Category: Economics: Ch 09

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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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The increasing use of dynamic pricing strategies

In September 2023, the Stonegate Group, the largest pub company in the UK with around 4,500 premises, announced that it was going to start increasing the pint of beer by 20p during busy periods. There was an immediate backlash on social media with many customers calling on people to boycott Stonegate’s pubs such as the Slug & Lettuce and Yates.

This announcement is an example of dynamic pricing, where firms with market power adjust prices relatively quickly in response to changing market conditions: i.e. to changes in demand and supply.

Traditionally, prices set by firms in most retail markets have been less flexible. They may eventually adjust to changing market conditions, but this could take weeks or even months. If a product proves to be popular on a particular day or time, firms have typically left the price unchanged with the item selling out and customers facing empty shelves. If the product is unpopular, then the firm is left with unsold stock.

One business that makes extensive use of dynamic pricing is Amazon. Prices for popular items on Amazon Marketplace change every 10 minutes and can fluctuate by more than 20 per cent in just one hour.

Conditions for dynamic pricing to operate

The Amazon example helps to illustrate the conditions that must be in place for a firm to implement dynamic pricing successfully. These include:

  • The capacity to collect and process large amounts of accurate real-time data on the demand for and supply of particular items i.e. the number of sales or the interest in the product.
  • The ability to adjust prices in a timely manner in response to changing market conditions indicated by the data.
  • Effectively communicating the potential advantages of the pricing strategy to consumers.

Consumer attitudes

The last point is an interesting one. As the Stonegate example illustrates, consumers tend to dislike dynamic pricing, especially when price rises reflect increases in demand. A previous article on this website discussed the unpopularity of dynamic pricing amongst fans in the ticket market for live musical events.

The precise reason for the increase in demand, can also have an impact on consumer attitudes. For example, following a mass shooting at a subway station in New York in April 2022, the authorities shut down the underground system. This led to a surge in demand for taxis and this was picked up by the algorithm/software used by Uber’s dynamic pricing system. Fares for Uber cars began to rise rapidly, and people started to post complaints on social media. Uber responded by disabling the dynamic pricing system and capping prices across the city. It also announced that it would refund customers who were charged higher prices after the subway system shut down.

There is a danger for businesses that if they fail to communicate the policy effectively, annoyed customers may respond by shopping elsewhere. However, if it is implemented successfully then it can help businesses to increase their revenue and may also have some advantages for consumers.

The growing popularity of dynamic pricing

It has been widely used in airline and hotel industries for many years. Robert Cross, who chairs a revenue management company predicts that ‘It will eventually be everywhere’.

More businesses in the UK appear to be using dynamic pricing. In a consumer confidence survey undertaken for Barclays in September 2023, 47 per cent of the respondents had noticed more examples of companies raising prices for goods/services in response to higher demand at peak times.

It has traditionally been more difficult for bricks-and-mortar retailers to implement dynamic pricing because of the costs of continually changing prices (so-called ‘menu costs’). However, this might change with the increasing use of electronic shelf labels.

It will be interesting to see if dynamic pricing becomes more widespread in the future or whether opposition from consumers limits its use.

Articles

Questions

  1. Explain the difference between surge and dynamic pricing.
  2. Using a diagram, explain how dynamic pricing can increase a firm’s revenue.
  3. Discuss both the advantages and disadvantages for consumers of firms using dynamic pricing.
  4. How might dynamic pricing influence consumer behaviour if it alters their expectations about future price changes.
  5. There is some evidence that the use of dynamic pricing is less unpopular amongst 18–24-year-olds than other age groups. Suggest some possible reasons why this might be the case.
  6. Using the concept of loss aversion, consider some different ways that a business could present a new dynamic pricing policy to its customers.
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Good COP and bad COP: reflections on the Glasgow climate change conference


The Climate Change Pact agreed by leaders at the end of COP26 in Glasgow went further than many pessimists had forecast, but not far enough to meet the goal of keeping global warming to 1.5°C above pre-industrial levels. The Pact states that:

limiting global warming to 1.5°C requires rapid, deep and sustained reductions in global greenhouse gas emissions, including reducing global carbon dioxide emissions by 45 per cent by 2030 relative to the 2010 level and to net zero around mid-century, as well as deep reductions in other greenhouse gases.

