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Researcher Trying To Teach Computer What Women He's Attracted To

jfruh writes: Harm de Vries, a post-doctoral researcher at the Université de Montréal, is trying to build an algorithm that will sort through pictures on Tinder and OKCupid and pick out women he'll find attractive. "Tinder kept giving me pictures of girls I wasn't attracted to," he said in a phone interview. "So I wondered if I could use deep learning." His program, built using deep learning techniques, has about a 68 percent success rate, which isn't that bad. (A human friend to whom de Vries described his preferences managed 76 percent.)

10 of 181 comments (clear)

  1. Female and alive. by harrkev · · Score: 4, Funny

    Let me guess: female and alive.

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  2. It is by will alone I sent my mind in motion... by Anonymous Coward · · Score: 4, Funny

    ...wait, opps, wrong de vries....

  3. Re:bullshit, guys don't get dates by Anonymous Coward · · Score: 5, Insightful

    I'm sure if it was a woman looking to filter men this project would be lauded as 'empowering.'

  4. Is this really a problem? by NotDrWho · · Score: 5, Funny

    I usually just type in "blonde Thai ladyboy" into the search box and the results are almost 100% what I'm looking for.

    Is that so hard?

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    SJW's don't eliminate discrimination. They just expropriate it for themselves.
  5. Wierd by Tailhook · · Score: 5, Funny

    The guy is creating a profile selection algorithm to sift through mostly fake algorithmically generated profiles because the fake profile site's own selection algorithm is inadequate.....

    Sexbots are going to be really, really popular.

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  6. Re:Shallow by circletimessquare · · Score: 5, Insightful

    actually the idea is to like the looks first, then talk to her. then reject the ones you dislike based on personality

    so you get physical attraction and personality compatibility. both

    if you just talk to girls and find someone you're compatible with on a personality level but you don't want to have sex with because they're physically unattractive to you, the term for that is "friend" (as an aside, many, many men posting on this site probably know this zone well)

    what you call shallow is actually called mate selection. if you can't get an erection, you're not going to procreate. mate selection is not friend selection. friend selection is a different topic. to not realize the difference is... shallow, ironically

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  7. How about a real challenge? by Kiyyik · · Score: 4, Funny

    Let's see if he can use deep learning to filter only the women that would have anything to do with someone who would do this.

  8. Re:bullshit, guys don't get dates by Anonymous Coward · · Score: 5, Insightful

    I'm sure if it was a woman looking to filter men this project would be lauded as 'empowering.'

    Tinder and similar apps are already doing this, both for men and women, and nobody but passive-aggressive gamergaters are bringing the misogyny discussion into this. Calling it shallow is fair, both for men and women, but is something a significant portion of both genders do.

  9. if at first you don't succeed, try the opposite by Pseudonymous+Powers · · Score: 5, Funny

    Researcher Trying To Teach Computer What Women He's Attracted To

    Well, at least he's trying something new. The usual, and completely wrongheaded, approach a computer nerd uses when trying to get laid is to try to teach women he's attracted to about computers.

  10. Needs more statistics by Idarubicin · · Score: 4, Insightful

    Neither the summary nor the linked article provide the necessary statistics to tell us how well this algorithm actually works. We're told it has a 68% success rate, which presumably means that 68% of the time it gives the same answer as de Vries (the human subject/programmer).

    The problem is, we're not told anything about the sensitivity or specificity of the technique. What is the rate of false positives? False negatives?

    Let's say that de Vries typically finds 1 out of 3 (33%) of the profile pictures "attractive". His computer could score 67% accuracy just by rejecting every single picture. (Such an algorithm would have zero sensitivity, but perfect specificity, and a terrible false negative rate. The "reject-everything" algorithm also scores better the more picky de Vries gets.)

    This sort of story is only interesting if it includes specific information about where and how his algorithm fails (and succeeds).

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    ~Idarubicin