housing retrofitting, and ramp up support for the unemployed.

Dealing with hyteresis

The economy is set to recover somewhat as the lockdown is eased, but it is not expected to return to the situation before the pandemic. Many jobs will be lost permanently unless government support continues.

Even then, many firms will have closed and others will have reassessed how many workers they need to employ and whether less labour-intensive methods would be more profitable. They may take the opportunity to consider whether technology, such as AI, can replace labour; or they may prefer to employ cheap telecommuters from India or the Philippines rather than workers coming into the office.

Policies to stimulate recovery will need to take these hysteresis effects into account if unemployment is to fall back to pre-Covid rates.

Videos

Articles

Report

Questions

  1. What are the arguments for and against substantial increased government expenditure on infrastructure projects?
  2. Should the UK government spend more or less on such projects than the amount already pledged? Justify your answer.
  3. What are the arguments for and against directing all extra government expenditure towards green projects?
  4. Look through the Resolution Foundation report and summarise the findings of each of its sections.
  5. What are the arguments for and against directing all extra government expenditure towards those sectors where there is the highest rate of job losses?
  6. What form could policies to protect employment take?
  7. How should the success of policies to generate employment be measured?
  8. What form does hysteresis play on the post-Covid-19 labour market? What four shocks mean that employment will not simply return to the pre-Covid situation?
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Economists and the real world

Economists are often criticised for making inaccurate forecasts and for making false assumptions. Their analysis is frequently dismissed by politicians when it contradicts their own views.

But is this fair? Have economists responded to the realities of the global economy and to the behaviour of people, firms, institutions and government as they respond to economic circumstances? The answer is a qualified yes.

Behavioural economics is increasingly challenging the simple assumption that people are ‘rational’, in the sense that they maximise their self interest by weighing up the marginal costs and benefits of alternatives open to them. And macroeconomic models are evolving to take account of a range of drivers of global growth and the business cycle.

The linked article and podcast below look at the views of 2019 Nobel Prize-winning economist Esther Duflo. She has challenged some of the traditional assumptions of economics about the nature of rationality and what motivates people. But her work is still very much in the tradition of economists. She examines evidence and sees how people respond to incentives and then derives policy implications from the analysis.

Take the case of the mobility of labour. She examines why people who lose their jobs may not always move to a new one if it’s in a different town. Partly this is for financial reasons – moving is costly and housing may be more expensive where the new job is located. Partly, however, it is for reasons of identity. Many people are attached to where they currently live. They may be reluctant to leave family and friends and familiar surroundings and hope that a new job will turn up – even if it means a cut in wages. This is not irrational; it just means that people are driven by more than simply wages.

Duflo is doing what economists typically do – examining behaviour in the light of evidence. In her case, she is revisiting the concept of rationality to take account of evidence on what motivates people and the way they behave.

In the light of workers’ motivation, she considers the implications for the gains from trade. Is free trade policy necessarily desirable if people lose their jobs because of cheap imports from China and other developing countries where labour costs are low?

The answer is not a clear yes or no, as import-competing industries are only part of the story. If protectionist policies are pursued, other countries may retaliate with protectionist policies themselves. In such cases, people working in the export sector may lose their jobs.

She also looks at how people may respond to a rise or cut in tax rates. Again the answer is not clear cut and an examination of empirical evidence is necessary to devise appropriate policy. Not only is there an income and substitution effect from tax changes, but people are motivated to work by factors other than take-home pay. Likewise, firms are encouraged to invest by factors other than the simple post-tax profitability of investment.

