AI and the future of work
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The International Monetary Fund has a 4,000-word study on artificial intelligence and the future of work.
IMF’s one major conclusion: the poor and uneducated will lose jobs and be displaced. Up to 26 percent of work force will be affected in low-income countries and 40 percent in middle income economies like the Philippines.
In rich countries, up to 60 percent of the work force will be affected, but mostly for the better.
Here is part of the IMF report:
Artificial intelligence (AI) is set to profoundly change the global economy, with some commentators seeing it as akin to a new industrial revolution.
Its consequences for economies and societies remain hard to foresee. This is especially evident in the context of labor markets, where AI promises to increase productivity while threatening to replace humans in some jobs and to complement them in others.
Almost 40 percent of global employment is exposed to AI, with advanced economies at greater risk but also better poised to exploit AI benefits than emerging market and developing economies.
In advanced economies, about 60 percent of jobs are exposed to AI, due to prevalence of cognitive-task-oriented jobs.
Of these, about half may be negatively affected by AI, while the rest could benefit from enhanced productivity through AI integration.
Overall exposure is 40 percent in emerging market economies and 26 percent in low-income countries. Although many emerging market and developing economies may experience less immediate AI-related disruptions, they are also less ready to seize AI’s advantages.
This could exacerbate the digital divide and cross-country income disparity.
AI will affect income and wealth inequality.
AI displacement risks extend to higher-wage earners. However, potential AI complementarity is positively correlated with income.
The effect on labor income inequality depends largely on the extent to which AI displaces or complements high-income workers.
With high complementarity, higher-wage earners can expect a more-than-proportional increase in their labor income, leading to an increase in labor 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.
The gains in productivity, if strong, could result in higher growth and higher incomes for most workers.
Owing to capital deepening and a productivity surge, AI adoption is expected to boost total income.
If AI strongly complements human labor in certain occupations and the productivity gains are sufficiently large, higher growth and labor demand could more than compensate for the partial replacement of labor tasks by AI, and incomes could increase along most of the income distribution.
College-educated workers are better prepared to move from jobs at risk of displacement to high-complementarity jobs; older workers may be more vulnerable to the AI-driven transformation.
Workers without postsecondary education show reduced mobility. Younger workers who are adaptable and familiar with new technologies may also be better able to leverage the new opportunities.
In contrast, older workers may struggle with re-employment, adapting to technology, mobility and training for new job skills.
To harness AI’s potential fully, priorities depend on countries’ development levels.
Advanced and more developed emerging market economies should invest in AI innovation and integration, while advancing adequate regulatory frameworks to optimize benefits from increased AI use.
For less prepared emerging market and developing economies, foundational infrastructural development and building a digitally skilled labor force are paramount. For all economies, social safety nets and retraining for AI-susceptible workers are crucial to ensure inclusivity.
Artificial intelligence (AI) promises to boost productivity and growth, but its impact on economies and societies is uncertain, varying by job roles and sectors, with the potential to amplify disparities.
As a positive productivity shock, AI will expand economies’ production frontiers and will lead to reallocations between labor and capital while triggering potentially profound changes in many jobs and sectors.
AI offers unprecedented opportunities for solving complex problems and improving the accuracy of predictions, enhancing decision-making, boosting economic growth and improving lives.
AI represents a wide spectrum of technologies designed to enable machines to perceive, interpret, act and learn with the intent to emulate human cognitive abilities.
Generative AI (GenAI) includes systems such as sophisticated large language models that can create new content, ranging from text to images, by learning from extensive training data.
Other AI models, in contrast, are more specialized, focusing on discrete tasks such as pattern identification.
Meanwhile, automation is characterized by its focus on optimizing repetitive tasks to boost productivity, rather than producing new content.
The field of AI is experiencing a swift evolution, especially with the advent of GenAI, which has broadened AI’s potential applications. This suggests that its impact will expand to reshape job functions and the division of labor.
One critical dimension to consider is the societal acceptability of AI.
Acceptability may vary depending on job roles. Some professions may seamlessly integrate AI tools, while others could face resistance because of cultural, ethical or operational concerns.
This uncertainty becomes especially pronounced in labor markets. Although AI holds the potential for production-oriented applications, its effect will likely be mixed.
In some sectors where human oversight of AI is necessary, it could amplify worker productivity and labor demand. Conversely, in other sectors, AI might pave the way for significant job displacements.
A rise in aggregate productivity of the economy could however strengthen overall economic demand, potentially creating more job opportunities for most workers in a ripple effect.
Moreover, this evolution could also lead to the emergence of new sectors and job roles – and the disappearance of others – transcending mere intersectoral reallocation.
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