AI’s ability to translate into real economic growth needs a reality check warn Chinese scholars
- The Solow Paradox was used to understand the slowdown in productivity growth in the US in the 1970s and 80s despite rapid IT development over same period
Artificial intelligence and big data have been compared to oil and electricity in terms of their importance to future economic growth but will the hype live up to reality?
A growing number of academics, including some Chinese scholars, are calling for a reality check on the much-touted fourth industrial revolution, arguing it could fall victim to what is known as the Solow Paradox.
Postulated by American economist Robert Solow the theory describes the “discrepancy between measures of investment in information technology and measures of output at the national level.” The theory was used to help understand the slowdown in productivity growth in the US in the 1970s and 1980s despite rapid development of information technology over the same period.
AI could face the same paradoxical situation, amid growing calls for long-term research and investment in the technology and its dependency on infrastructure and collaborative technologies, according to Du Chuanzhong, a Nankai University professor and director at the Nankai Industrial Economic Institute in China.
“Right now, the major impact of AI is still in the services sector,” said Du at an academic seminar on AI held in Beijing last weekend. “Any boost to manufacturing is still some distance away – there are gaps to fill with new algorithms, supporting technologies and innovation around business models.”
Yang Danhui, a researcher at the Chinese Academy of Social Sciences (CASS) and director of CASS Industrial Economics Institute, echoed Du’s remarks, saying that public security remains the biggest AI application in China so far, despite global expectations for it to transform manufacturing.
