How Singapore’s government-run dating service works
Three years after the demise of the Social Development Network, it looks like a new government-run matchmaker is back on the cards for Singapore.
Earlier this month, a pilot progamme by GovTech called FirstDate was announced, with government workers set to be the first batch of daters. If this sounds familiar, that’s because I was the first to report on GovTech testing the waters with this idea all the way back in April for The Straits Times.
How will the matchmaking work? What questions are even in the matchmaking questionnaire? (Read on for the full list)
On FirstDate’s website, one line stands out: “FirstDate uses a Nobel prize-winning framework called the Gale-Shapley Stable Marriage Algorithm”. It’s a brow-raising detail because, despite the name, the algorithm has almost nothing to do with marriage, but more on this later.
The dating service will use Singpass to verify the identity of users, match people in cycles (you get only one match each cycle), and share contact details only when both users agree to their match.
To get a sense of how the matchmaking works, here’s the questionnaire that the government workers signing up must fill out. The questions are a mix of close-ended and open-ended ones, across 8 categories, spanning topics like interests and passions, lifestyle and daily habits, and communication and relationship style.
These are the questions:
What are you into these days? (pick up to 5 out of a checklist of items like gaming, film and cinema, volunteering, cafe-hopping, etc)
Now, spill! What do you actually love about your hobbies? (open-ended, optional)
What cuisines do you eat on repeat and never get sick of? (pick up to 3 out of a checklist)
Which restaurant do you keep going back to and why? (open-ended, optional)
How often do you find an excuse to leave the country? (close-ended, with options like every chance I get (4+ trips a year) to I prefer staying in Singapore (never))
What kind of traveler are you, really? (close-ended, with options like adventure junkie, culture seeker, and I don’t travel much)
What’s a country that’s ruined all other countries for you? (open-ended, optional)
Team sunrise, or team “it’s 2am and I’m still up”? (close-ended)
Gym rat, occasional jogger, or exercise is a myth to you? (close-ended)
Any food rules we should know about? (close-ended, with options like vegetarian, pescatarian, halal)
Do you smoke? (close-ended)
Be honest! What does your room look like right now? (close-ended, with options like spotless, organised chaos, and tidy up only when needed)
Hustle mode, or protecting your personal time? (close-ended, with options like career comes first right now and personal life comes first)
Real talk. How much of your day disappears into your phone? (close-ended)
Describe your social energy. Are you the life of the party, or the one who left an hour ago? (close-ended)
How important is it for you that a match brings the same energy, or do opposites attract for you? (close-ended)
After a brutal work week, what’s your reset button? (close-ended, with options like alone time at home and going out and socialising)
New city, new hobby, new anything. How do you feel about the unknown? (close-ended, with options like love it and prefer to stick to what I know)
When you’re feeling a lot, what do you actually do about it? (close-ended, with options like express openly and through actions rather than words)
How do you like to be loved? (close-ended, pick up to three, with the five love languages as options)
How do you express love? (close-ended, pick up to three, also with the five love languages as options)
Non-stop texting, or comfortable silence. Where do you land? (close-ended)
Mid-disagreement, what’s your gut instinct? (close-ended)
Paint us a picture. What does your dream first date look like? (open-ended, optional)
What are your non-negotiable green flags in a partner? (pick 3 that matter most to you, out of options like kindness, humour, and honesty)
Are you always working on yourself, or is “good enough” good enough? (close-ended)
Do you see yourself having children? (close-ended, with options like yes, open to it, and definitely not)
Saver, spender, or “I’ll figure it out eventually”? (close-ended)
What’s your religion, if any? (close-ended)
Any hard nos for you? Be honest, we won’t judge. (close-ended, optional, with options like smoking, different dietary needs, and someone of a different religion)
What’s the youngest age you’d consider dating? (open-ended)
What’s the oldest age you’d consider dating? (open-ended)
Write a short note for your future match! Tell us about yourself in a few sentences. (open-ended)
Subscribe for free to receive new posts and support my work.
After a question about the name you prefer to go by and your mobile number, the questionnaire also collects information about how many first dates you’ve been on in the past year, whether you’ve used a dating app or matchmaking service before, and when you last went on a first date.
An earlier prototype of GovTech’s dating service proposed free meals for first dates, which is what I assume all the food-related questions are for.
But how will the rest of the data collected through these questions be used? The fascinating history of the Gale-Shapley Stable Marriage Algorithm (also known as the deferred acceptance algorithm) gives us some clues.
Before the algorithm earned its name, a similar system was used to match medical school residents with residency programmes in hospitals in the United States since the 1950s. After an interview process, doctors and hospitals provide a rank ordered list of their preferences, which the algorithm turns into a stable match.
What makes the match stable is that after all the matching has concluded, no pair would rather be paired with one another over their current partners.
Confused? This YouTube video explains it better than I can:
What made the algorithm so novel was that it proved that such a stable match always exists when there are equal participants of each type (and that there is a solution to achieve it). The 2012 Nobel Prize in economics went to one of the mathematicians who developed the algorithm (Shapley) and an economist who pointed out the medical resident example and used it to develop other real world applications.
