AI Can Exacerbate Job Losses, Market Fall and Supply Chain Errors in Next Downturn: IMF

Update: 2024-05-31 14:51 GMT
In the next downturn, artificial intelligence can exacerbate job losses, financial market losses and supply chain errors across countries. In order to remain prepared, countries have to ensure that tax systems favour people over automation, workers are protected from AI labour market disruptions and financial institutions make disclosures on usage of AI, said Gita Gopinath, first deputy managing director of IMF. (Representational Image: DC)

 Chennai: In the next downturn, artificial intelligence can exacerbate job losses, financial market losses and supply chain errors across countries. In order to remain prepared, countries have to ensure that tax systems favour people over automation, workers are protected from AI labour market disruptions and financial institutions make disclosures on usage of AI, said Gita Gopinath, first deputy managing director of IMF.

“In the next downturn, AI is likely to threaten a wider range of jobs than in past cycles, including higher-skilled cognitive jobs. An estimated 30 per cent of jobs in advanced economies are at risk of being replaced by AI. It will be 20 per cent for emerging markets and 18 per cent for low-income countries,” Gopinath said in a global summit on AI.

During good times, firms invest in automation and hold on to workers, even if the value-added of those workers declines. However, in a downturn, these firms simply let go of workers to cut costs. This will result in unprecedented job losses and unprecedented numbers of long-term unemployed.

Further, use of AI in capital market activities is improving. However, in a future downturn with unfamiliar patterns, AI systems might struggle to respond. They might become overly conservative and rebalance portfolios toward safe assets, leading to collapses of asset prices across different financial markets.

In a future downturn, AI algorithms trained on stale information could also trigger a series of forecasting errors, creating more rapid swings in production and inventories and cause crippling delays and shortages of critical supplies across the globe.

These forms of risks could turn a regular downturn into an AI-amplified economic and financial crisis and present immense challenges for policymakers.

According to Gopinath, countries should ensure that tax systems do not inefficiently favour automation over people.

Countries also should reconsider existing corporate tax incentives that may be making AI ‘special’ and encourage labour substituting investments. To protect workers from AI labour market disruptions, heavier investments in education and training are essential, especially in emerging-market and developing economies.

“We need to protect them by adapting social safety nets to a world where AI could create prolonged job losses and make generous provision of unemployment insurance,” she said.

Further, financial regulators will need to enhance both supervision and regulation by upskilling themselves to understand AI-related risks. Disclosures by financial institutions and securities issuers may need to be strengthened, to provide visibility on the use of AI.

Countries also have to make a serious international effort to AI-proof their economies.

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