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    AI could lead to job losses and exacerbate economic crises: IMF’s first deputy managing director Geeta Gopinath says

    Artificial intelligence (AI) could exacerbate economic crises and can lead to job losses during times of economic downturn, International Monetary Fund’s (IMF) Deputy Managing Director Geeta Gopinath said in her speech at the AI for Good Global Summit on May 30. Gopinath explained that previous waves of automation have shown that while companies continue to hold on to workers when flush with profits, “the extent to which automation could replace humans only becomes fully visible during or immediately after a downturn.”

    Gopinath gave the example of the Global Financial Crisis of the early 2000s. She mentioned that during that crisis, rather than rehiring workers after a slump many firms automated their operations—leading to the most severe “jobless recovery” ever seen in the US and Western Europe. She mentioned that AI could accentuate this dynamic, adding that an estimated 30% of jobs in advanced economies are at risk of being replaced by AI. The automation of these jobs by AI could lead to long-term unemployment because the workers being replaced would lack the requisite skills in an economy where AI is increasingly prevalent.

    Impact of AI-inclusion in the financial services industry:

    The financial services industry has heavily relied on algorithmic trading even prior to the recent AI boom. Gopinath said that the industry is rapidly replacing older models for algorithmic trading with more complex ones that can make decisions by themselves. “With its ability to harness vast amounts of information to make predictions, AI can help improve the allocation of resources and enhance financial inclusion,” Gopinath pointed out, highlighting how AI’s involvement in financial services could be a positive development in normal circumstances. 

    However, if there is an economic downturn in the future, AI could struggle to respond. This is because AI has been shown to perform poorly when faced with events that drastically differ from the data it has been trained on, which is what would happen when AI is met with patterns of unfamiliar job losses. As a result of this, the AI might become overly conservative and rebalance portfolios toward safe assets. “ The models’ decision to leave other assets will then be rewarded as their prices fall, and a self-confirming spiral of fire-sales and collapsing asset prices across different financial markets could ensue,” Gopinath explained, adding that the black box nature of AI could make such events particularly challenging.

    Demerits of AI involvement in supply chain management:

    The user-friendly nature of AI models could encourage companies to rely on AI for their production decisions. Again, like the financial services industry, this could provide benefits in normal circumstances but would be detrimental during a downturn. AI models trained on stale data could, “trigger a series of forecasting errors, creating more rapid swings in production and inventories” Gopinath said. This could, in turn, cause delays and shortages of critical supplies across the globe. 

    How can these future threats be mitigated?

    Gopinath suggested the following measures to prevent an economic crisis—

    Preventing bias for automation in tax systems: She quoted research by the IMF and said that the tax systems of several countries—including Germany, the United States, and Hong Kong— tend to favor automation. This means that businesses end up getting a relative tax advantage for using software/hardware that substitutes labor compared to what they would get for using technologies that complement human labor. Gopinath said that while this could be justified in situations where the social returns from automation are sufficiently high, given the economic risks of automation, it is questionable whether the returns would be high enough. She emphasized that she isn’t suggesting a separate tax for AI, but rather asking countries to reconsider tax incentives that favor automation

    Helping workers cope with the impact of AI: She argued that there is a need for heavier investments in education and training, especially in emerging markets. As per the AI Preparedness Index, emerging markets and low-income countries are less prepared for the technological shift to AI than advanced economies. She mentioned that forthcoming research by the IMF shows that more generous provision of unemployment insurance can help workers adapt to job market changes. It could help curb automation-related wage declines by giving unemployed people more time to find work. 

    Needs for measures to lower potential financial risks: To mitigate these risks, the regulators would themselves need to be upskilled. “Disclosures by financial institutions and securities issuers may need to be strengthened, to provide visibility on how they use AI, on the source of their AI models, and on their circuit breakers to reduce herding and distress sales,” Gopinath explained. AI models involved in decision-making will also need to be stress-tested to deal with unexpected events. Such models would also need sufficient human oversight to prevent “cascading breakdowns”.

    Gopinath said policymakers should closely track how AI is developed and created. They need to create and analyze a wide range of potential scenarios on how AI might impact economies, which will require economic analysis of AI’s potential implications on things like employment, productivity, and financial stability.

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    The post AI could lead to job losses and exacerbate economic crises: IMF’s first deputy managing director Geeta Gopinath says appeared first on MEDIANAMA.

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