There is a lot of hype about artificial intelligence (AI) and technology sparking off a revival of growth globally. As Nobel Laureate economist Robert Solow said in 1987 about the productivity puzzle: “You can see the computer age everywhere but the productivity statistics”. In recent years, growth everywhere has slowed down 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 inter-locking reasons, such as financial crises, capital deepening, trade and mismeasurement factors.

When AI arrived with a ChatGPT bang, everyone thought this was the biggest productivity innovation since the internet, as we could now write research thesis to poems in seconds. In a recent essay on the macroeconomics of AI, Stanford economists Erik Brynjolfsson and Gabriel Unger argued that AI could develop in three different forks (good or bad), namely through productivity growth, income inequality and industrial concentration. Without a proper set of policies and regulations, we may end up with the worst of three worlds – low productivity, worse income inequality and huge power concentration.

On the other hand, with the right set of policies, an emerging and developing market economy (EMDE) could end up with higher productivity, more inclusivity and less market concentration. It takes a lot of market size and talents to achieve leadership in AI and technology. The Australian Strategic Policy Institute (ASPI) has recently published a paper tracking 64 core technologies using cited research papers, which showed that the leading position of United States and China have reversed in the last five years........

© The Statesman