[938LIVE #TalkBack] Is facial recognition effective for public transport?

Associate Professor Terence Sim from the Department of Computer Science joined CNA938 #TalkBack segment on facial recognition technology in public transport, prompted by the closed trial now underway at Punggol Coast MRT Station.

Host Daniel Martin put the question to Prof Sim, whose research spans biometric authentication and facial recognition: can a system built to verify one face at a time handle a gantry at rush hour?

Prof Sim's answer centred on throughput. Similar systems already run in cities such as Beijing, Osaka and Moscow, but Singapore's population is more racially diverse than most, and that diversity exposes a known weak point. "It's been found that darker skin tones cause problems for the systems, elderly women tend to have difficulty, and of course children, because their facial structure changes rapidly," he said, adding that headgear, masks and even a fresh shave can throw off a match against someone's enrolled image.

Average daily MRT ridership hit 3.49 million trips in 2025, according to the latest LTA statistics, concentrated in evening bursts between 5pm and 7pm, a volume far beyond any office facial recognition deployment. Prof Sim outlined three ways such a system can fail: false positives, false negatives, and misidentification, where one enrolled commuter is charged for another's ride. Citing the best error rates he could find, he estimated roughly 10,500 people could be barred from the gate daily, and about 1,750 could be wrongly charged for someone else's trip.

His conclusion: lighting, crowding and privacy concerns mean facial recognition technology is unlikely to replace tapping outright.

Listen to the full segment: CNA938 Rewind - #TalkBack (6 Aug): Is facial recognition effective for public transport?