Category: Economics: Ch 12

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AI: benefits but catastrophic risk



Artificial intelligence (AI) has become a key technology in the 21st Century. Businesses use AI systems to analyse data, automate routine tasks, improve customer service, write software, create content and even assist with decision-making. As AI improves and becomes even more capable, governments, economists, businesses and society are debating its effects on productivity, employment and economic growth – and also its potentially extreme dangers.

Some commentators compare AI to earlier technological revolutions such as the steam engine, electricity and the Internet. They argue that AI will continue to increase productivity, create new industries and improve living standards. Others worry that AI may eliminate a large numbers of jobs, increase inequality, concentrate economic power in a few firms and, in the most extreme scenarios, pose a threat to humanity itself.

These debates raise important questions including how society should evaluate the potential risks of a technology whose benefits may be enormous but whose long-term consequences remain uncertain.

AI and the labour market

Historically, technological change has had both positive and negative effects on employment. Automation reduced the demand for many agricultural workers, while creating jobs in manufacturing. Computers automated clerical tasks but generated entirely new industries in software, telecommunications and digital services.

AI appears likely to follow a similar pattern. According to the World Economic Forum, advances in AI, robotics and information-processing technologies are expected to transform labour markets significantly during the second half of the 2020s, creating demand for new skills while reducing demand for others. The fastest-growing skills are expected to include AI and big data, technological literacy and cybersecurity.

The potential benefits

AI may benefit labour markets in several ways:

  • Higher productivity: Workers can complete tasks more quickly with AI assistance.
  • New occupations: Demand has emerged for AI engineers, prompt specialists, data scientists and AI governance professionals.
  • Better decision-making: Firms can use AI to improve forecasting, inventory management and customer service.
  • Complementing human skills: AI may perform repetitive tasks, allowing employees to focus on creativity, problem-solving and interpersonal activities.
  • Economic growth: Higher productivity can increase profits, wages and living standards over time.

Many economists argue that AI will not simply replace workers but will change the tasks they perform. Research from the OECD suggests that even highly AI-exposed occupations continue to require management, communication, collaboration and social skills that technologies struggle to replicate.

The potential costs

At the same time, AI may create significant labour-market challenges. Many white-collar occupations previously considered relatively safe from automation are becoming vulnerable. Generative AI systems can draft reports, analyse legal documents, write computer code and create marketing content. This means that some professional and administrative roles may face considerable disruption.

The World Economic Forum reports that business leaders have differing expectations about the effects of AI. In a 2026 survey (see link below), around 54 per cent expected AI to displace existing jobs, while only 24 per cent expected it to create new jobs within their organisations. Economists have identified several potential problems:

  • Structural unemployment: workers in industries that are in decline may struggle to find employment requiring their existing skills.
  • Increased income inequality: there may be a growing income disparity between highly skilled and less-skilled workers.
  • Growing market power: the largest technology firms that own the most advanced AI systems may see their market power grow further creating dominance in certain areas.
  • Regional inequalities: AI-related investment may become concentrated in particular cities and countries, exacerbating regional inequalities within and between countries.
  • Pressure on governments: to address issues of structural unemployment and increasing inequality, governments may be forced to expand retraining and social-support programmes.

AI and catastrophic risk

Most economic discussion around AI focuses on employment and productivity. However, some researchers argue that the most significant risks from AI may be much broader.

Economists distinguish between ordinary risks and catastrophic risks. Catastrophic risks involve events with a very low probability of occurring but potentially enormous consequences. Examples include nuclear accidents, pandemics and certain climate-related disasters.

AI raises similar concerns. Advanced AI systems could potentially be used to conduct cyberattacks, spread misinformation, disrupt critical infrastructure or support the development of dangerous technologies. Some researchers have even suggested that highly advanced AI systems could pose an existential risk to humanity if they become sufficiently powerful and are not properly controlled.

This became a widely discussed topic in the media in September 2026 following the resignation of an employee, Jacob Coxon, from AI firm, Anthropic. He said that people working on AI were ‘genuinely frightened’ about how quickly AI was advancing and what it might mean for the future of humanity. He said:

I believe that if we don’t slow down at the current rate of progress, there is a strong chance that we could all die in the immediate future.

