Tag: frictional unemployment

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Will AI make the world less equal?

With businesses increasing their use of AI, this is likely to have significant effects on employment. But how will this affect the distribution of income, both within countries and between countries?

In some ways, AI is likely to increase inequality within countries as it displaces low-skilled workers and enhances the productivity of higher-skilled workers. In other ways, it could reduce inequality by allowing lower-skilled workers to increase their productivity, while displacing some higher-skilled workers and managers through the increased adoption of automated processes.

The effect of AI on the distribution of income between countries will depend crucially on its accessibility. If it is widely available to low-income countries, it could significantly enhance the productivity of small businesses and workers in such countries and help to reduce the income gap with the richer world. If the gains in such countries, however, are largely experienced by multinational companies, whether in mines and plantations, or in labour-intensive industries, such as garment production, few of the gains may accrue to workers and global inequality may increase.

Redistribution within a country

The deployment of AI may result in labour displacement. AI is likely to replace both manual and white-collar jobs that involve straightforward and repetitive tasks. These include: routine clerical work, such as data entry, filing and scheduling; paralegal work, contract drafting and legal research; consulting, business research and market analysis; accounting and bookkeeping; financial trading; proofreading, copy mark-up and translation; graphic design; machine operation; warehouse work, where AI-enabled warehouse robots do many receiving, sorting, stacking, retrieval, carrying and loading tasks (e.g. Amazon’s Sequoia robotic system); basic coding or document sifting; market research and advertising design; call-centre work, such as enquiry handling, sales, telemarketing and customer service; hospitality reception; sales cashiers in supermarkets and stores; analysis of health data and diagnosis. Such jobs can all be performed by AI assistants, AI assisted robots or chat bots.

Women are likely to be disproportionately affected because they perform a higher share of the administrative and service roles most exposed to AI.

Workers displaced by AI may find that they can find employment only in lower-paid jobs. Examples include direct customer-facing roles, such as bar staff, shop assistants, hairdressers and nail and beauty consultants.

Such job displacement by AI is likely to redistribute income from relatively low-skilled labour to capital: a redistribution from wages to profits. This will tend to lead to greater inequality.

AI is also likely to lead to a redistribution of income towards certain types of high-skilled labour that are difficult to replace with AI but which could be enhanced by it. Take the case of skilled traders, such as plumbers, electricians and carpenters. They might be able to use AI in their work to enhance their productivity, through diagnosis, planning, problem-solving, measurement, etc. but the AI would not displace them. Instead, it could increase their incomes by allowing them to do their work more efficiently or effectively and thus increase their output per hour and enhance their hourly reward. Another example is architecture, where AI can automate repetitive tasks and open up new design possibilities, allowing architects to focus on creativity, flexibility, aesthetics, empathy with clients and ethical decision-making.

An important distinction is between disembodied and embodied AI investment. Disembodied AI investment could include AI ‘assistants’, such as ChatGPT and other software that can be used in existing jobs to enhance productivity. Such investment can usually be rolled out relatively quickly. Although the extra productivity may allow some reduction in the number of workers, disembodied AI investment is likely to be less disruptive than embodied AI investment. The latter includes robotics and automation, where workers are replaced by machines. This would require more investment and may be slower to be adopted.

Then there are jobs that will be created by AI. These include prompt engineers, who develop questions and prompt techniques to optimise AI output; health tech experts, who help organisations implement new medical AI products; AI educators, who train people in the uses of AI in the workplace; ethics advisors, who help companies ensure that their uses of AI are aligned with their values, responsibilities and goals; and cybersecurity experts who put systems in place to prevent AI stealing sensitive information. Such jobs may be relatively highly paid.

In other cases, the gains from AI in employment are likely to accrue mainly to the consumer, with probably little change in the incomes of the workers themselves. This is particularly the case in parts of the public sector where wages/salaries are only very loosely related to productivity and where a large part of the work involves providing a personal service. For example, health professionals’ productivity could be enhanced by AI, which could allow faster and more accurate diagnosis, more efficient monitoring and greater accuracy in surgery. The main gainers would be the patients, with probably little change in the incomes of the health professionals themselves. Teachers’ productivity could be improved by allowing more rapid and efficient marking, preparation of materials and record keeping, allowing more time to be spent with students. Again, the main gainers would be the students, with little change in teachers’ incomes. Other jobs in this category include social workers, therapists, solicitors and barristers, HR specialists, senior managers and musicians.

Thus there is likely to be a distribution away from lower-skilled workers to both capital and higher-skilled workers who can use AI, to people who work in new jobs created by AI and to the consumers of certain services.

AI will accelerate productivity growth and, with it, GDP growth, but will probably displace workers faster than new roles emerge. This is likely to increase inequality and be a major challenge for society. Can the labour market adapt? Could the effects be modified if people moved to a four- or three-day week? Will governments introduce statutory limits to weekly working hours? Will training and education adapt to the new demands of employers?

Redistribution between countries

AI threatens to widen the global rich–poor divide. It will give wealthier nations a productivity and innovation edge, which could displace low-skilled jobs in low-income nations. Labour-intensive production could be replaced by automated production, with the capital owned by the multinational companies of just a few countries, such as the USA and China, which between them account for 40% of global corporate AI R&D spending. For some companies, it would make sense to relocate production to rich countries, or certain wealthier developing countries, with better digital infrastructure, advanced data systems and more reliable power supply.

For other companies, however, production might still be based in low-income countries to take advantage of low-cost local materials. But there would still be a redistribution from wages in such countries to the profits of multinationals.

