4 ms·

Stable Diffusion: What Does a Technical Author Look Like?

14 points by djha-skin 4y ago

cs702 4y ago
To no one's surprise and to almost everyone's disappointment, the model has learned from pictures on the Web that such an author looks like a white guy, usually older than 30, with a simple/bad haircut, exhibiting varying degrees of unkempt facial hair, typically wearing thick glasses, standing in the middle of a bland-looking room... and ticking every other checkbox that goes with the stereotype. At present, that stereotype accurately represents reality. Oh, and some of the faces are... recognizable (e.g., one of the images looks like a younger Geoff Hinton with facial hair and an early-Beatles haircut). Along with most people on HN, I look forward to a future in which the training data, and the generated images, will be more diverse.
wincy 4y ago
I mean there’s a headshot of Martin Fowler on the page and… he looks a lot like the generated pictures. If his headshot was in there I wouldn’t have thought it was out of the ordinary.
colordrops 4y ago
Perhaps an unpopular opinion, but isn't the model just representing the world as it is, rather than what we want it to be? I'm all for the diversification of various fields traditionally dominated by a specific cohort. But are data models the right place for that activism? It feels wrong to me to make the data biased and different from reality, even if for a good cause. Where does it end? You won't know which results from the model are based on typical distributions in fact and which are due to intentional tweaks for one agenda or another.
- majormajor 4y ago
  The right place to start is probably at the pre-K level. https://press.princeton.edu/books/hardcover/9780691171807/can-college-level-the-playing-field https://press.princeton.edu/books/hardcover/9780691171807/ca... / book discussed well at https://crookedtimber.org/2023/02/06/can-college-level-the-playing-field-no-it-really-cant/ https://crookedtimber.org/2023/02/06/can-college-level-the-p... But most people feel powerless to do anything about that so ... the discussion instead lands in whatever they are familiar with.
- dragonwriter 4y ago
  > Perhaps an unpopular opinion, but isn't the model just representing the world as it is, rather than what we want it to be? Probably not, becayse its trainung data almost certainly has biases compared to “the world as it is”, and the model itself has some error with regard to the training data. It's representing one view of the world seen through multiple levels of filters each with their own set of (systematic or random) biases. (Which is not too dissimilar to any individual human, but any widely used model's biases are likely to have much wider impact than any single human’s.)
  - colordrops 4y ago
    Sure, it absolutely makes sense to adjust models to account for biased inputs. Say for instance the pictures you train on are from tundra but you want to use the model in a jungle region. But you should use vetted stats to determine the nature of the landscape to feed them model (e.g. 95% of land is jungle, so feed 95% jungle images), rather than feeding it tundra images because you think the jungle is too hot.
    - dragonwriter 4y ago
      If its a model for art, I’ll absolutely feed it tundra images if I think the jungle is (or just looks) too hot. Of course, I’ll also embrace the projected cool vibe of the resulting imagery as a feature, and won’t object to people pointing out that the model is biased toward tundra over jungle and that is something users who aren’t actively looking for that bias might want to be aware of.
kleiba 4y ago
The results speak volumes about the current state of AI. And perhaps of our broader society - at least as the internet sees it. ...just not to me, unfortunately. What is the beef we're having? That there's not enough variety? That it's all guys? That they're all white? That they're all bearded? What is it?
- kleiba 4y ago
  I bet if he had tasked a human illustrator with creating a painting of a technical author, chances are it wouldn't have been of an elderly black woman either. I mean, that is not to say that there aren't any technical writers who are elderly black women. But the odds that a randomly picked technical writer resembles one of the stable diffusion creations are probably higher.
- dragonwriter 4y ago
  > That there's not enough variety? That it's all guys? That they're all white? That they're all bearded? Well, yes, all of that. Its 4 gens of 4 images each, and its 16 white, 16 bearded, 16 men, 15 with glasses, and pretty much all middle aged. That’s an extraordinarily lot read into the prompt. (I also think its something about the hidden prompting or fine tuning of the model of the particular site they are using; i can’t get anything with that little diversity out of DreamStudio or clipdrop — StabilityAI’s first party frontends which use SDXL — or my own local testing with the SD1.5 and SD2.1-768-based models I use; heck, base SD or most checkpoints that aren’t specilaized for the purpose aren’t that consistently biased toward photographic style, leaving out the demographic biases the results shown.)