So how far would the commitments made in Glasgow restrict global warming and what actions need to be put in place to meet these commitments?

Short-term commitments and long-term goals

According to Climate Action Tracker, the short-term commitments to action that countries set out would cause global warming of 2.4°C by the end of the century, the effects of which would be calamitous in terms of rising sea levels and extreme weather.

However, long-term commitments to goals, as opposed to specific actions, if turned into specific actions to meet the goals would restrict warming to around 1.8°C by the end of the century. These long-term goals include reaching net zero emissions by certain dates. For the majority of the 136 countries agreeing to reach net zero, the date they set was 2050, but for some developing countries, it was later. China, Brazil, Indonesia, Russia, Nigeria, Sri Lanka and Saudi Arabia, for example, set a date of 2060 and India of 2070. Some countries set an earlier target and others, such as Benin, Bhutan, Cambodia, Guyana, Liberia and Madagascar, claimed they had already reached zero net emissions.

Despite these target dates, Climate Action Tracker argues that only 6 per cent of countries pledging net zero have robust policies in place to meet the targets. The problem is that actions are required by firms and individuals. They must cut their direct emissions and reduce the consumption of products whose production involved emissions.

Governments can incentivise individuals and firms through emissions and product taxes, through carbon pricing, through cap-and-trade schemes, through subsidies on green investment, production and consumption, through legal limits on emissions, through trying to change behaviour by education campaigns, and so on. In each case, the extent to which individuals and firms will respond is hard to predict. People may want to reduce global warming and yet be reluctant to change their own behaviour, seeing themselves as too insignificant to make any difference and blaming big business, governments or rich individuals. It is important, therefore, for governments to get incentive mechanisms right to achieve the stated targets.

Let us turn to some specific targets specified in the Climate Change Pact.

Phasing out fossil fuel subsidies

Paragraph 20 of the Climate Change Pact

Calls upon Parties to accelerate … efforts towards the … phase-out of inefficient fossil fuel subsidies, while providing targeted support to the poorest and most vulnerable in line with national circumstances and recognizing the need for support towards a just transition.

Production subsidies include tax breaks or direct payments that reduce the cost of producing coal, oil or gas. Consumption subsidies cut fuel prices for the end user, such as by fixing the price at the petrol pump below the market rate. They are often justified as a way of making energy cheaper for poorer people. In fact, they provide a bigger benefit to wealthier people, who are larger users of energy. A more efficient way of helping the poor would be through benefits or general tax relief. Removing consumption subsidies in 32 countries alone would, according to International Institute for Sustainable Development, cut greenhouse gas emission by an average of 6 per cent by 2025.

The chart shows the 15 countries providing the largest amount of support to fossil fuel industries in 2020 (in 2021 prices). The bars are in billions of dollars and the percentage of GDP is also given for each country. Subsidies include both production and consumption subsidies. (Click here for a PowerPoint of the chart.) In addition to the direct subsidies shown in the chart, there are the indirect costs of subsidies, including pollution, environmental destruction and the impact on the climate. According to the IMF, these amounted to $5.4 trillion in 2020.

But getting countries to agree on a path to cutting subsidies, when conditions vary enormously from one country to another, proved very difficult.