But it is not just in manufacturing where low-income countries are vulnerable to the integration of AI. Several countries, such as India, the Philippines, Mexico and Egypt have seen considerable investment in call centres and IT services for business process outsourcing and customer services. AI now poses a threat to employment in this industry as it has the potential to replace large numbers of workers.

AI-related job losses could exacerbate unemployment and deepen poverty in poorer countries, which, with limited resources, limited training and underdeveloped social protection systems, are less equipped to absorb economic and social shocks. This will further widen the global divide. In the case of embodied AI investment, it may only be possible in low-income countries through multinational investment and could displace many traditional jobs, with much of the benefit going in additional multinational profit.

But it is not all bad news for low-income countries. AI-driven innovations in healthcare, education, and agriculture, if adopted in poor countries, can make a significant contribution to raising living standards and can slow, or even reverse, the widening gap between rich and poor nations. Some of the greatest potential is in small-scale agriculture. Smallholders can boost crop yields though precision farming powered by AI; AI tools can help farmers buy seeds, fertilisers and animals and sell their produce at optimum times and prices; AI-enabled education tools can help farmers learn new techniques.

Articles

Questions

  1. What types of job are most vulnerable to AI?
  2. How will AI change the comparative advantage of low-income countries and what effect will it be likely to have on the pattern of global trade?
  3. Assess alternative policies that governments in high-income countries can adopt to offset the growth in inequality caused by the increasing use of AI.
  4. What policies can governments in low-income countries or aid agencies adopt to offset the growth in inequality within low-income countries and between high- and low-income countries?
  5. How might the growth of AI affect your own approach to career development?
  6. Is AI likely to increase or decrease economic power? Explain.
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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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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?
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A way out of the poverty trap?

On November 11, the government published a White Paper on welfare reform. Central to the proposals is the replacing of the range of out-of-work benefits, housing benefit and tax credits with a single universal benefit. The system will be introduced for new claimants in 2013 and for those currently on benefits sometime after 2015.

When the unemployed find work, the benefit will be withdrawn at a rate of 65p of each £1 earned. At present, because of the complexity of the system, some claimants on multiple benefits can find that the withdrawal rate is almost 100%. When income tax is added in, the tax-plus-lost-benefit rate does sometimes exceed 100%. Thus some people find themselves in a poverty trap, whereby it’s not worth getting a job. It’s financially benefical to stay on benefits.

The other crucial element of the proposal is to deny people benefits who turn down a legitimate job.

a. Failure to meet a requirement to prepare for work (applicable to jobseekers and those in the Employment and Support Allowance Work-Related Activity Group) will lead to 100 per cent of payments ceasing until the recipient re-complies with requirements and for a fixed period after re-compliance (fixed period sanctions start at one week, rising to two, then four weeks with each subsequent failure to comply).

b. Failure to actively seek employment or be available for work will lead to payment ceasing for four weeks for a first failure and up to three months for a second.

c. The most serious failures that apply only to jobseekers will lead to Jobseeker’s Allowance payment ceasing for a fixed period of at least three months (longer for repeat offences). Actions that could trigger this level of penalty include failure to accept a reasonable job offer, failure to apply for a job or failure to attend Mandatory Work Activity.

The following podcasts and articles look at the details of the proposals and discuss their merits and drawbacks,

Podcasts and webcasts
Not going to work if you can is ‘not an option’ ITV, part of speech by Iain Duncan Smith (11/11/10)
IDS: Staying on benefits ‘irrational choice’ BBC Today Programme, Chris Buckler, Iain Duncan Smith Smith (11/11/10)
Iain Duncan Smith unveils new benefits system BBC News (11/11/10)
Welfare reform success ‘far from certain’ BBC Today Programme, Norman Smith (11/11/10)

Articles
Benefits system overhaul ‘to make work pay’ BBC News (11/11/10)
At-a-glance: Benefits overhaul BBC News (11/11/10)
Benefits explained: A basic guide to entitlements BBC News (11/11/10)
Is welfare reform doomed to fail? BBC News, Norman Smith (11/11/10)
A bold and principled approach to benefits Telegraph (11/11/10)
Reshaping the benefits system The Economist, Blighty blog (11/11/10)
Unemployment benefits shake-up ‘a fair deal’ Independent (11/11/10)
Tougher welfare sanctions spark ‘destitution’ warnings Independent (11/11/10)
Iain Duncan Smith: it’s a sin that people fail to take up work Guardian, Patrick Wintour, Randeep Ramesh and Hélène Mulholland (11/11/10)
Preacher Duncan Smith aims for holy grail of welfare policy Guardian, Randeep Ramesh (11/11/10)

Documents, official information and data
Universal Credit: welfare that works Department for Work and Pensions, Links to White Paper (11/11/10)
Benefits and financial support Directgov
Economic and Labour Market Review (see tables in Chapters 2 and 6), National Statistics

Questions

  1. Explain what is meant by the ‘poverty trap’ (or ‘welfare trap’).
  2. Summarise the reforms to benefits proposed in the White Paper.
  3. Examine whether the Coalition government’s proposal for a universal benefit will lead to greater fairness.
  4. Will a withdrawal rate of 65% provide a strong incentive for people out of work to take a job?
  5. Why may some be paying a combined tax-plus-lost-benefit rate of 76%?
  6. Why is there an inherent trade-off between making work pay (and thus eliminating the poverty trap) and keeping the cost of welfare benefits down? Would reducing the level of benefit be an appropriate answer to this trade-off?
  7. One aim of the benefits reform is to reduce unemployment. What type of unemployment is likely to be affected?
  8. Find out the current level of unemployment and the level of job vacancies and, in the light of this, comment on the likely effectiveness of the policy in reducing unemployment (a) shortly after the new system is introduced; (b) over the longer term.