erulabs 4y ago
Ah, the ouroboros raises its head once more. If we force the machine to show a statistically representative group, are we being more or less racist than if we tell it to show us reality? Is there any meaningful difference between reality and what we expect? If too many technical writers are white, are we being racist to try to change that? Was it racism that led to the situation in the first place? If we "fix" it, are we making the world better, or worse? Murray Rothbard, one of my favorite historians, has a brief aside about the Washington monument that I quite enjoy: If a state forces a statue into place - how can it be taken down? Not by planned action of another state - we've changed nothing - we're just in a different, statue-less planned state. Rothbard contends the only way is revolution - ie: the statues must be pulled down by a spontaneous mob. Only then can we have a starting square to begin sinlessly from. I do not like this idea, but I cannot reason my way around it either. Mirrors will always show us what we don't want to see. When we make a mirror that does not, it will no longer be a mirror.
- majormajor 4y ago
  > Not by planned action of another state - we've changed nothing - we're just in a different, statue-less planned state. Some planned states (or even state-planned states) are preferable to other planned states; I completely fail to see his objection to that. Revolution and starting without a plan (I disagree that most revolutions start without a plan, though) runs much more "what if we end up worse" risk. In the US the answer to many of those race-based questions is, yes, racism played a big role. This is harder to see now than it was 60 years ago when many present policies and goals were formed, when it wasn't just "individual racists" but obviously-racist states and laws and policies. The need to counteract those past effects can be seen in the names of some of the results: "Affirmative Action," for instance, is very obviously about taking action to counteract it, without today's qualms about "but is that itself racist?" Today the argument is also about "in the places that it has not yet fully balanced things, why" and hence the discussion of things like "systemic racism" (take away a families money and opportunities for 100 years, see how well they do in the following century compared to one that wasn't attacked; etc).
  - erulabs 4y ago
deleted 4y ago
[deleted]
prepend 4y ago
These all look like good representatives of technical authors. I think if you show those generated images to a population and asked if they thought they looked like a technical author, the population would agree. So it seems like StableDiffusion is doing a pretty good job. Maybe this is a side commentary on sexism or racism or something in the technical author field, but it’s pretty funny that Martin Fowler, the living embodiment of the stereotype of white, middle-aged, male, beardo tech guy is publishing this article. If this stereotype results in some privilege in the world, then Fowler is likely a huge beneficiary of it. I did some playing around with SD too with just “portrait of an apple” and it doesn’t generate a unique diversity of all the types of apples in the world. And it doesn’t even proportion the images based on sales or popularity or season. I don’t think this is a statement on the bias in AI toward a particular apple type.
williamstein 4y ago
A google image search for "Technical Author" has a lot more women in the results, and also this very article lower down the page...
dragonwriter 4y ago
Not sure what “Stable Diffusion” this is using; the interface doesn’t look like either of the StabilityAI frontends (clipdrop or DreamStudio) that make the newest model (SDXL) available, looks like maybe stablediffusionweb? Doing some quick testing on ClipDrop, the sets I’ve run have been overall – and mostly individually for each set of four – more diverse than their results (using no style filter, and the analog film, photographic, and cinematic styles) in gender, race, and (for the men) facial hair style or lack thereof. (Heck, I don’t keep the base models around, but my usual first-choice-for-general use SD1.5-based checkpoint is a lot more diverse on this prompt, too — a explicit style prompting; i wonder if the site they are using is doing a lot of extra hidden positive and/or negative prompting — or a fine-tuned model w that might be introducing additional bias — to get what they feel is a consumer-friendly look from quick prompts.)