Other researchers have raised similar concerns and there have since been calls from some of the biggest AI companies for regulation of AI to prevent this.

The policy debate and CBA

All of this creates a challenge for cost-benefit analysis. Suppose AI generates trillions of pounds of economic benefits. But, if there is also a very small probability of catastrophic harm, how should policymakers weigh up the two?

Traditional cost-benefit analysis values risk by multiplying the size of a potential outcome by its probability. However, this approach becomes problematic when both the probability and the consequences are highly uncertain. The risks may be extremely difficult to estimate, while the potential costs could be vast and affect future generations. For this reason, governments and firms increasingly use scenario analysis, stress testing and AI safety assessments to evaluate potential risks. These approaches attempt to prepare for extreme outcomes rather than relying solely on probability calculations.

Supporters of AI argue that technological progress has historically improved living standards and that restricting AI too heavily could reduce innovation and economic growth. Critics argue that uncertainty about potentially catastrophic outcomes justifies a more cautious approach.

The debate therefore extends beyond labour economics to the wider issue of managing catastrophic risk. As with nuclear power or climate change, policymakers must decide how much risk society is willing to accept in exchange for potentially large economic benefits.

Articles

Reports

Questions

  1. How might AI increase productivity while also causing unemployment in some sectors? Which sectors are likely to be affected the most?
  2. Why is it difficult to estimate the costs and benefits of advanced AI?
  3. Assume that a disaster is estimated to cost society £1000 billion (£1 000 000 000 000). The chances of the disaster occurring are said to be minute, however. Estimates vary from a probability of one in a million to one in a billion. What estimate of this cost would you include in a cost–benefit analysis?
  4. Why are many low-income countries apparently prepared to accept riskier projects than are high-income ones?
  5. Discuss whether the greatest economic challenge posed by AI is (a) job displacement; (b) increased inequality; (c) market concentration and the power of large technology firms; or (d) catastrophic long-term risks.
  6. Read the article by Bill Gates, The turbulent AI era is here. The choices we make now are critical. According to him, what steps should the world take to ensure that ‘AI will be a force for good and leave everyone better off’?
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Feeding Godzilla



The World Meteorological Organization predicts that a ‘super El Niño’ is building. This has been nicknamed ‘Godzilla’. If forecasts are correct, this will be the most extreme El Niño in 1000 years.

El Niño is a natural phenomenon. It occurs when the surface temperatures in the central and eastern tropical Pacific Ocean warm and cause the trade winds that typically blow from east to west across the Pacific Ocean to weaken or even reverse direction. As well as increasing global temperatures and causing intense heatwaves, it can result in droughts in some parts of the world, such as eastern Australia, south-east Asia and southern Africa, and intense rain and flooding in parts of South America, eastern Africa and south-western North America.

Typically, in an El-Niño event, the surface temperature of the central-eastern equatorial Pacific Ocean rises by 1°C to 1.5°C above the average. In the current El Niño, it is forecast to rise by up to 4°C by the end of 2026 and into 2027. It is already between 2.2°C and 2.6°C above the average. The effects could be catastrophic and hence the term ‘Godzilla’.

Although El Niño is a natural phenomenon, its severity is a direct result of climate change. This in turn is a direct result of economic decisions, and the effects will have severe economic consequences.

The economic causes

Climate change is an external cost of private economic decisions. When people or organisations burn fossil fuels, the climate costs of the CO2 emissions are not borne by the emitter. They are an external cost. This is illustrated in the diagram below, which shows the costs and benefits of electricity production from fossil fuels. (Click here for a PowerPoint.)

In this example, to make things simple, we assume that the external climate costs begin with the first unit of electricity generated and increase at a constant rate. The marginal social cost (MSC) of electricity generation equals the marginal private costs (MPC) to the generating company plus the marginal external cost in production MECP.

As you can see, the MSC curve is above the MPC curve. The vertical distance between them is equal to the MECP. It is also assumed that there are no externalities in consumption, which means that the marginal social benefit (MSB) curve is the same as the marginal private benefit (MPB) curve.

Competitive market forces, with producers and consumers responding only to private costs and benefits, will result in a market equilibrium at point a: i.e. where demand equals supply. The market equilibrium price is Ppc, while the market equilibrium quantity is Qpc. At Ppc, with no externalities on the consumption side, MPB is equal to MSB. The market price reflects both the private and social benefits from the last unit consumed. However, the presence of external costs in production means that MSC > MPC.

