In the first post of this series, I explained what I was out to learn, what I looked at, and how I tagged it. Ultimately, we want to look at the data and be able to answer questions like “Are female AIs more subservient than male AIs?” And in order to do that, we first have to understand what the distributions are for sex and subservience. So let’s talk distributions.
Distribution is a fancy term for how many of each value we see for a given attribute. For example, if we wanted to look at the distribution of eye color across the world, we would count how many browns, blues, hazels, ambers, green, gray, and reds that we see, (finding a way to deal with heterochromia, etc.) and compare them in a bar chart.
Of course eye color is not of interest in this case. For Gendered AI, we are interested in comparing other attributes to gender presentation. We’ll look at the other attributes in later posts, but we’re going to begin with sex ratio, and that will fill up a post all its own.
Simple sex ratio
Author’s request: With that section title I know some hackles are already raised. Please know this is very tough space to write for. Despite having paid for a number of paid content reviews, I may have made some missteps. I am a n00b writer on these topics, and I respond best to friendly engagement rather than a digital pillory.
The very simple explanation of sex ratio is women-to-men. But of course that’s waaaaay too simple for either the real world or our purposes. At the very (very) least, AI might have no gender, so we need a “none” or “other” category. Let’s start with these very oversimplified numbers and move to more detailed later.
The chart shown below shows the data from the survey focusing on simple categories of female, other, and male. The chart shows that AI characters are strongly overweighted male, with a rough ratio of 2 male : 1 female : 0.75 other. The 2:1 M:F ratio is eerily in line with USC Signal Analysis and Interpretation Laboratory’s finding where speaking roles in 1000 scripts they studied, men’s dialogue, and even the number of characters was double (or over) that for women. This is greatly different than the real-world sex ratios of 1:1 as reported in the Wikipedia article about world sex ratios.
I would talk about the weird discrepancies of just this distribution, but any ranting at this point would be overshadowed by the ranting that happens next. Deep breath.
Having an “other” category isn’t enough. After all, characters in one of these bars can be as different as HAL and Gigolo Joe, and that doesn’t seem right. So, let’s break this oversimplification down into more refined bits.
More detailed gender presentation ratios
First, of course, we should note that characters rarely discuss gender directly, and—at least in this sample—discuss gender dysphoria all of never. Also we can’t reach out to ask any of them directly since they’re fictional. So when I speak of gender, it should be read as “gender presentation,” and unfortunately at this point you are stuck with nothing more scientific than my reading of the following four variables.
- Primary sex characteristics, or biological presentation: The presence of masculine or feminine sexual organs. None of the titles I reviewed were pornographic, and full-frontal nudity is pretty rare up until Westworld, so this often comes down to implication. Gigolo Joe, for instance, could not do what must be a key part of his primary function without male sex organs (with all the important caveats that penetrative sex is just one kind of sex), so he is listed as “Masculine” here.
- Secondary sex characteristics, or body presentation: These are much more directly observable, and include those other markers of sex, like facial hair and shoulder-to-hip ratio.
- Voice presentation: This is my hearing of whether the voice has a lower, masculine register, or a higher, feminine register. (In a few cases I checked on the actor listing in IMDB and did web searches for evidence of self-identification.)
- Pronoun presentation: How other characters refer to the AI character with pronouns. R2D2, for instance, has absolutely no sex characteristics, and no voice, but is still referred to as a “he” throughout the Star Wars franchise.
A note on labeling: I’m aware that there are tricky nuances in the labels. After all, how is body not part of one’s biology? But the shorthand proves useful so we can use the shorthand “BIO” and know what it means instead of always having to use the longer phrase “implicit or explicit primary sex characteristics.”
For each AI character, I tagged each of these variables as either Masculine, Fluid, Neutral, Feminine, Unknown, Multiple, Many, or N/A. (The “n/a” may seem weird, but for instance, HAL doesn’t have a body, so primary and secondary sex characteristics are not applicable.)
Combining voice and pronouns into “social”
There are plenty of characters with no voice or non-human voices, and a few characters that are not referred to by pronoun. Since these two indicate a social performance of gender, I treated them in the algorithms as an “OR” when considering stacking. That means if either variable was present, and they didn’t contradict, I counted it the presenting aspect. Compare these two examples…
- Wall·E: N/A Primary, N/A Secondary, masculine voice, unmentioned pronoun = socially male
- R2D2: N/A Primary, N/A Secondary, neutral voice, male pronoun = also socially male
The main thing to note about how these three variables (counting voice and pronouns as “socially”) played out is that they overwhelmingly stacked. That’s not a term of art, so let me explain. It means that if a character has masculine primary sex characteristics, that invariably meant that he also had masculine secondary sex characteristics, and voice/pronouns. If a character had no evidence of primary sex characteristics, but had feminine secondary sex characteristics, she invariably had feminine voice/pronouns.
It makes more sense if I show you. So, here are six representative examples from the survey of how this monosex stacking looks.
I suspect this is an effect of binary concepts of gender on the part of the markers of the sci-fi, implemented as increasingly detailed costumes for the AI. But when you consider these variables, these 6 are a pale semblance of what could be. Include “fluid” or “nonbinary” as a possibility, and don’t bother with stacking, and there are 58 more possible combinations of these variables.
Hey, want to feel both hyper-reductive and overwhelmed at the complexity of gender? Try writing a categorization algorithm for analysis.