14 points by djha-skin 4y ago

To no one's surprise and to almost everyone's disappointment, the model has learned from pictures on the Web that such an author looks like a white guy, usually older than 30, with a simple/bad haircut, exhibiting varying degrees of unkempt facial hair, typically wearing thick glasses, standing in the middle of a bland-looking room... and ticking every other checkbox that goes with the stereotype. At present, that stereotype accurately represents reality. Oh, and some of the faces are... recognizable (e.g., one of the images looks like a younger Geoff Hinton with facial hair and an early-Beatles haircut). Along with most people on HN, I look forward to a future in which the training data, and the generated images, will be more diverse.

wincy 4y ago

I mean there’s a headshot of Martin Fowler on the page and… he looks a lot like the generated pictures. If his headshot was in there I wouldn’t have thought it was out of the ordinary.

colordrops 4y ago

Perhaps an unpopular opinion, but isn't the model just representing the world as it is, rather than what we want it to be? I'm all for the diversification of various fields traditionally dominated by a specific cohort. But are data models the right place for that activism? It feels wrong to me to make the data biased and different from reality, even if for a good cause. Where does it end? You won't know which results from the model are based on typical distributions in fact and which are due to intentional tweaks for one agenda or another.

majormajor 4y ago
The right place to start is probably at the pre-K level. https://press.princeton.edu/books/hardcover/9780691171807/can-college-level-the-playing-field https://press.princeton.edu/books/hardcover/9780691171807/ca... / book discussed well at https://crookedtimber.org/2023/02/06/can-college-level-the-playing-field-no-it-really-cant/ https://crookedtimber.org/2023/02/06/can-college-level-the-p... But most people feel powerless to do anything about that so ... the discussion instead lands in whatever they are familiar with.
dragonwriter 4y ago
> Perhaps an unpopular opinion, but isn't the model just representing the world as it is, rather than what we want it to be? Probably not, becayse its trainung data almost certainly has biases compared to “the world as it is”, and the model itself has some error with regard to the training data. It's representing one view of the world seen through multiple levels of filters each with their own set of (systematic or random) biases. (Which is not too dissimilar to any individual human, but any widely used model's biases are likely to have much wider impact than any single human’s.)
- colordrops 4y ago
  Sure, it absolutely makes sense to adjust models to account for biased inputs. Say for instance the pictures you train on are from tundra but you want to use the model in a jungle region. But you should use vetted stats to determine the nature of the landscape to feed them model (e.g. 95% of land is jungle, so feed 95% jungle images), rather than feeding it tundra images because you think the jungle is too hot.
  - dragonwriter 4y ago
    If its a model for art, I’ll absolutely feed it tundra images if I think the jungle is (or just looks) too hot. Of course, I’ll also embrace the projected cool vibe of the resulting imagery as a feature, and won’t object to people pointing out that the model is biased toward tundra over jungle and that is something users who aren’t actively looking for that bias might want to be aware of.

kleiba 4y ago

The results speak volumes about the current state of AI. And perhaps of our broader society - at least as the internet sees it. ...just not to me, unfortunately. What is the beef we're having? That there's not enough variety? That it's all guys? That they're all white? That they're all bearded? What is it?

kleiba 4y ago
I bet if he had tasked a human illustrator with creating a painting of a technical author, chances are it wouldn't have been of an elderly black woman either. I mean, that is not to say that there aren't any technical writers who are elderly black women. But the odds that a randomly picked technical writer resembles one of the stable diffusion creations are probably higher.
dragonwriter 4y ago
> That there's not enough variety? That it's all guys? That they're all white? That they're all bearded? Well, yes, all of that. Its 4 gens of 4 images each, and its 16 white, 16 bearded, 16 men, 15 with glasses, and pretty much all middle aged. That’s an extraordinarily lot read into the prompt. (I also think its something about the hidden prompting or fine tuning of the model of the particular site they are using; i can’t get anything with that little diversity out of DreamStudio or clipdrop — StabilityAI’s first party frontends which use SDXL — or my own local testing with the SD1.5 and SD2.1-768-based models I use; heck, base SD or most checkpoints that aren’t specilaized for the purpose aren’t that consistently biased toward photographic style, leaving out the demographic biases the results shown.)

