author here, i just realized this site doesn't work on mobile. I used javascript to generate the tables of images. While I blunder through trying to fix this, you can view the pictures here
Agreed. These creepy images make me wonder if some neural net-based text generator could optimize against algorithms detecting both readable English and scary/traumatic/intense/whatever prose.. and produce mental imagery darker than any human author has.
It wouldn't maximize fear response in humans, only in the neural net that results from the training set.
If we get to where we can simulate human neural nets (and identify the "scary" neurons) then we could perform gradient descent against those. That's an interesting concept. I don't know if that's been visited in SF, but it has potential. Imagine a set of not-so-random squiggles that causes uncontrollable fear to its beholder.
There was also an Outer Limits episode with a similar theme if I recall correctly. There is a lot of cross-pollination of ideas, and I think that's a good thing.
So when I was back in high school I was playing around with one of the Kai art programs (I forget which one actually) that let you generate different patterns. I couldn't explain why but the patterns that were kind of regular-ish and curvy/abstract (anything that looked like cells under a microscope or those with a honeycomb-like structure) made me deeply, anxiously, almost panic-attack level uncomfortable. This startled me when it happened the first time. There was nothing at all I could logically connect it to.
The best way I can describe it is that I get that deep stomach-fluttery feeling that comes with being really nervous and apprehensive, but without any of the emotional content of anxiety at all.
I forgot about that experience for a long time, until the first Google 'Deep Dream' images were released. Turns out that the Internet has given this a name - trypophobia (fear of holes). The regular, not-quite-identifiable quality to the images is what seems to do it to me.
Even now, my stomach is fluttering like I'm about to go on a scary roller coaster. Again though, this comes with no emotional panic. I'm not upset by it, it isn't self-reinforcing like anxiety is. It's just a really odd feeling. A very strong 'get away from this' feeling.
I've read the hypothesis that this comes from an instinct to avoid danger, such as beehives and poisonous creatures and that makes a lot of sense (not totally sure from memory though so I might be getting it wrong; I need to find the study I'm thinking of).
So I don't doubt that at least for some people it's possible to synthesize images that provoke a strong physiological response that could make them flee.
Gut instinct wants to say that it's a bit of an uncanny valley experience as well. Our brains are wired to recognize patterns, and seeing something very organic, but also very mechanical just sets off those deep instinctual alarms that something's not quite right.
Is this the track by I-Doser on Spotify? I listened to it with decent headphones and it just seemed like ambient noise with some chanting in the background. Should I have listened to it in a certain setting, or with eyes closed, or while looking at something?
Some of the more abstract images at the beginning really remind me of Beksiński's paintings. (some NSFW, but good, dark art overall) https://art.vniz.net/en/beksinski/ There's just enough of abstract ideas and randomly included genitalia.
(now I really wish someone did a Beksiński + photos mixer... there's ~240 samples just on that site)
A movie called Ostatnia Rodzina (Last Family) about Beksiński family was recently released in Poland (https://www.youtube.com/watch?v=XfFt9RfO9Bc), definitely one of the best movies I've seen this year. Unfortunately I don't know if it will screen outside Poland and UK.
You'll have to translate from polish, but they do send internationally. The email contract is at art@bosz.com.pl
Fun fact: with prints, without seeing the original pictures in his home town you miss out on his notes of what substances did he ingest while painting. (sometimes attached or on the frames if I remember correctly)
It's mesmerizing to see this NSFW detection applied in reverse, and it's even more interesting to observe your mind react to the generated images. You can see the sort-of-mons pubis patterns, the maybe-pubic hair, the perhaps-breasts and the suspiciously phallic appendages, complete with realistic colors.
Interestingly, all exposed skin suggests that the training dataset for the NSFW detection was skewed towards caucasians, given how the synthesized images are near-completely devoid of skin tones other than light pink. Perhaps this is a good visual indication of unintentional 'bias' in datasets?
Who wants to volunteer to acquire and organize a several thousand jpg set of "ebony" category porn and submit it? If training material is required, there's undoubtedly a lot of categorized porn for all possible races in the world already, it's just a matter of getting volunteers to do it.
I'm actually really curious whether nudes of dark-skinned people pass the default model at all. Luckily, detector can be seeded to work with a different model, so we can have several of them; but this would be a useful pull-request.
It may be more beneficial to train for just body feature recognition instead of skin tone because last I saw, from the neck down women have only so much variance across body shapes.
We already have a huge amount of homemade porn by people all across the world, but the dataset is not very well labeled compared to professional mainstream porn and that will impact the research.
In other posts I've seen, generative networks produced biases unrelated to what people consider NSFW such as brighter lip color, so I think restricting features related to anything above the neck or below the knees from impacting the CNNs would be helpful.
