Tag: Bill Gates

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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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GDP and development

The link below is to an article by Bill Gates, founder of Microsoft. He argues that per-capita GDP is a poor indicator of development, especially in Sub-Saharan Africa.

The problems with using GDP as an indicator of the level of development of a country are well known and several alternative measures are in common use. Perhaps the best known is the United Nations Development Programme’s Human Development Index (HDI), where countries are given an HDI of between 0 and 1. HDI is the average of three indices based on three sets of variables: (i) life expectancy at birth, (ii) education (a weighted average of (a) the mean years that a 25-year-old person or older has spent in school and (b) the number of years of schooling that a 5-year-old child is expected to have over their lifetime) and (iii) real gross national income (GNY) per capita, measured in US dollars at purchasing-power parity exchange rates (see Box 27.1 in Economics 8th edition for more details).

But although indicators such as this capture more elements of development than simple per-capita GNP or GNY, there are still serious shortcomings. A major problem is the lack of and inaccuracy of statistics, especially when applied to the rural subsistence and informal urban sectors. The problem is recognised and some countries are trying to address the problem (see the second article below), but the problem is huge. As Gates says:

It is clear to me that we need to devote greater resources to getting basic GDP numbers right. … National statistics offices across Africa need more support so that they can obtain and report timelier and more accurate data. Donor governments and international organisations such as the World Bank need to do more to help African authorities produce a clearer picture of their economies. And African policymakers need to be more consistent about demanding better statistics and using them to inform decisions.

Another problem is how you convert data into internationally comparable forms. For example, how are inflation, exchange rates, income distribution, the quality of health provision and education, etc. taken into account?

How GDP understates economic growth The Guardian, Bill Gates (8/5/13)
States’ GDP computation report out soon, says Nigeria statistics bureau Premium Times (Nigeria), Bassey Udo (9/5/13)
Michael Porter Presents New Alternative to GDP: The Social Progress Index (SPI) Triple Pundit, Raz Godelnik (13/4/13)

Questions

  1. By accessing the Human Development Index site, identify which countries have a much higher ranking by HDP than by per capita gross national income. Explain why.
  2. Why is expressing GNY in purchasing-power parity (PPP) terms likely to increase the GNY figures for the poorest countries?
  3. Explain the following quote from the Gates article: ‘I have long believed that GDP understates growth even in rich countries, where its measurement is quite sophisticated, because it is very difficult to compare the value of baskets of goods across different time periods’.
  4. Why is GNY per capita, even when expressed in PPP terms, likely to understate the level of development in subsistence economies?
  5. Explain whether the rate of growth of GNY per capita is likely to understate or overstate the rate of economic development of sub-Saharan African countries?
  6. Why are the challenges of calculating GDP or GNY particularly acute in sub-Saharan Africa?