I remember it like it was yesterday. I was about 15 years old and had accompanied a friend to a fair at a girls’ school. All the proceeds from the fair were earmarked for charity. Apart from the usual tuck shops, there was a long line of stalls offering various games that people could try their hand at and hope to win a prize. These included innocuous point and shoot or dart games where one paid a certain amount to have three chances at nailing a moving balloon. The prize was usually a coupon to spend more at the tuck shops. In some cases, it was a choice from an array of toys on a shelf put up behind the moving balloon by the stall’s operator.

Some of the stalls were very different, however. They involved games of chance, usually with a deck of cards. Each stall’s operator was a skilled card sharp. My friend, also aged 15, was drawn irresistibly to these. The stakes were very small, just a few coins, but he was hooked. After a few minutes of trying his hand at these, he ran through the small allowance his parents had given him to spend at the fair. He turned to me and asked me for a loan so that he could continue to bet. One look at his eyes and I knew that he had lost all control. The look in a hooked person’s eyes that I could read at that young age was certainly obvious to the card sharps, who kept asking him to stay, adding that all the proceeds were going to a good cause anyway. Good cause or not, like my friend, I was a penniless student at the time, and all I had left was enough loose change for our bus rides home. I refused to part with those coins and dragged him away from the action.

Today, a surveillance camera backed up with Artificial-Intelligence-enabled algorithms for facial recognition can read the look in a hooked gambler’s eyes. A recent article in Los Angeles Times (lat.ms/2JjcYXs), provided by Bloomberg, speaks of how hidden cameras and facial recognition technology are being used by casinos in Macau to spot inveterate gamblers to peel them off from the casual crowd. The higher a gambler’s propensity to take risks, the more money a casino makes. These hidden cameras are powered by algorithms that analyse the way prospective high rollers behave when they are at a table. Casino managers are also alerted by facial recognition technology from a German firm when high rollers walk into the premises, so that they can immediately dispatch hosts to the high roller’s side.

Such private use of facial recognition technology for profit making may seem sinister, but it can be easily understood when one realizes that businesses have tried to segment their customers from time immemorial. Any marketing student or sales person worth his or her salt has had to sit through endless hours of training on customer segmentation, and can spout various theories, both empirical and behavioural, on the subject. As far as picking out great gamblers is concerned, more than 3 million people visit Macau every month, the only place in China where gambling is legal. Some of these are families on holiday, who come to watch while the serious gamblers get a fix for their addiction. The casinos need to quickly segment this large number into high rollers and eye-rollers, and to pick out the serious from the spectator.

Governmental use of facial recognition technology for surveillance is also beginning to look sinister. Some governments have recognized that they need to limit such surveillance in a nod to their citizens’ rights to privacy. San Francisco’s Board of Supervisors (its legislature) voted to ban city agencies from using facial recognition technology on 14 May 2019. In January, when legislator Aaron Peskin introduced the measure, he said he had “yet to be persuaded that there is any beneficial use of this technology that outweighs the potential for government actors to use it for coercive and oppressive ends". San Francisco’s legislation does not bar city agencies from procuring the technology. It just makes them seek permission from the Board of Supervisors first to write policies governing its use, and then asks for annual reports on how often and why it was used. The measure also does not ban private citizens from using facial recognition technology and it does not apply to areas in the city such as airports and ports, which are regulated at a federal level by the US government. Federal measures are also in place in other countries, such as China, where the state’s effort to monitor its citizens is already the stuff of legend.

San Francisco is known to be a “liberal" city while simultaneously being a hotbed for technology innovation. Last week, the city voted to ban e-cigarettes, effectively shutting out JUUL Labs Inc., which is headquartered there, and is reportedly the second-highest valued venture capital-backed firm in the US. JUUL is now worth more than $38 billion in only two short years from its official founding. JUUL is not mentioned by name in the legislation, but has been the target of many lawsuits that accuse the company of targeting teens to addict them to nicotine, possibly the most addictive substance known to man. I haven’t heard from him in decades, but I hope that my gambling friend, at least, escaped that poison.

Siddharth Pai is founder of Siana Capital, a venture fund management company focused on deep science and tech in India