It’s called a marriage algorithm because the theory used marriage proposals as a memorable but theoretical example. The real world applications of the algorithm (like school choice systems) tend to have little to do with dating, for reasons that I’ll elaborate on below.
What does this mean for those signing up to FirstDate? Well, the algorithm is why FirstDate’s matching takes place in what its developers call “cycles” or “programmatic rounds”.
Presumably, the algorithm uses each user’s questionnaire answers to rank all participants of the opposite gender based on compatibility. The algorithm then matches everyone until all couples are in stable matches (see above).
After you decide to say yes or no to your match, that’s it for the cycle. You’ll have to wait for the next one to get a new stable match with a new pool of participants.
From my perspective, there are three glaring issues that emerge when applying this kind of game theory to dating:
Problem 1: The algorithm was intended as a solution to a matching problem where there are two groups of people that need to be paired with the other, such that no two people would both prefer each other over the partners they are assigned.
This is not a guarantee that the match will be a satisfactory or happy one. It is only a guarantee that they will not prefer someone else who also prefers them in the pool. (Side note: While the nature of the algorithm might imply that same-sex pairings are not possible, other dating-related implementations of the algorithm have allowed for same-sex pairings. It is doubtful that this will happen here though, because, well, Singapore.)
This is why the algorithm has been so useful in contexts like matching medical school residents to hospitals, school choice systems, or matching US army recruits to their units. These are matches that participants have committed to, even if the outcome is not their ideal or top choice.
All of this is further complicated when there are outside options. Like, say, other online dating services or your workplace crush who isn’t participating in the process. Because there is no commitment to the process (because this isn’t your state-assigned waifu, thank god), the maths that underpins the algorithm doesn’t really make sense.
We just need to look at the biggest example of a dating app using the Gale-Shapley algorithm: Hinge. The company claims to use the algorithm, using your past behaviour to deliver the “most compatible” matches that you occasionally see surfaced to the top of your feed. Are they the most compatible within the app? Possibly! Do you care? Probably not!
In short, stable matches mean nothing when nobody is committed and the best options might exist outside of the matchmaking pool.
In 2024, I interviewed one of the folks behind the Aphrodite Project, a university-based matching system that spits out just one ideal match each year, using a modified version of the Gale-Shapley algorithm. Their users definitely don’t experience swiping fatigue, but, notably, even with just the one algorithmically-determined match each cycle, people still get ghosted.
Problem 2: The algorithm was designed to match people in terms of ranked preferences.
This becomes an issue when the questionnaire includes open-ended fields and ambiguous questions without a clear objective indication of how it translates to preference, in that it often conflates who you are with what you want. For instance, if you value humour in a partner, does that mean that you’re a good match for someone who also values humour in a partner?
If you’re a gym rat, does that mean you also want to match with other gym rats?
Subscribe for free to receive new posts and support my work.
Another sign that a questionnaire isn’t the best way to understand preferences is that the forerunner example of the algorithm in action had medical residents and hospitals submit their preferences after they had conducted interviews with each other.
Basically, the information gathering process matters for determining what one’s preferences even are and it isn’t clear that a questionnaire is the ideal way for daters to signal their preferences to each other (or in this case, an algorithm), despite what the creators of OKCupid and compatibility questionnaires in lifestyle magazines might argue.
Problem 3: Finally, and most importantly, it is not at all logical that dating successfully is about finding the person who most matches your stated preferences. In this regard, FirstDate is really not unlike the online dating apps that it is looking to innovate on.
This point is so important that it bears repeating: The problem with modern dating is not simply a problem of mismatched preferences!
According to FirstDate’s website, it “started with a question among a group of GovTech officers: does having more potential matches necessarily make it easier to find a suitable match?”
This is a similar diagnosis to what the folks behind the Aphrodite Project came to, but I feel that it captures an incomplete part of the whole picture.
The rise of online dating paralleled the rise of a particular way of thinking about love that’s more checklist oriented than it is holistic, where daters increasingly screen their options ahead of time against a predetermined list of green and red flags.
This checklist of things is, in my view, one of the biggest issues with online dating, in that it tends to amplify and exacerbate our personal biases rather than inviting us to step outside of them. What’s the common denominator to being constantly unlucky in love? Why that, dear reader, is you.
How does a system for matchmaking people account for the fact that the people who need matchmaking also tend to be the worst at understanding what they really want in a relationship?
Let me paint you a picture of what seems to be the common dating experience in Singapore: You’re on a first date with someone in a chain restaurant in a mall somewhere in central Singapore. The conversation revolves almost entirely around the biodata and information that HR and recruiters would collect from you.
Where do you live? Where did you study? What job do you have?
There’s nothing innately wrong with having preferences relating to these things, but dating that’s all about these preferences betrays a deeply transactional and instrumentalist view of love that sees other people not as potential life partners, but pathways to potential lifestyles. Not lovers, but co-owners of a financial venture. Not people, but breeders of sought-after children.
It’s a mindset that’s enabled by the market-driven logic of dating apps,