The socially optimal output would be Q*, where P = MSB = MSC, achieved at the socially optimal price of P*. This is illustrated at point c and clearly shows how external costs of production in a perfectly competitive market result in overproduction: i.e. Qpc > Q*. From society’s point of view, too much electricity is being produced from fossil fuels.

Total social surplus equals consumer surplus plus producer surplus minus the external costs. At the market equilibrium (Qpc) this is areas eaPpc+ Ppcaf – fba (or hjk, as it is the same size). At the socially optimal level of output (Q*) total social surplus is areas ecP* + P*cgf – fcg (or hlm).

Although consumer-plus-producer surplus is higher at the market equilibrium (Qpc) than at the socially optimum output (Q*) by the area cag, the external costs are higher still by the area cbag (or ljkm). Therefore, total social surplus at the market equilibrium is smaller than at the socially optimal point by area abc. This is a deadweight welfare loss and represents the excess of social costs over social benefits at all outputs above Q*. Put another way, moving from Qpc to Q* would represent a gain in social surplus of the area abc, as the fall in external costs outweighs the fall in consumer-plus-producer surplus.

One of the reasons why external environmental costs cause problems in a free-market economy is that no one has legal ownership of the atmosphere. Therefore, nobody has the ability either to prevent or to charge for their use as a ‘dumping ground’ for CO2. Such a ‘market’ is missing. Control must, therefore, be left to the government, international organisations, local authorities or regulators.

But such control is often too little. For example, when President Trump came to office in January 2025, he announced that the USA would withdraw from the UN’s Paris Agreement on climate change and that his policy towards oil production would be to ‘drill, baby, drill’. Indeed, governments globally spend hundreds of billions of dollars a year in subsidising oil, gas and coal production and its use, partly from pressure from the fossil fuel industry and partly to reduce the cost of living for consumers. This embeds fossil fuel dependence.

Game theory can help to explain the slow process of carbon reduction. For an individual country, such as the USA, it might argue that its optimum solution would be for other countries to cut their emissions, while maintaining its own levels. This approach would yield most of the benefits to the USA and none of the costs. However, when all countries argue like this, no progress is made. It’s a prisoners’ dilemma. Only if countries believe that the other countries will (a) ratify an agreement to cut emissions and (b) stick to the approved terms, is the agreement likely to succeed. This requires trust on all sides as well as the ability to monitor the outcomes.

Another major problem area concerns equity. Most countries will feel that they are being asked to do too much and that others are being asked to do too little. High-income countries will want to adopt a grandfathering approach. The starting point with this approach would be current levels of pollution. Every country would then be required to make the same percentage cut. Low-income countries, on the other hand, will want the bulk of the cuts, if not all of them, to be made by the rich countries. After all, the rich countries produce much higher levels of pollutants per capita than do the poor countries, and curbing growth in low-income countries would have a far more serious impact on levels of absolute poverty.

But will a supersized El Niño persuade countries to make deeper cuts in carbon emissions? In recent months commitments to achieving net zero emissions have waned. But the following economic consequences may encourage some countries to make deeper emissions cuts.

Economic consequences of a Godzilla El Niño



Extreme droughts, heat, wildfires and harvest failures in some areas and extreme rainfall and flooding in others will have severe economic consequences, often for the poorest people. There will be reductions in crop yields and loss of livelihood. Food prices will rise globally. This will add to the inflationary pressures from higher oil prices caused by the Iran war.

Droughts and wildfires in south-east Asia and Australia could have disastrous effects on harvests of palm oil, coffee, cocoa, rice, maize, wheat and various tropical fruits. Droughts and heat reduce output from hydropower and possibly wind energy, and industrial production may slow as a result of extreme heat in workplaces.

In Europe, warmer winters and unusually wet springs promote rapid plant growth. When this is followed by summer heatwaves, the undergrowth dries out and provides fuel for the wildfires. A super El Niño will amplify this. France and Spain have experienced massive wildfires these past few months. In the UK, the 2026 summer has been the hottest on record. The costs in Europe of the heat and wildfires in terms of lost crops and animals have been immense.