Podcast

Article

Questions

  1. In traditional ‘neoclassical’ economics, what is meant by ‘rationality’ in terms of (a) consumer behaviour; (b) producer behaviour?
  2. How might the concept of rationality be expanded to take into account a whole range of factors other than the direct costs and benefits of a decision?
  3. What is meant by bounded rationality?
  4. What would be the effect on workers’ willingness to work more or fewer hours as a result of a cut in the marginal income tax rate if (a) the income effect was greater than the substitution effect; (b) the substitution effect was greater than the income effect? Would your answers to (a) and (b) be the opposite in the case of a rise in the marginal income tax rate?
  5. Give some arguments that you consider to be legitimate for imposing controls on imports in (a) the short run; (b) the long run. How might you counter these arguments from a free-trade perspective?
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The rise of the machines

What will production look like in 20 years time? Will familiar jobs in both manufacturing and the services be taken over by robots? And if so, which ones? What will be the effect on wages and on unemployment? Will most people be better off, or will just a few gain while others get by with minimum-wage jobs or no jobs at all?

The BBC has been running a series looking at new uses for robots and whether they will take people’s jobs? This complements three reports: one by Boston Consulting one by Deloitte and an earlier one by Deloitte and Michael Osborne and Carl Frey from Oxford University’s Martin School. As Jane Wakefield, the BBC’s technology reporter states:

Boston Consulting Group predicts that by 2025, up to a quarter of jobs will be replaced by either smart software or robots, while a study from Oxford University has suggested that 35% of existing UK jobs are at risk of automation in the next 20 years.

Jobs at threat from machines include factory work, office work, work in the leisure sector, work in medicine, law, education and other professions, train drivers and even taxi and lorry drivers. At present, in many of these jobs machines work alongside humans. For example, robots on production lines are common, and robots help doctors perform surgery and provide other back-up services in medicine.

A robot may not yet have a good bedside manner but it is pretty good at wading through huge reams of data to find possible treatments for diseases.

Even if robots don’t take over all jobs in these fields, they are likely to replace an increasing proportion of many of these jobs, leaving humans to concentrate on the areas that require judgement, creativity, human empathy and finesse.

These developments raise a number of questions. If robots have a higher marginal revenue product/marginal cost ratio than humans, will employers choose to replace humans by robots, wholly or in part? How are investment costs factored into the decision? And what about industrial relations? Will employers risk disputes with employees? Will they simply be concerned with maximising profit or will they take wider social concerns into account?

Then there is the question of what new jobs would be created for those who lose their jobs to machines. According to the earlier Deloitte study, which focused on London, over 80% of companies in London say that over the next 10 years they will be most likely to take on people with skills in ‘digital know-how’, ‘management’ and ‘creativity’.

But even if new jobs are created through the extra spending power generated by the extra production – and this has been the pattern since the start of the industrial revolution some 250 years ago – will these new jobs be open largely to those with high levels of transferable skills? Will the result be an ever widening of the income gap between rich and poor? Or will there be plenty of new jobs throughout the economy in a wide variety of areas where humans are valued for the special qualities they bring? As the authors of the later Deloitte paper state:

The dominant trend is of contracting employment in agriculture and manufacturing being more than offset by rapid growth in the caring, creative, technology and business services sectors.

The issues of job replacement and job creation, and of the effects on income distribution and the balance between work and leisure, are considered in the following videos and articles, and in the three reports.

Videos

What is artificial intelligence? BBC News, Valery Eremenko (13/9/15)
What jobs will robots take over? BBC News, David Botti (15/8/14)
Could a robot do your job? BBC News, Rory Cellan-Jones (14/9/15)
Intelligent machines: The robots that work alongside humans BBC News, Rory Cellan-Jones (14/9/15)
Intelligent machines: Will you be replaced by a robot? BBC News, John Maguire (14/9/15)
Will our emotions change the way adverts work? BBC News, Dan Simmons (24/7/15)
Could A Robot Do My Job? BBC Panorama, Rohan Silva (14/9/15)

Articles

Technology has created more jobs in the last 144 years than it has destroyed, Deloitte study finds Independent, Doug Bolton (18/8/15)
Technology has created more jobs than it has destroyed, says 140 years of data The Guardian, Katie Allen (18/8/15)
Will a robot take your job? BBC News (11/9/15)
Intelligent Machines: The jobs robots will steal first BBC News, Jane Wakefield (14/9/15)
Robots Could Take 35 Per Cent Of UK Jobs In The Next 20 Years Says New Study Huffington Post, Thomas Tamblyn (14/9/15)
The new white-collar fear: will robots take your job? The Telegraph, Rohan Silva (12/9/15)
Does technology destroy jobs? Data from 140 years says no Catch news, Sourjya Bhowmick (11/9/15)