erulabs 4y ago

Ah, the ouroboros raises its head once more. If we force the machine to show a statistically representative group, are we being more or less racist than if we tell it to show us reality? Is there any meaningful difference between reality and what we expect? If too many technical writers are white, are we being racist to try to change that? Was it racism that led to the situation in the first place? If we "fix" it, are we making the world better, or worse? Murray Rothbard, one of my favorite historians, has a brief aside about the Washington monument that I quite enjoy: If a state forces a statue into place - how can it be taken down? Not by planned action of another state - we've changed nothing - we're just in a different, statue-less planned state. Rothbard contends the only way is revolution - ie: the statues must be pulled down by a spontaneous mob. Only then can we have a starting square to begin sinlessly from. I do not like this idea, but I cannot reason my way around it either. Mirrors will always show us what we don't want to see. When we make a mirror that does not, it will no longer be a mirror.

majormajor 4y ago
> Not by planned action of another state - we've changed nothing - we're just in a different, statue-less planned state. Some planned states (or even state-planned states) are preferable to other planned states; I completely fail to see his objection to that. Revolution and starting without a plan (I disagree that most revolutions start without a plan, though) runs much more "what if we end up worse" risk. In the US the answer to many of those race-based questions is, yes, racism played a big role. This is harder to see now than it was 60 years ago when many present policies and goals were formed, when it wasn't just "individual racists" but obviously-racist states and laws and policies. The need to counteract those past effects can be seen in the names of some of the results: "Affirmative Action," for instance, is very obviously about taking action to counteract it, without today's qualms about "but is that itself racist?" Today the argument is also about "in the places that it has not yet fully balanced things, why" and hence the discussion of things like "systemic racism" (take away a families money and opportunities for 100 years, see how well they do in the following century compared to one that wasn't attacked; etc).
- erulabs 4y ago

deleted 4y ago

[deleted]

prepend 4y ago

These all look like good representatives of technical authors. I think if you show those generated images to a population and asked if they thought they looked like a technical author, the population would agree. So it seems like StableDiffusion is doing a pretty good job. Maybe this is a side commentary on sexism or racism or something in the technical author field, but it’s pretty funny that Martin Fowler, the living embodiment of the stereotype of white, middle-aged, male, beardo tech guy is publishing this article. If this stereotype results in some privilege in the world, then Fowler is likely a huge beneficiary of it. I did some playing around with SD too with just “portrait of an apple” and it doesn’t generate a unique diversity of all the types of apples in the world. And it doesn’t even proportion the images based on sales or popularity or season. I don’t think this is a statement on the bias in AI toward a particular apple type.

williamstein 4y ago

A google image search for "Technical Author" has a lot more women in the results, and also this very article lower down the page...

dragonwriter 4y ago

Not sure what “Stable Diffusion” this is using; the interface doesn’t look like either of the StabilityAI frontends (clipdrop or DreamStudio) that make the newest model (SDXL) available, looks like maybe stablediffusionweb? Doing some quick testing on ClipDrop, the sets I’ve run have been overall – and mostly individually for each set of four – more diverse than their results (using no style filter, and the analog film, photographic, and cinematic styles) in gender, race, and (for the men) facial hair style or lack thereof. (Heck, I don’t keep the base models around, but my usual first-choice-for-general use SD1.5-based checkpoint is a lot more diverse on this prompt, too — a explicit style prompting; i wonder if the site they are using is doing a lot of extra hidden positive and/or negative prompting — or a fine-tuned model w that might be introducing additional bias — to get what they feel is a consumer-friendly look from quick prompts.)