Floods and storms damage roads, power grids, railways and buildings. This forces governments to spend money on repairs instead of long-term investments. People are displaced and many are likely to lose their lives.

Fortunately, El Niños fade after a few months to be replaced by the cooler La Niña. The problem is that, with global warming, the next El Niño in a few years could be even more extreme with even more serious economic consequences.

The hope is that governments wake up to the pressing need to reduce carbon emissions.

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Information

Articles

Questions

  1. What is the current state of progress towards meeting the goals of the UN Paris Climate Agreement?
  2. Are there any externalities in consumption that affect global warming?
  3. How might technological progress make it privately profitable to reduce carbon emissions?
  4. How might global supply chains and shipping be affected by a super El Niño?
  5. What role can education play in tackling climate change and its effects?
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Manchesterism: will greater devolution boost economic growth and help tackle inequality?


Andy Burnham is set to become UK Prime Minister on 20 July if no-one else stands to replace Keir Starmer. In a speech on 29 June, he outlined his economic vision. Central to this is devolution, where a greater number of economic decisions would be taken locally rather than by central government. This approach has been dubbed ‘Manchesterism’, in reference to his time as Mayor of Greater Manchester from 2017 to earlier this year. Under his mayoralty, Greater Manchester (GM) achieved faster economic growth than other regions or cities in the UK. From 2017 to 2023, GM’s gross value added grew by an average of 6.6% per annum and the city of Manchester’s by 8.4% – the highest of any city in the UK. The UK average was 4.9% and London’s was 4.6%.

The UK, especially England, is one of the least devolved of the OECD countries. One aspect of this is taxation. The chart shows local taxes and, in the case of federal countries, state/regional/provincial taxes too. (Click here for a PowerPoint.)

Only 4.9% of UK tax revenue is in the form of local taxes (council tax and 50% of business rates) and the amount that can be raised in council tax is capped by the central government. The remainder of UK tax revenue goes to central government in the form of income taxes, social security taxes (national insurance), VAT, excise duties, etc. This compares with an average of 7.1% local taxes and 24.5% local plus regional taxes across the 17 OECD countries shown in the chart.

Andy Burnham plans to shift some of the spending and tax-raising powers from Whitehall to metro mayors and local councils. The aim is to stimulate productivity and economic growth at a regional and local level by tailoring support and incentives to local needs and strengths. Local leaders will be best positioned to understand these needs and strengths and will be able to customise spending and support appropriately.

Examples of the types of greater autonomy over decision making would include:

  • Control over adult education budgets to allow them to be tailored to provide training and apprenticeships to meet the skills requirements of existing and emerging industries in the area;
  • Forming partnerships with local universities to support research and development that complements regional economic growth;
  • Providing greater funding for and control over local transport infrastructure, including roads, buses, trams, trains, etc., with local consultation to make them fit for the local population and businesses;
  • Tailoring business incentives to local needs and to the needs of the businesses themselves so as to attract an increase in investment;
  • Greatly expanding council house building, which has virtually dried up in recent years, with mayors and/or local authorities empowered to develop local housing strategies, including affordable housing programmes, and to direct housing investment funding to particular housing developments in areas of greatest need.

Andy Burnham has pledged to stick to the government’s two existing fiscal rules:
a) The Stability Rule (Fiscal Mandate): the current (day-to-day) budget must be in balance or surplus. In other words the provision of salaries, public services, state pensions, welfare, etc. must be covered by government revenues (largely taxation). The government should borrow only to fund long-term investment.
b) The Debt Rule (Stock Mandate): each year, public-sector net financial liabilities (PSNFL) must be forecast by the OBR to be falling as a share of GDP compared to the previous year in three years’ time. This acts as a break on the amount of borrowing for long-term investment.

It is likely, therefore, that there will be little extra government money for investment. Rather, the policy involves a redistribution of public-sector investment from central government to mayoral/local authorities.

