Technology

AI likely to worsen economic inequality, says IMF

Artificial intelligence (AI) could impact almost 40% of global employment, says International Monetary Fund (IMF), and will “likely worsen overall inequality” if policymakers do not proactively work to prevent the technology from stoking social tensions.

In an analysis published 14 January 2024, the IMF examined the potential impact of AI on the global labour market, noting that while it has the potential to “jumpstart productivity, boost global growth and raise incomes around the world”, it could just as easily “replace jobs and deepen inequality”.

The IMF said that while the net effect of AI is difficult to predict due to the complex ways it will ripple through economies, its overall impact on both income levels and overall inequality will largely depend on the extent to which AI-induced productivity gains are able to offset the impacts of AI-induced job losses.

However, in a blogpost accompanying the analysis, IMF managing director Kristalina Georgieva said that, in most scenarios, AI would probably worsen global economic equality and deepen social tensions without political intervention.

“It is crucial for countries to establish comprehensive social safety nets and offer retraining programmes for vulnerable workers. In doing so, we can make the AI transition more inclusive, protecting livelihoods and curbing inequality,” she wrote.

Impact on income levels and inequality

The IMF analysis said that unlike historical waves of automation, which have predominately affected “routine tasks”, the capability of AI to process vast amounts of information, identify patterns and make decisions puts occupations once considered immune to automation in the firing line.  

“Jobs that require nuanced judgement, creative problem-solving, or intricate data interpretation – traditionally the domain of highly educated professionals – may now be augmented or even replaced by advanced AI algorithms, potentially exacerbating inequality across and within occupations,” it said.

“This shift challenges the conventional wisdom that technological advances threaten primarily lower skill jobs and points to a broader and deeper transformation of the labour market than by previous technological revolutions.”

However, it also said that the outcomes of AI’s proliferation are unlikely to be felt equally, and will be shaped by the existing material conditions within (and between) specific industries, occupations and countries.

For example, while it said AI will affect jobs previously untouched by prior waves of automation, the technology is still much more likely to benefit white-collar workers already in higher paying jobs because the nature of their work is ‘complementary’ to the functions of AI.

In contrast, it is more likely to have a displacing effect on lower-earners, where it is more likely to replace rather compliment their work.

The IMF suggested that while massively increased productivity at the macro level could usher in “labour income rises for all workers” – including those with either low exposure or “high exposure and low complementarity” between AI and their jobs – income inequality would still increase because the increase is larger for workers whose jobs already synergise with the technology.

“Owing to capital deepening and a productivity surge, AI adoption is expected to boost total income. If AI strongly complements human labour in certain occupations and the productivity gains are sufficiently large, higher growth and labour demand could more than compensate for the partial replacement of labour tasks by AI, and incomes could increase along most of the income distribution,” it said.

“Model simulations suggest that, with high complementarity [between AI and their jobs], higher-wage earners can expect a more-than-proportional increase in their labour income, leading to an increase in labour income inequality.

“This would amplify the increase in income and wealth inequality that results from enhanced capital returns that accrue to high earners. Countries’ choices regarding the definition of AI property rights, as well as redistributive and other fiscal policies, will ultimately shape its impact on income and wealth distribution.”

Impact on national and global inequality

The IMF similarly noted that while advanced economies such as the UK are more susceptible to the impacts of AI due to having a higher concentration of jobs “that require complex cognitive tasks”, they are also better placed to reap the benefits due to the ability of workers to adapt, already high levels of exposure to AI, and easier access to capital.

“Emerging market and developing economies, often still reliant on manual labour and traditional industries, may initially face fewer AI-induced disruptions,” it said. “However, these economies may also miss out on early AI-driven productivity gains, given their lack of infrastructure and a skilled workforce.

“Over time, the AI divide could exacerbate existing economic disparities, with advanced economies harnessing AI for competitive advantage while emerging market and developing economies grapple with integrating AI into their growth models.”

It added that, unlike labour income inequality, which can decrease in certain scenarios where AI’s displacing effect lowers everyone’s incomes, capital income and wealth inequality “always increase” with greater AI adoption, both nationally and globally.

“The main reason for the increase in capital income and wealth inequality is that AI leads to labour displacement and an increase in the demand for AI capital, increasing capital returns and asset holdings’ value,” it said.

“Since in the model, as in the data, high income workers hold a large share of assets, they benefit more from the rise in capital returns. As a result, in all scenarios, independent of the impact on labour income, the total income of top earners increases because of capital income gains.”

It added the higher skill base of workers in richer countries could have further consequences for global economic disparities if jobs are reshored to advanced economies.

“Such a shift could trigger reallocation of capital and labour from less developed regions, which are not as prepared to harness AI, toward more technologically advanced and AI-ready countries. Call centers located in emerging market economies are a potential example,” it said, adding that while these dynamics are currently highly uncertain, it’s possible that less developed countries could “leapfrog” in certain sectors with enough investment, preventing the “reshoring” of activity to the rich countries.

For high income countries and more advanced developing economies, the IMF therefore recommends creating adequate regulatory frameworks to optimise the benefits of increasing adoption. For lower income countries, it recommends prioritising digital infrastructure and human capital to “alleviate skill shortages, expand the provision of health care and education, and improve productivity and competitiveness in new sectors.”

Given the complexity and uncertainty around the impacts of AI, however, which are all highly dependent on how specific dynamics and scenarios unravel, the IMF said that “ensuring social cohesion is paramount”.

“The potential implications of AI demand a proactive approach from policymakers geared toward maintaining social cohesion. While long-term productivity gains from AI are likely, during the transition, job displacement and changes in income distribution could have substantial political economy implications. History shows that economic pressures can lead to social unrest and demands for political change,” it said.

“Policies must promote the equitable and ethical integration of AI and train the next generation of workers in these new technologies; they must also protect and help retrain workers currently at risk from disruptions.

“The cross-border nature of AI amplifies its ethical and data security challenges and calls for international cooperation to ensure responsible use, as recently laid out in the Bletchley Declaration, signed by 28 countries and the EU. Countries have varying capacity to address these issues, which highlights the need for harmonised global principles and local legislation.”

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