The first draft of the conference agreement called for countries to ‘to accelerate the phasing-out of coal and subsidies for fossil fuels’. But, after objections from major coal producing countries, such as China, India and Australia, this was weakened to calling on countries to accelerate the shift to clean energy systems ‘by scaling up the deployment of clean power generation and energy efficiency measures, including accelerating efforts towards the phasedown of unabated coal power and phase-out of inefficient fossil fuel subsidies’. (‘Unabated’ coal power refers to power generation with no carbon capture.) Changing ‘phasing-out’ to ‘the phasedown’ caused consternation among many delegates who saw this as a substantial weakening of the drive to end the use of coal.

Another problem is in defining ‘inefficient’ subsidies. Countries are likely to define them in a way that suits them.

The key question was the extent to which countries would actually adopt such measures and what the details would be. Would they be strong enough? This remained to be seen.

As an article in the journal, Nature, points out:

There are three main barriers to removing production subsidies … First, fossil-fuel companies are powerful political groups. Second, there are legitimate concerns about job losses in communities that have few alternative employment options. And third, people often worry that rising energy prices might depress economic growth or trigger inflation.

The other question with the phasing out of subsidies is how and how much would there be ‘targeted support to the poorest and most vulnerable in line with national circumstances’.

Financial support for developing countries

Transitioning to a low-carbon economy and investing in measures to protect people from rising sea levels, floods, droughts, fires, etc. costs money. With many developing countries facing serious financial problems, especially in the light of measures to support their economies and healthcare systems to mitigate the effects of COVID-19, support is needed from the developed world.

In the COP21 Paris Agreement in 2015, developed countries pledged $100 billion by 2020 to support mitigation of and adaptation to the effects of climate change by developing countries. But the target was not reached. The COP26 Pact urged ‘developed country Parties to fully deliver on the $100 billion goal urgently and through to 2025’. It also emphasised the importance of transparency in the implementation of their pledges. The proposal was also discussed to set up a trillion dollar per year fund from 2025, but no agreement was reached.

It remains to be seen just how much support will be given.

Then there was the question of compensating developing countries for the loss and damage which has already resulted from climate change. Large historical polluters, such as the USA, the UK and various EU countries, were unwilling to agree to a compensation mechanism, fearing that any recognition of culpability could make them open to lawsuits and demands for financial compensation.

Other decisions

  • More than 100 countries at the meeting agreed to cut global methane emissions by at least 30 per cent from 2020 levels by 2030. Methane is a more powerful but shorter-living greenhouse gas than carbon. It is responsible for about a third of all human-generated global warming. China, India and Russia, however, did not sign up.
  • Again, more than 100 countries agreed to stop deforestation by 2030. These countries include Indonesia and Brazil, which has been heavily criticised for allowing large parts of the Amazon rainforest to be cleared for farming, such that the Amazon region in recent years has been a net emitter of carbon from the felling and burning of trees. The pledge has been met with considerable cynicism, however, as it unclear how it will be policed. Much of the deforestation around the world is already illegal but goes ahead anyway.
  • A mechanism for trading carbon credits was agreed. This allows countries which plant forests or build wind farms to earn credits. However, it may simply provide a mechanism for rich countries and businesses to keep emitting as usual by buying credits.
  • Forty-five countries pledged to invest in green agricultural practices to make farming more sustainable.
  • Twenty-two countries signed a declaration to create zero-emission maritime shipping routes.
  • The USA and China signed a joint declaration promising to boost co-operation over the next decade on various climate actions, including reducing methane emissions, tackling deforestation and regulating decarbonisation.

Blah, blah, blah or real action?

Many of the decisions merely represent targets. What is essential is for countries clearly to spell out the mechanisms they will use for achieving them. So far there is too little detail. It was agreed, therefore, to reconvene in a year’s time at COP27 in Egypt. Countries will be expected to spell out in detail what actions they are taking to meet their emissions targets and other targets such as ending deforestation and reducing coal-fired generation.