In theory, such a policy of devolution need not see a redistribution from richer to poorer regions, but that might be part of the policy when the details are published. The UK has a bigger gap in productivity (GDP per worker) between its capital city and other large cities than in do other countries. Birmingham, Sheffield, Leeds, Newcastle, etc., as well as Cardiff, Glasgow, Edinburgh and Belfast, lag further behind London in output per head and economic growth than do other European countries lag behind their capital city. Thus the gap between Paris and Lyon, Toulouse and Marseille is narrower; as is that between Belin and Munich, Hamburg and Frankfurt. It is a similar picture in Spain and Italy. In the USA, some cities, such as San Francisco, outperform Washington DC and New York. A redistribution of government funding from London to the regions could see their incomes rise faster without having too much impact on London, which would still continue to attract large amounts of private investment.

Overall, there would be little increase in government funding. ‘Manchesterism’ is not, therefore, a demand-side policy. It is a supply-side policy – directing funds to areas where, combined with local incentives and local knowledge, the funding could yield greater returns and thereby increase potential GDP.

But this is not to say that there is no effect on aggregate demand. The hope is that devolution along the lines outlined by Andy Burnham will attract increased private investment, thereby increasing actual GDP as well as further increasing potential GDP.

We wait to see the details over the coming weeks.

Articles

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Data

Questions

  1. Use an aggregate demand and supply diagram (simple or dynamic) to illustrate the effects on real GDP of a successful devolution strategy.
  2. Find out the details of the last Conservative government’s ‘levelling up’ policy. Was it similar in aims to that of ‘Manchesterism’?
  3. How could a policy of devolution as outlined by Andy Burnham affect income distribution within regions?
  4. Find out about the approach to regional policy in the EU. Is it similar to that being advocated by Andy Burnham?
  5. What is meant by ‘regional multipliers’? Why might they differ from the national multiplier?
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The 4Ps approach to merger policy in the UK

The approach towards mergers remains the most controversial area of competition policy. Some argue that policy makers in both the UK and EU have been too easily persuaded by the arguments put forward by firms and so have allowed too many mergers to proceed. Others claim that the opposite is true and that merger policy has prohibited mergers that should have been allowed to proceed. This, then, has a negative impact on investment, innovation, productivity and growth.

In recent years there has been more specific criticism of merger policy in the UK. The government has indicated that it wants the Competition and Markets Authority (CMA) to be less interventionist and take a more pro-growth approach.

In February 2025, in response to this criticism, the CMA launched its new ‘4 Ps’ approach to merger policy: Pace, Predictability, Proportionality and Process. Various changes to the investigation process have been proposed in the past 12 months using this framework.

Pace. The time taken by the CMA to initially assess a merger before deciding whether a Phase 1 investigation is necessary (i.e. the pre-notification procedure) was reduced from 65 to 40 working days. Also, the target to complete straightforward Phase 1 investigations was reduced from 35 to 25 days.

Predictability. The proposed merger guidelines, published in October 2025, provide more detail on (a) what criteria will be used to measure market shares when applying the ‘share of supply test’ (this is where the combined UK market share of two merging businesses is at least 25%, provided one business has a UK turnover of at least £10 million), and (b) the factors that are likely to lead to the competition authorities concluding that one business has gained ‘material influence over another’. Businesses had complained that there was too much uncertainty about the way the share of supply test and material influence were applied. The CMA is also considering greater alignment with other international regulators over decision making rather than its previous policy of acting independently. All these measures should increase the predictability of the investigation process.

Proportionality. Proportionality refers to the objective of addressing any competition issues in merger cases in a way that places the minimum burden on the businesses involved. To improve proportionality, the CMA has indicated that in future cases it will be more willing to use behavioural remedies – requiring firms to take or desist from certain actions. New draft guidelines identify more situations where the use of behavioural remedies may be appropriate. However, they also show that the CMA still views structural remedies (e.g. preventing the merger or requiring firms to demerge or to sell certain assets) as more effective in many situations. Another important measure to improve proportionality is the introduction of a new ‘wait and see’ approach to global mergers. The CMA will now wait to see if the actions taken by other competition authorities in global cases address any concerns in the UK market before deciding whether to launch a review.

Process. To improve the process, the CMA has announced plans to engage with businesses at a much earlier point in the process. For example, it has pledged to share its provisional thinking in the early stages of an investigation by implementing new ‘teach-in’ sessions and having more regular update meetings. Much earlier meetings that focus on possible remedies will also take place. This may make it possible for the CMA to assess the suitability of more complex remedies during a Phase 1 investigation rather than having to wait for a longer and more costly Phase 2 review. Phase 2 reviews will also no longer be managed by panels of independent experts. This role will now be carried out by the internal CMA board.