Reports

Takeoff in Robotics Will Power the Next Productivity Surge in Manufacturing Boston Consulting Group (10/2/15)
Agiletown: the relentless march of technology and London’s response Deloitte (November 2014)
Technology and people: The great job-creating machine Deloitte, Ian Stewart, Debapratim De and Alex Cole (August 2015)

Questions

  1. Which are the fastest growing and fastest declining occupations? To what extent can these changes be explained by changes in technology?
  2. What type of unemployment is caused by rapid technological change?
  3. Why, if automation replaces jobs, have jobs increased over the past 250 years?
  4. In what occupations is artificial intelligence (AI) most likely to replace humans?
  5. To what extent are robots and humans complementary rather than substitute inputs into production?
  6. “Our analysis of more recent employment data also reveals a clear pattern to the way in which technology has affected work.” What is this pattern? Explain.
  7. Why might AI make work more interesting for workers?
  8. Using a diagram, show how an increase in workers’ marginal productivity from working alongside robots can result in an increase in employment. Is this necessarily the case? Explain.
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Job losses and labour mobility

Lloyds Banking Group has announced that it plans to reduce its labour force by 9000. Some of this reduction may be achieved by not replacing staff that leave, but some may have to be achieved through redundancies.

The reasons given for the reduction in jobs are technological change and changes in customer practice. More banking services are available online and customers are making more use of these services and less use of branch banking. Also, the increasingly widespread availability of cash machines (ATMs) means that fewer people withdraw cash from branches.

And it’s not just outside branches that technological change is impacting on bank jobs. Much of the work previously done by humans is now done by software programs.

One result is that many bank branches have closed. Lloyds says that the latest planned changes will see 150 fewer branches – 6.7% of its network of 2250.

What’s happening in banking is happening much more widely across modern economies. Online shopping is reducing the need for physical shops. Computers in offices are reducing the need, in many cases, for office staff. More sophisticated machines, often controlled by increasingly sophisticated computers, are replacing jobs in manufacturing.

So is this bad news for employees? It is if you are in one of those industries cutting employment. But new jobs are being created as the economy expands. So if you have a good set of skills and are willing to retrain and possibly move home, it might be relatively easy to find a new, albeit different, job.

As far as total unemployment is concerned, more rapid changes in technology create a rise in frictional and structural unemployment. This can be minimised, however, or even reduced, if there is greater labour mobility. This can be achieved by better training, education and the development of transferable skills in a more adaptive labour force, where people see changing jobs as a ‘normal’ part of a career.

Webcasts

Lloyds Bank cuts 9,000 jobs – but what of the tech future? Channel 4 News, Symeon Brown (28/10/14)
Lloyds Bank confirms 9,000 job losses and branch closures BBC News, Kamal Ahmed (28/10/14)

Article

Lloyds job cuts show the technology axe still swings for white collar workers The Guardian, Phillip Inman (28/10/14)

Reports

Unleashing Aspiration: The Final Report of the Panel on Fair Access to the Professions Cabinet Office (July 2009)
Fair access to professional careers: a progress report Cabinet Office (30/5/12)

Questions

  1. Is a reduction in banking jobs inevitable? Explain.
  2. What could banks do to reduce the hardship to employees from a reduction in employment?
  3. What other industries are likely to see significant job losses resulting from technological progress?
  4. Distinguish between demand-deficient, real-wage, structural and frictional unemployment. Which of these are an example, or examples, of equilibrium unemployment?
  5. What policies could the government pursue to reduce (a) frictional unemployment; (b) structural unemployment?
  6. What types of industry are likely to see an increase in employment and in what areas of these industries?