Anyway, if they hadn’t stacked like they did, I would have had to describe their genders with a four-part-code that would result in 64 genders. But, because they do stack, that meant there were these 6, plus “multiple,” “genderfluid,” “neutral,” and “none,” for a total 9. Note that online lists of genders vary from the 58 available to Facebook’s users to the 229 found on this more creative list (my favorite is “Schrodigender – A gender which you can both feel and not feel” giving a clue to how serious that particular list is.) So while 9 can feel heavy, it does not compare to the complexity of the real world.
OK, given those descriptions of the subcategories, here’s how the numbers played out in the much more detailed analysis of gender presentation in sci-fi AI.
Detailed gender presentation
I’ve noted that we’re here for the correlations, not distributions, here, but in and of itself, this is remarkable. The subcategories provide a deeper (and more troubling) look into the data, and is necessary because these categories have to be thought of differently. Observe, for example, that the biologically-gendered characters are nearly at parity, while the bodily- and socially-gendered characters skew male. There is a frustrating 2:1 ratio for bodily male:bodily female and an infuriating 5:1 for socially male:socially female.
These ratios bear…discussion.
1 biologically male : 1 biologically female
A harsh interpretation of this stat would read a kind of heterosexual panic, where—when sex or procreation is involved—Hollywood needs to assert loudly over a hastily-ordered beer that whoa whoa whoa: Only AI chicks and AI dudes get it on. Or if they do get it on with people it’s with the right gender.
Or, more charitably I suppose, humans are largely heterosexual, and since there is a rough 1:1 sex ratio in humans, there should be a 1:1 sex ratio in them. (?) It’s a hard thing to second-guess.
It gets darker in the other categories where the sci-fi AI has a body but no biological apparatus. The ratios still skew heavily male. As if, when it comes to just being a person, a total sausagefest is the norm.
2 bodily male : 1 bodily female
Recall from above that this category is reserved for those AI characters that present a gendered body but do not have gendered reproductive or sexual capabilities. We will discuss the germane-ness and embodiment of these AIs in a later post, but for now we can note that this category of AI character, with its 2:1 ratio is roughly in the middle between the biologically and socially gendered categories, and in-line with the oversimplified distribution seen above.
5 socially male : 1 socially female
This is the category where the only markers of gender are voice and pronouns. In other words, characters for whom a gender seems like an arbitrary choice. WTF is up with a 5:1 ratio? Why are all these “arbitrarily” gendered AI characters guys? We’ll talk about germaneness to the story later, but I want to see if there is some extradiegetic reason first.
Is it the available voice talent?
We have to acknowledge that filmmakers must hire someone to voice their speaking AI characters, even if there are no other markers. Despite the fact that…
- Androgynous voice actors exist
- Genderless synthesized voices are (admittedly, more recently than any entry in the survey) available
- An actor of one gender can sometimes voice a differently-gendered character
…it’s fair to say that most available voice talent is recognizably gendered, and the AI character may just inherit the presentation of its actor. Then you might expect the roles to match the sex ratios in the available talent pool. I couldn’t find any formal studies of this, so I created a throwaway account on voice.com—a major job site for voice actors—and performed separate searches for male and female talent. There I found 42,786 males, and 24,347 female non-union voice actors, around 2:1. (Union actors were closer to 1:1, with 3,079 male and 2,336 female. n.b. The site gives only those two gender options in its search.) Though that’s more anecdotal than I’d like, even the worse ratio of 2:1 still pales compared the 5:1 of socially gendered AI, so no, that’s not it. You might think that explains the “simply” gendered characters, but my suspicion is that the genders of the characters are set in the script and pass down through the process, unquestioned after that.
Is it what sci-fi audiences want?
Might the ratio be some sales rationale, some presumption that sci-fi audiences are mostly men and therefore might only be more interested in male characters? No, of course numbers vary by show and genre, but this article by Victoria McNally shows that there is only a slight majority of men in these audiences (hovering around 60% male and 40% female, rather than 73% male and 17% female, which the 5:1 socially gendered ratio would have you believe.)
Plus the 2018 annual Hollywood Diversity Report by UCLA shows that “new evidence from 2015–16 suggests that America’s increasingly diverse audiences prefer diverse film and television content,” so we would have to greatly exaggerate the connection between the sex ratio of the audience and those we see here.
There has to be some other reason, and I suspect it’s the dark patriarchal notion that “male” is somehow the default gender. Even though it is, literally, not.
Is it that Hollywood itself is mostly white and male?
The 2018 Hollywood Diversity Report shows that gatekeepers, writers, directors, and (points at self) critics are still overwhelmingly white and male. White male writers and directors account for 91.9% and 86.2% if their fields, respectively. This is closer to the 73% male, but still a crappy, crappy excuse for the default assignment of AI as male. Representation matters and this is sorry representation.
P.S. Don’t get uppity, real world
The Global Gender Gap Report issued on 17 DEC 2018 by the World Economic Forum showed (in collaboration with LinkedIn) that women only occupy 22% of jobs in AI professions. (See page viii, 28–35 of that report.)
You probably had a general sense of this disparity from simply being an audience member. But it’s “nice” to have some data to back it up. Be forewarned: It gets worse when we look at correlations. (No, really.) But before we do that, we should look at the rest of the distributions, in the next post.