Some critics argue that the CMA has not fully considered the potential benefits of mergers in many cases. For example, a merger could (a) have procompetitive effects, known as rivalry enhancing efficiencies (REEs) and/or (b) benefits for consumers outside of the relevant market, known as relevant customer benefits (RCBs). In response to this criticism, the CMA is currently reassessing its approach to including evidence on REEs and RCBs.

The CMA is still currently consulting with interested parties about many of these proposed changes. It will be interesting to see what final decisions are made in the next couple of years.

Articles

CMA documentation

Questions

  1. Of all the mergers considered by the CMA in 2024/25, find out what percentage were formally investigated. How many were blocked from taking place? Do you believe that this indicates that merger policy is too weak or too strong?
  2. What three criteria must be met for a business arrangement to be classed as a ‘relevant merger situation’ by the CMA?
  3. Identify some different methods that one business could use to gain material influence over the way another company operates.
  4. Outline the ‘turnover test’, the ‘share of supply test’ and the ‘hybrid test’.
  5. Discuss the potential advantages of using behavioural remedies as opposed to structural remedies in merger cases. Why has the CMA still preferred the use of structural remedies in most situations?
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The second-hand market and GDP

This Christmas, more people are considering giving second-hand (or ‘pre-loved’) goods as presents. This allows them to afford better-quality presents and to save money at a time when a large proportion of the population are finding that their finances are stretched. This continues a trend towards buying second-hand products – a trend driven by the rise of various online retailers, such as Vinted and Preloved, and a growing online presence of charity shops, as well as extensive use of established platforms, such as Facebook Marketplace, eBay, Depop, Gumtree and Nextdoor.

Clearly, people gain from buying and selling second-hand items – part of the ‘circular economy’. But what are the implications for gross domestic product (GDP)? After all, GDP is one of the main indicators of the size of an economy, and growth in GDP is probably the most widely-used measure of economic progress. Are second-hand transactions captured in GDP?

If you directly sell your own second-hand items, this does not count towards GDP. There is no new product being made. The items are only counted when they are first produced. Any service you provide to the purchaser (and to yourself) is in a similar category to housework, childcare, DIY and other services that people provide to themselves, household members and friends. But like such services, there is a strong argument that they should be.

Likewise, the environmental benefits (positive externalities) of recycling products, rather than throwing them away or hoarding them, are not counted. In fact, if reusing products causes fewer new products to be made, this would be counted as subtracting from GDP.

If, however, you set up a business by buying and selling second-hand items, the service you provide would contribute towards GDP. What would be counted would the value added to the product – captured through the difference in the purchase and selling prices. In fact, HMRC has warned people that buying and selling second-hand items is taxable, as it counts as self-employment for tax purposes. But it is only this value added that counts. If you buy an item on Vinted, only the value added by Vinted counts towards GDP.

As no production takes place, the purchase of second-hand items adds either nothing to GDP or just the service of a retailer. It is effectively just a transfer of goods and money. If buying second-hand items means that you buy fewer new ones, then that would cause GDP to fall if the response of firms is to produce fewer newer items. However, the person selling the second-hand items will gain revenue, which could be used to buy new items. If that increased production, that would boost GDP. The net effect on GDP of this transfer of goods and money in the second-hand market will be pretty small.

Yet, clearly, the second-hand market provides a welfare gain to both sellers and purchasers – a gain that is likely to grow as the use of second-hand markets increases. At Christmas time, it provides a timely warning of the limitations of using GDP to measure wellbeing.

Articles

Questions

  1. What other items or activities affecting human wellbeing are not counted in GDP?
  2. Name some goods and services that are produced, and hence are included in GDP, but which can be classed as ‘bads’.
  3. For what reasons might a country have a high GDP per capita but a poor average level of wellbeing?
  4. How might GDP figures be adjusted for international comparison purposes?
  5. Would it be possible to adjust GDP figures to take account of externalities in production (negative and positive)? If so, how?
  6. Production involves human costs. To what extent does GDP take this into account?
  7. What is meant by the circular economy? How might you have a ‘circular’ Christmas?