A wide variety of erotic interests.

Here's a question we're often asked about our sexual desire research: Did you guys watch a lot of porn?

As scientists, we are thorough, systematic, and attentive. So, yes—we watched more porn than Hugh Hefner. With a dispassionate eye, we read and watched all internationally popular varieties of erotica: BBWs, Michael Lucas, Harry Potter slash, cameltoes, GILFs, Lauren Dane, futanari, fisting, hurt/comfort fanfic, Buck Angel, bukkake, Sean Cody, JR Ward, wetlook, lions, and tigers, and bears! Oh, my!

I'm sure you haven't heard of all of these, though you may perhaps know a few. Quite possibly there's one you know intimately. Erotica is like dog-whistle politics: we each know and respond to our own specific interests, while others' interests are dull, gross, or offensive.

Since we also collected and analyzed more hard data about humankind's sexual interests than any scientist since Kinsey—and beat him by several orders of magnitude—we're often asked a follow-up regarding our systematic consumption of erotica: Why?

If we can just data mine a billion searches, a million websites, a million stories, a half-million videos, why bother reading and watching all this stuff?

Answer No. 1: So you don't have to.

We're all a little curious about what other persons like. Sometimes it's a nervous, fearful curiosity; too often a disparaging, self-righteous curiosity; most frequently it's the hope to learn how to boost our own desirability to the other. But even though we may want to know what actually turns on men, women, gays, straights, we don't really want to see what turns them on--not the raw reality of it. Let scientists investigate and report back.

Well... we're those scientists.

Answer No. 2: To identify previously undetected differences, similarities, and patterns across diverse erotica. Sure, many important patterns show up in the hard data, such as the cross-cultural interest in viewing large penises among both straight and gay men. But sometimes the only way to identify an interesting phenomenon is to observe it with your own eyes, such as the perfectly complementary role of camera POV in gay and straight porn. Sometimes the only way to spot something intriguing is to read it with your own eyes, such as the divergent ways that men and women write erotic rape stories.

By exposing ourselves to an encyclopedic range of erotica, we were able to catalog numerous sexual patterns and phenomena previously unknown to science. Many of these surprising findings allowed us to generate new hypotheses we could test out using our ocean of online behavioral data. One notable example: Futanari anime eventually led us to our model of "erotical illusions": gender-specific perceptual tricks of the sexual brain.

The first two questions invariably lead to a final inquiry: What was it like watching all that stuff? Since we're both heterosexual males, the vast majority of erotica we read and viewed struck our brains as either somewhat gross (most straight stuff, all gay stuff) or tedious (all women's stuff). Female and gay researchers, naturally, would perceive a different distribution of gross and tedious.

When we started out, a lot of material was very hard to get through. We questioned the value of personal immersion and briefly considered generating our hypotheses solely from the hard data. Eventually, however, we progressed through two more psychic stages.

First, repetition produced habituation. We became desensitized to the content, the way adult webmasters do.  We experienced a kind of attentive detachment, like examining moon craters through a telescope. This was when we were able to start generating productive hypotheses.

But then, to our great surprise, our perspective expanded. We began feeling an empathetic, non-erotic fascination with the myriad vibrant creations of the sexual brain. Something akin to Jane Goodall's or Dian Fossey's compassionate, personal engagement with primates. Ultimately, we observed not only for the science, but for the intricate beauty and marvel of it.

About the Authors

Sai Gaddam, Ph.D.

Sai Gaddam, Ph.D., studies biologically inspired models of machine learning. He is co-author of A Billion Wicked Thoughts.

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