I would be curious to know what these images would look like if it were trained on a corpus including both the dataset used AND a dataset of hand-drawn pornography, including anime and 'cartoony' porn. I'd also be curious to know how often this sort of network would bar educational content. There is an important difference between nudity and pornography. It's a distinction that I would think would be very difficult to train any automated system on, but I am prepared to be surprised.
It's the easiest cheapest way nowadays to sound insightful.
Edit: I think I came across harsher than I meant to. All I meant was that we could have simply said I wonder how it deals with different skin tones. Instead, we get into race and biases etc.
Interesting that regarding universities being sued for lack of cc in their free online content everyone was up in arms, but mention the word race and everyone goes on high alert.
I couldn't reply in time before you made your edit, but truthfully I was going to post the same thing: I was struggling with how to phrase my original comment, but I was looking for a shorthand way of saying "people with light pink and white skin" without coming off as either callous or overly euphemistic.
Really, my curiosity stems from being new to how neural networks work -- naively, I've grown accustomed to processes where the outputs reflect the input, and at first blush to me, supposing a varied dataset, this didn't appear to be the case. Those who replied to me provided persuasive arguments as to why the hues of the synthesized images may not necessarily imply that the training dataset wasn't that varied after all.
Now the interesting things is that from what culture roam this dataset was acquired from considering that operating markets of Yahoo are US, Europe, Japan?
Does it resemble demographics of these markets? Or does it represent the desires of these markets?
More importantly is there are a good validation set of subtle examples of something being NSFW and SFW? Especially considering that the subject is mostly defined as I do not know to how to define it I definitely know it when I see it.
when running the experiments, i noticed the neural net responds much more strongly to contrast than color. this is consistent with previous work where the the first layers of a conv net isolate colors in a few filters. i wouldn't read too much into this
This is amazing! I'm particularly pleased to see how it comes out because I remember wanting to do precisely this (generative model plus porn) back in 2000. I had recently seen Geoff Hinton give a talk, and back then I had half my focus on maths and computers and half on art and design. Of course I never got close to doing anything about it :) Maybe it wouldn't have been possible.
I'm not terribly surprised - humans do too. Contrast is well established as being far more important for perceived image 'quality' than color fidelity.
It could also reflect what is most distinguishable. Which is easier for a NN to confidently distinguish: black pubic hair on black skin, or black pubic hair on white skin? Darker nipples on black skin, or darker nipples on white skin? etc You're doing gradient ascent on confidence of classification, not simply trying to find a plausible input, but the maximal input. There's no reason to expect this to be racially unbiased as there are simple objective reasons that higher contrast would be useful. (Similarly, I would not be surprised if a face recognition NN worked better on Europeans rather than Chinese, for the prima facie reason that they have more variable facial features and other aspects like multiple hair colors other than black.)
And since Yahoo needs to detect porn of all races and there's plenty of black porn out there, it would be odd if their porn detector had such a huge gaping hole in it.
> Similarly, I would not be surprised if a face recognition NN worked better on Europeans rather than Chinese, for the prima facie reason that they have more variable facial features and other aspects like multiple hair colors other than black
Hair color, yes, but facial feature variability? I think your perception of more variability in European faces than Chinese ones says more about where/how you grew up than about the actual variability. To someone who grew up in an Asian monoculture, without exposure to media with European faces, all Europeans would look alike too.
Err... I'm not so sure about this. I understand that as you grow up in one community, your brain networks/neurons specialize for distinguishing differences in facial features in that community more than in others. While I haven't seen enough chinese to argue, they have lesser facial feature variations, I can imagine how the algorithm defines facial features would be biased more towards the caucasian/European faces. So from the POV of the "facial feature detection" algorithm, European faces will have more variation in facial features than Chinese faces.
Context: I grew up in southern india and spent most of my early years there, but travelled out to the northern India in the mid twenties. I can now say, I can see facial feature variations in the NE India folks(these folks have facial similarity with chinese) I see around now (I currently live in the south)
>To someone who grew up in an Asian monoculture, without exposure to media with European faces, all Europeans would look alike too.
I'm instead sure about this because of a funny incident that happened to my mother just a few years ago. She was standing near a pizzeria when a chinese waitress stepped out and said (translating from italian, sorry if I make some mistakes):
waitress: "Take away?"
my mother: "What?"
waitress: "Take away?"
my mother:"No, I haven't ordered anything"
waitress: "You Italians! You look all alike!"
It's funny how racial bias always comes out in discussion about NN. It all depends on the training data and that's all there is to it. Yet somehow, some people tend to blame the models or the programmers for not correcting this "bias" that is not "supposed" to be there.
If the output of your fancy new NN classifies black people as gorillas it's absolutely the programmers' fault. It is useless for a large swathe of humanity, it creates a PR nightmare, etc.