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Questions

  1. What were the main achievements of COP26?
  2. What were the main failings of COP26?
  3. How can people be incentivised to reduce their direct and indirect greenhouse gas emissions?
  4. How is game theory relevant to understanding the difficulties in achieving global net zero emissions?
  5. Should developing countries be required to give up coal power?
  6. If the world is to achieve net zero greenhouse gas emissions, should all countries achieve net zero or should some countries achieve net negative emissions to allow others to continue with net positive emissions (albeit at a lower level)?
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Hacking capitalism

The development of open-source software and blockchain technology has enabled people to ‘hack’ capitalism – to present and provide alternatives to traditional modes of production, consumption and exchange. This has enabled more effective markets in second-hand products, new environmentally-friendly technologies and by-products that otherwise would have been negative externalities. Cryptocurrencies are increasingly providing the medium of exchange in such markets.

In a BBC podcast, Hacking Capitalism, Leo Johnson, head of PwC’s Disruption Practice and younger brother of Boris Johnson, argues that various changes to the way capitalism operates can make it much more effective in improving the lives of everyone, including those left behind in the current world. The changes can help address the failings of capitalism, such as climate change, environmental destruction, poverty and inequality, corruption, a reinforcement of economic and political power and the lack of general access to capital. And these changes are already taking place around the world and could lead to a new ‘golden age’ for capitalism.

The changes are built on new attitudes and new technologies. New attitudes include regarding nature and the land as living resources that need respect. This would involve moving away from monocultures and deforestation and, with appropriate technologies (old and new), could lead to greater output, greater equality within agriculture and increased carbon absorption. The podcast gives examples from the developing and developed world of successful moves towards smaller-scale and more diversified agriculture that are much more sustainable. The rise in farmers’ markets provides an important mechanism to drive both demand and supply.

In the current model of capitalism there are many barriers to prevent the poor from benefiting from the system. As the podcast states, there are some 2 billion people across the world with no access to finance, 2.6 billion without access to sanitation, 1.2 billion without access to power – a set of barriers that stops capitalism from unlocking the skills and productivity of the many.

These problems were made worse by the response to the financial crisis of 2007–8, when governments chose to save the existing model of capitalism by propping up financial markets through quantitative easing, which massively inflated asset prices and aggravated the problem of inequality. They missed the opportunity of creating money to invest in alternative technologies and infrastructure.

New technology is the key to developing this new fairer, more sustainable model of capitalism. Such technologies could be developed (and are being in many cases) by co-operative, open-source methods. Many people, through these methods, could contribute to the development of products and their adaptation to meet different needs. The barriers of intellectual property rights are by-passed.

New technologies that allow easy rental or sharing of equipment (such as tractors) by poor farmers can transform lives and massively increase productivity. So too can the development of cryptocurrencies to allow access to finance for small farmers and businesses. This is particularly important in countries where access to traditional finance is restricted and/or where the currency is not stable with high inflation rates.

Blockchain technology can also help to drive second-hand markets by providing greater transparency and thereby cut waste. Manufacturers could take a stake in such markets through a process of certification or transfer.

A final hack is one that can directly tackle the problem of externalities – one of the greatest weaknesses of conventional capitalism. New technologies can support ways of rewarding people for reducing external costs, such as paying indigenous people for protecting the land or forests. Carbon markets have been developed in recent years. Perhaps the best example is the European Emissions Trading Scheme (EMS). But so far they have been developed in isolation. If the revenues generated could go directly to those involved in environmental protection, this would help further to internalise the externalities. The podcasts gives an example of a technology used in the Amazon to identify the environmental benefits of protecting rain forests that can then be used to allow reliable payments to the indigenous people though blockchain currencies.

Podcast

Questions

  1. What are the main reasons why capitalism has led to such great inequality?
  2. What do you understand by ‘hacking’ capitalism?
  3. How is open-source software relevant to the development of technology that can have broad benefits across society?
  4. Does the current model of capitalism encourage a self-centred approach to life?
  5. How might blockchain technology help in the development of a more inclusive and fairer form of capitalism?
  6. How might farmers’ co-operatives encourage rural development?
  7. What are the political obstacles to the developments considered in the podcast?
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Apple v Fortnite

Competition authorities across the globe have recently been paying close attention to the activity of large firms in high-tech markets, in particular Google, Amazon, Facebook and Apple. One estimate suggests that 30 cases have been opened by the authorities since 2010, and a third of these were launched in 2020.

