4 ms·

To be clear I'm not making any statements about the creator, I imagine this is a reflection of the dataset: but the fact that there are so many categories for e

To be clear I'm not making any statements about the creator, I imagine this is a reflection of the dataset: but the fact that there are so many categories for east Asian (Chinese, Japanese, Korean, and I hazard that the "Asian" tag would probably mostly generate east Asians) says volumes about the sexualizing gaze cast on Asian women. While certainly there's an ethical argument over such an algorithm (both for and against) with regards to sex workers and exploitation, it seems to me that the granularity of choice and what choices are available to the consumer also may require additional consideration, lest it reinforce negative stereotypes, introduces new stereotypes, or allows for harmful attitudes to be stimulated. I'm not trying to be sanctimonious or overly moralizing, but half the tags I would associate with ethnicity are east Asian. And while I lean towards treating it as a mere curiosity, I think it's worth discussing as having unintended consequences and interesting implications at the very least.

gricardo99 4y ago
You raise some very interesting points. For me this also demonstrates how deeply rooted, historical bias and prejudice bleeds through to this technology and could become a perpetuating factor. These models will reflect societal values, for better or worse. But also what will the next model, and successive models, that are trained on data from AI generate images, be like? It seems you could get an amplified or skewed model that is pretty far from reality. At least currently they are all trained on “real” images (granted some images are heavily edited or photoshopped). I can imagine that In the (not too distant) future most images will be generated and not “real”.
- lofatdairy 4y ago
  Yeah, I wanted to stress that the categorizations seem more to me to be symptomatic than a reflection of OP's decision making. I loathe the label "problematic", but it seemed worth noting a potentially unintended consequence that could introduce some harms. That said, it might be too early to speculate on models trained on the outputs of other models. This algorithm seems to benefit greatly from the post-DALLE 2 art-gen renaissance, but still has a number of oddities and uncanny outputs (noted in the rest of this thread) that I imagine are nearly unavoidable given how familiar the human form is. But certainly, if such decisions end up amplified in later work, or through widespread usage, then the consequences are more significant than, say, simply reflecting uncritically a skewed data set.
Jensson 4y ago
Blonde, brunette, ginger and white all refers to Europeans, which represents less people than the Chinese tag alone, so it doesn't seem like it fetishizes Asians more than whites. The strange part is why we don't have equally rich categories for Africans. Native Americans not having their categories makes sense since there are so few of them left today, so Africans are the only large group left out.
- lofatdairy 4y ago
  I thought about that while writing my comment, but while hair color correlates pretty well with ethnicity, the level of granularity given to Asians still seems somewhat unique. There are, for instance, no distinction between French and Italian, nor British and Scottish categories. Blonde and ginger do have fairly ethnic implications, but not many people would answer with their hair color if asked where their family originates. That, and the fact that these hair colors are not restricted to white people, due to multi-ethnicity being a thing, as well as commercial hair dye, made me drop them in my "half the ethnic labels" comment (though I will concede that the image in most people's heads when hearing any of those terms would be a white person). This is also coming from a perspective where I'm assuming that the audience for this algorithm (outside of academic consideration) would be westerners where white people tend to be the majority. In that case fetishization generally would only apply to racial minorities, due to the fact that the term seems to imply a sexually gratifying quality to the "uncommon". I add that, speaking as an Asian American, that it's not necessarily all that easy for most people to tell Chinese from Japanese from Koreans, whereas it's basically tautologically given that a blonde can be differentiated from a brunette since the terms are more strictly aesthetic rather than geographic. On your point about Africans, I would extend it to both Latina and the fact that "Indian" seems to be a catch-all for any South Asians. Middle Easterners are also not represented (though this doesn't strike me as a thing where racial equality is necessarily desirable). However, this is where I think the data set is mostly responsible.
  - numpad0 4y ago
    I think they took the tags from some uploader website. CJK ethnicities can be inherently identified by types of sources(smuggled amateur films, commercially made, etc) as well as by styles, when appearing in those sites.
golemiprague 4y ago
tsol 4y ago
This is one of the most interesting comments here. I notice a lot of biases in image generation AI, it's so subtle it's almost at an ideological level. The style of art it creates, the color and dress of the people it generates-- there are little things that that make you wonder "why this instead of something else?"
lodi 4y ago
> but the fact that there are so many categories for east Asian... says volumes about the sexualizing gaze cast on Asian women I think you're reading too much intent into 4 labels. From an American perspective, Japanese was the original--commercial, censored--"Asian" porn, "Chinese" is typically amateur uncensored, etc. I... won't elaborate further here, but there are stylistic differences that have nothing to do with race.
- Kye 4y ago
  The tags should reflect that if it's really about the niche and not the ethnicity.
garmanarnar 4y ago
Keep in mind this AI is biased towards white men's interests which means it heavily fetishizes and degrades Asian women. Even searching for other races shows predominantly Asian women in the results, its quite disturbing.

