How Machine Learning Can Transform Online Dating

First time accepted submitter hrb1979 writes "Thought I'd share an interview with Kang Zhao — the professor behind the machine learning algorithm which could transform online dating. His algorithm takes into account both a user's tastes (in an approach similar to the Netflix recommendation engine) and their attractiveness (by analyzing how many responses they get) — enabling the machine to 'learn' and hence propose higher potential matches. His research was recently covered in both a Forbes' article and the MIT Technology Review, though this interview provides more depth and color."

Comments

Not the algorithm we need

[russotto]

All the algorithms in the world aren't going to help when the intersection of "people you'd care to date" and "people who'd care to date you" is empty. What we need is an algorithm to convince people to lower their expectations when they're unattractive, boring, unmannerly, old, poor and/or cheap, have baggage, etc.

I prefer this formula; it's more honest

[tekrat]

The perfect formula for matchmaking:

Males: Enter income.
Females: Enter attractiveness.

Match up most attractive to highest earners.

Re:Dating Algorithm Corollary

[serviscope_minor]

I seldom see drop-dead gorgeous female engineers or scientists....You don't think there is a strong correlation between attractiveness and personal qualities/careers/etc.?

Let us say that intelligence and attractiveness are uncorrelated.

The probability of being both at once is very low, since you're multiplying the two small independent probabilities associated with attractiveness and intelligence.

If, of course you chose any segment of the population not selected specifically for attractiveness, then the probability of any given member being attractive is low.

Drop-dead gorgeous female scientists and engineers are particularly rare because (a) female scientists and enigneers are rare and (b) drop-dead gorgeousness is rare. Even uncorrelated if you multiply those tow probabilities, a small number results.

If you have something where members are chosen for attractiveness then yes, the average member will be more attractive than the average.

Would I say that my fellow scientists and engineers are on average less attractive than a random sampling of the population? That's a hard call. There are whole segments of the population that I rarely mix with which makes such things hard to judge. I never have cause to visit grim, deprived, crime ridden former mining towns of the North for example. But I haven't noticed any particular difference. There's one guy in my office you could easily tell from the outside (long hair, overweight and wearing anime t-shirts is kind of a give away). The rest not so much.