SINGAPORE (Aug 22): Despite acknowledging that intelligent technology could progressively claim many jobs, the Singapore government is also confident that artificial intelligence (AI) will concurrently create new jobs in areas such as data analytics, cybersecurity, robotics engineering and revenue management.

A five-year programme called AI.SG – under which Singapore’s National Research Foundation (NRF) has pledged $150 million in funding for up to 100 commercial AI projects – is one example of the city state’s initiatives to develop its status as an innovation capital.

In the latest series of briefing reviews by MIT Technology Review, Asia’s AI Agenda: The Deep Dive Editions, the Massachusetts Institute of Technology publication has identified two ways in which automation technologies are currently being employed to revive Singapore’s competitive position and create new opportunities.

Firstly, automation technologies are currently being used to either stimulate or re-establish less prominent sectors of Singapore’s economy such as the automotive industry, says MIT Technology Review.

It points out that even without traditional businesses in assembly or parts manufacturing, the city state is nonetheless home to a growing number of global auto companies carrying out headquarters activities, supply chain management, procurement and R&D.

Another way AI is currently being employed in Singapore is to help established organisations free up resources in order to boost labour productivity, particularly in sectors which cement the nations’ role as a global business hub, such as healthcare – where AI is expected to play a prominent role in prevention, diagnosis and drug creation, among others.

Fintech has been outlined as another potential “AI hot spot” due to recent changes in Singapore’s financial regulations, which MIT Technology Review describes as light-touch regulation that has placed the city state ahead of other Asian financial hubs.

See: MAS to loosen regulatory barriers for banks carrying on permissible non-financial businesses

As such, a growing crop of domestic startups and incubators focusing on fintech-specific applications has produced.

These include Singapore-based startup Active Intelligence, which aims to use neuro-linguistic programming and machine intelligence to enable natural-language dialogue over messaging services and voice or IoT devices, as well as AIDA Technologies, a developer of predictive machine-learning based solutions for risk and compliance management in the banking and insurance industries.

Other candidates for AI transformation are the logistics, transport, environmental services and securities industries, says the publication.

Singapore’s growing AI aspirations, however, still run the risk of facing a number of challenges.

Given that the city state’s technology startup scene is still relatively small with few deep-tech AI ventures, says MIT Technology Review, this lack of scale could encourage breakthrough AI companies to turn to larger AI ecosystems such as Silicon Valley instead.

Local companies may also be facing a lack of support from capital markets, it adds, although the government aims to address this funding bottleneck through its AI.SG initiative.

Lastly, Singapore’s affluence and security may inadvertently result in “zombie” tech startups with low sales and few staff, given how persistent weak productivity growth has painted the city state’s companies as slow adopters of innovation, which some may attribute to a lack of drive and hunger – especially given the government’s support.

“Asia as a regional economy is poised not only to benefit greatly from advancements in AI technologies, but also to define them. This will be particularly so in Singapore – a focused, nimble, and knowledge-intensive economy whose organisations are perpetually concerned with achieving advantage through technology, and where domestic, regional, and global technology investments create a virtuous cycle,” writes MIT Technology Review.

“AI, when deployed correctly, will not eliminate jobs so much as deconstruct them and reorganise them around groups of competencies, enabling both humans and machines to work in more productive ways.”