gricardo99 4y ago

You raise some very interesting points. For me this also demonstrates how deeply rooted, historical bias and prejudice bleeds through to this technology and could become a perpetuating factor. These models will reflect societal values, for better or worse. But also what will the next model, and successive models, that are trained on data from AI generate images, be like? It seems you could get an amplified or skewed model that is pretty far from reality. At least currently they are all trained on “real” images (granted some images are heavily edited or photoshopped). I can imagine that In the (not too distant) future most images will be generated and not “real”.

lofatdairy 4y ago
Yeah, I wanted to stress that the categorizations seem more to me to be symptomatic than a reflection of OP's decision making. I loathe the label "problematic", but it seemed worth noting a potentially unintended consequence that could introduce some harms. That said, it might be too early to speculate on models trained on the outputs of other models. This algorithm seems to benefit greatly from the post-DALLE 2 art-gen renaissance, but still has a number of oddities and uncanny outputs (noted in the rest of this thread) that I imagine are nearly unavoidable given how familiar the human form is. But certainly, if such decisions end up amplified in later work, or through widespread usage, then the consequences are more significant than, say, simply reflecting uncritically a skewed data set.

Jensson 4y ago

Blonde, brunette, ginger and white all refers to Europeans, which represents less people than the Chinese tag alone, so it doesn't seem like it fetishizes Asians more than whites. The strange part is why we don't have equally rich categories for Africans. Native Americans not having their categories makes sense since there are so few of them left today, so Africans are the only large group left out.

lofatdairy 4y ago
I thought about that while writing my comment, but while hair color correlates pretty well with ethnicity, the level of granularity given to Asians still seems somewhat unique. There are, for instance, no distinction between French and Italian, nor British and Scottish categories. Blonde and ginger do have fairly ethnic implications, but not many people would answer with their hair color if asked where their family originates. That, and the fact that these hair colors are not restricted to white people, due to multi-ethnicity being a thing, as well as commercial hair dye, made me drop them in my "half the ethnic labels" comment (though I will concede that the image in most people's heads when hearing any of those terms would be a white person). This is also coming from a perspective where I'm assuming that the audience for this algorithm (outside of academic consideration) would be westerners where white people tend to be the majority. In that case fetishization generally would only apply to racial minorities, due to the fact that the term seems to imply a sexually gratifying quality to the "uncommon". I add that, speaking as an Asian American, that it's not necessarily all that easy for most people to tell Chinese from Japanese from Koreans, whereas it's basically tautologically given that a blonde can be differentiated from a brunette since the terms are more strictly aesthetic rather than geographic. On your point about Africans, I would extend it to both Latina and the fact that "Indian" seems to be a catch-all for any South Asians. Middle Easterners are also not represented (though this doesn't strike me as a thing where racial equality is necessarily desirable). However, this is where I think the data set is mostly responsible.
- numpad0 4y ago
  I think they took the tags from some uploader website. CJK ethnicities can be inherently identified by types of sources(smuggled amateur films, commercially made, etc) as well as by styles, when appearing in those sites.

golemiprague 4y ago

tsol 4y ago

This is one of the most interesting comments here. I notice a lot of biases in image generation AI, it's so subtle it's almost at an ideological level. The style of art it creates, the color and dress of the people it generates-- there are little things that that make you wonder "why this instead of something else?"

lodi 4y ago

> but the fact that there are so many categories for east Asian... says volumes about the sexualizing gaze cast on Asian women I think you're reading too much intent into 4 labels. From an American perspective, Japanese was the original--commercial, censored--"Asian" porn, "Chinese" is typically amateur uncensored, etc. I... won't elaborate further here, but there are stylistic differences that have nothing to do with race.

Kye 4y ago
The tags should reflect that if it's really about the niche and not the ethnicity.

garmanarnar 4y ago

Keep in mind this AI is biased towards white men's interests which means it heavily fetishizes and degrades Asian women. Even searching for other races shows predominantly Asian women in the results, its quite disturbing.