One of the most prominent recent cases in the US courts concerns a complaint made by Epic Games, producer of the popular Fortnite game, against Apple. The background to the case is Apple’s standard practice on its App Store of taking a 30% cut of all paid app and in-app purchases. Therefore, a Fortnite player purchasing $10 worth of in-game currency would result in $7 for Epic and $3 for Apple.

However, in August 2020 Epic decided, contrary to Apple’s terms and conditions, to offer players an alternative way to purchase in-game currency. Gamers would see a choice screen giving them the option to buy currency through the Apple App Store or to buy it directly from Epic. Crucially, purchasing directly from Epic would be cheaper. For example, the same $10 worth of in-game currency on the App Store would cost only $8 if purchased directly from Epic.

It is clear to see why Epic was in favour of direct payments – it earns revenue of $8 instead of $7. However, note that the benefits for gamers are even larger – they save $2 by buying directly. In other words, Epic is passing on 2/3 of the cost saving to consumers.

Apple very quickly responded to Epic’s introduction of the direct purchase alternative by removing Fortnite from the App Store. Epic then filed a complaint with the US District Court.

The Epic v Apple court case

The case concerned Apple restricting game developers’ ability to promote purchasing mechanisms outside the App Store. However, more broadly, it also examined Apple’s complete control of the iOS app market since all apps must be distributed through the Apple App Store. Epic had previously disrupted PC games distribution by launching its own platform with lower fees. The setup of iOS and Apple’s actions against Epic make this an impossible way to reach users.

The Court’s analysis of the Epic v Apple case depended upon several key factors. First, the market definition. To be found to have breached competition law Apple must have a significant share of the market. If the market is defined as that for iOS apps, this is clearly the case. However, if, as Apple argues, it is broader, encompassing the options to play Epic games through web browsers, gaming consoles and PCs, then this is not the case.

Second, even if the market is narrowly defined, Apple argues that its control of the app distribution market is essential to provide user friendly and secure provision of apps. Furthermore, revenue extracted from app producers can enable more investment in the iOS. Without Apple controlling the market, app producers would be able to free-ride on the visibility the App Store provides for their apps.

The ruling

The US Court announced its ruling on 10 September 2021. The judge decided that the market was broader than just iOS and thus Apple is not considered to be a monopolist. This has been touted as a major success for Apple, as it will allow the company to maintain its control of the app distribution market. However, the Court also ruled that Apple must allow game developers to link and direct users to alternative purchasing methods outside the App Store.

The Court’s decision in the Epic v Apple case closely follows concessions recently made by Apple for so called ‘reader apps’ such as Spotify and Netflix. Following an investigation by the Japanese authorities, these concessions allowed such apps to promote and receive purchases directly from consumers as long as they were made outside the app. These apps could be treated differently, as digital goods are consumed on multiple devices. However, the decision in the Epic case now extends such concessions to gaming apps.

It is unclear whether Apple will appeal the decision in the case Epic brought. If not, Apple stands to lose considerable revenue from its 30% share of in-app purchases. It will be very interesting to see how this ruling affects how Apple runs the App Store. Epic, on the other hand, has already made clear it will appeal the decision, aiming to prevent Apple gaining a share of any payment users make outside the app.

Matt Olczak and Jon Guest

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Questions

  1. Why might a firm involved in a competition case, such as Apple, try to convince the authorities to define the relevant market as broadly as possible?
  2. Using the example of the Epic v Apple case, explain how Apple’s actions could be seen as both exclusionary and exploitative abuses of a dominant position.