Introduction
Unemployment refers to the situation where individuals who are willing and able to work at the prevailing wage rate are unable to find employment. The Monetary Authority of Singapore (MAS) noted in December 2019 that unemployment was set to rise, attributing this to weaknesses in external demand and the acceleration in the development and deployment of artificial intelligence (AI) solutions. Weak external demand reduces firms' need for labour as exports decline, leading to cyclical unemployment, while AI-driven technological change can displace workers in traditional industries, resulting in structural unemployment. Together these factors raise the overall unemployment rate in Singapore.
Weak external demand and cyclical unemployment
One key factor behind rising unemployment was weakness in external demand, driven by the US-China trade war in 2019. Multiple rounds of tariffs imposed by both economies reduced trade volumes and lowered incomes for businesses and consumers in both countries. As the United States and China are two of Singapore's major trading partners, a slowdown in their economies directly affects Singapore's export sector.
A fall in export demand reduces Singapore's net exports (X minus M), lowering aggregate demand (AD). Heightened global uncertainty can also dampen investor confidence, reducing foreign direct investment and private investment (I). The combined fall in investment and net exports contracts aggregate demand, reducing real national income from Y0 to Y1.
As economic growth slows, firms cut costs by reducing their demand for factor inputs, including labour. Firms lay off workers or reduce hiring, raising cyclical unemployment, which is unemployment caused by insufficient aggregate demand. This lifts the overall unemployment rate.
Acceleration in artificial intelligence and structural unemployment
The rapid advancement and deployment of AI in Singapore has also contributed to rising unemployment by displacing workers in certain industries. Automation and AI raise productivity and efficiency, but they reduce the need for human labour in routine and repetitive tasks.
For example, the introduction of autonomous vehicles could gradually replace jobs traditionally held by bus and truck drivers, with trials of self-driving buses and taxis already conducted on university campuses and in certain districts. Similarly, AI solutions in manufacturing, retail and financial services can displace roles such as customer service, data entry and logistics.
While AI adoption creates new opportunities in engineering, programming and data science, many displaced workers lack the skills to transition into these roles. This results in structural unemployment, where workers face long-term displacement because of a mismatch between their existing skills and the skills now demanded. Without adequate retraining and reskilling, unemployment may continue to rise as technology advances.
Conclusion
Both weak external demand and the acceleration of AI contribute to rising unemployment in Singapore. Falling global demand reduces export revenues and investment, lowering aggregate demand and raising cyclical unemployment, while automation displaces workers and creates structural unemployment when their skills no longer match available jobs. Although growth and technological progress are necessary for long-term advancement, policies such as job retraining and labour market support are crucial to help workers adapt and to limit the rise in unemployment.