There is a lot of hype about artificial intelligence (AI) and technology sparking a revival of economic growth globally. As Nobel laureate economist Robert Solow said in 1987 about the productivity puzzle, “You can see the computer age everywhere but in the productivity statistics.”
In recent years, growth has slowed everywhere due to productivity declines, in spite of the internet and computer revolution. From 1996 to 2005, US labour productivity growth averaged 2.62 per cent, but slowed to 1 per cent from 2006 to 2017. This trend cuts across different countries and has different interlocking reasons, such as financial crises, trade and capital deepening.
When AI advanced with the introduction of ChatGPT, many thought it was the biggest productivity innovation since the internet as it is now possible to write research papers and compose poems in a fraction of the time it used to take. In a recent essay, Stanford economists Erik Brynjolfsson and Gabriel Unger argued that AI could develop in three different ways (good or bad), namely through productivity growth, income inequality and industrial concentration.
Without a proper set of policies, we may end up with the worst of three worlds – low productivity, worse income inequality and a huge concentration of power. However, with the right set of policies, an emerging or developing market economy could end up with higher productivity, more inclusivity and less market concentration.
It takes a large market size to achieve leadership in AI and technology. The Australian Strategic Policy Institute recently published a paper tracking 64 core technologies using cited research papers, which showed that the leading position of the United States and China have reversed in the past five years (2019-2023). India is now in the top five countries for 45 of 64 technologies; it has one of the largest cohorts of STEM graduates entering the workforce.
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