It depends on how you define "programmers' fault". In this case it would more a case of needing more training data to correct the mistake, which may or may not be the programmer's fault.
Of course it can be the programmer's fault. Programming NNs is not just about picking an unbiased sample set of data, you need to help the NN know what it's looking for.
As I've explained in https://news.ycombinator.com/item?id=12759089, different races have different sets of facial features which are used for facial recognition (because they vary more). Now, when programming the NN, what if you only told it to look for the set of facial features you thought was important? It's very easy to let unconscious biases seep into your code.
> different races have different sets of facial features which are used for facial recognition
I thought that «race» is a social construct not a scientific one and thus can't be relied on as a deciding factor in a scientific experiment or endeavor like face detection.
"The cross-race effect (sometimes called cross-race bias, other-race bias or own-race bias) refers to the tendency to more easily recognize members of one's own race."
This premise is not well grounded in facts as evidence can show that some people esp. racially unaware, uneducated or desensitized don't fall into this category. To support their claim, they cite a US-only study which can't be sufficient to extrapolate for all humanity as a universal fact since we all know that US society is divided along racial line and it's deeply ingrained into people's minds from childhood.
It's like their caste system and with a highly cultural not scientific element to it.
Yeah, Humans perceive and classify race (accurately or inaccurately) and that's why it can't be a reliable indicator or cornerstone for any reliable scientific system esp. when taking into account the "fluid" or "conflicting" nature of some of the prevailing definitions of races out there.
Actually, no, _some_ humans in certain places / cultures currently perceive and classify race.
The Roman empire spanned swathes of North Africa and had major centres there and traded with subsaharan Africa. And traded with the 'orient' all the way to China.
Their writings don't make racial classifications. They don't even remark much on skin colour or other features.
Visual features were known, but not considered that significant. And later in the empire people from all over the world became Romans via citizenship and what we now call "race" never factored into it.
> I would not be surprised if a face recognition NN worked better on Europeans rather than Chinese, for the prima facie reason that they have more variable facial features and other aspects like multiple hair colors other than black
To people who are used to them. i.e. to you.
I'm Irish, and can tell many Irish accents apart. But I've had people from England not being able to hear the difference between Irish accents, thinking they all just sounded Irish.
I've literally been in a group of Europeans in Africa, and Africans mixing up several of the women there, because they were all relatively tall, slim build, with longish straight brown hair.
> I would not be surprised if a face recognition NN worked better on Europeans rather than Chinese, for the prima facie reason that they have more variable facial features and other aspects like multiple hair colors other than black
This is false. Each individual has a preferred set of facial features that are used to distinguish faces, and this set is usually dependent on our race and/or where we grow up. People of some races look alike to us because they have lesser variability in this set, but may have more variability in a different set of facial features that our mind is not used to looking for.
A face recognition NN would be biased this way only if the training set was biased, or if it was only taught one set of features.
> (Similarly, I would not be surprised if a face recognition NN worked better on Europeans rather than Chinese, for the prima facie reason that they have more variable facial features and other aspects like multiple hair colors other than black.)
You might be surprised to learn that to Chinese people, westerners all look more or less the same. To Africans, white people look more or less the same. Our biological hardware is great at distinguishing minute differences in things (especially people) we are very familiar with, while we automatically start generalizing about things we are less familiar with.
For comparison: a metal fan may be able to distinguish a dozen distinctly different styles of Norwegian Black Metal, while to outsiders it's all loud white noise made by people dressed like undead clowns.
> You might be surprised to learn that to Chinese people, westerners all look more or less the same.
Yes, I would definitely be surprised if Chinese people thought a pale-skinned Irish woman with shocking red hair looked more or less the same as an olive skinned mediterranean brunette.
The fact of the matter is, the greatly reduced range of hair and skin color in the Chinese is a legitimate reason to think they look more "the same" than a European/Westerner. There is undisputably greater diversity in appearance in Europe than China.
The borders of China aren't exactly clear in the image you posted, but here's what I'm seeing:
Europe ranges from 1-14
"Western" ranges from 1-23
China ranges from 12-17
Am I interpreting the image incorrectly? Doesn't it confirm my assertion that China has a smaller range of skin tone?
Edit: The definition of "Western" appears to be very vague, but for reference I referenced at the rough vague shape of the United States to determine the 1-23 figure.
The way I read it almost all of Europe is in the 1-12 range with the exception of Spain. China is 12 to 17 or 12 to 20 depending on how you read the borders. I would eliminate North America from consideration unless we are talking about aboriginals, since it's a melting pot. (That is to say, it goes without saying that it has more variety.)
But my point is only to say that your statement of "greatly reduced range of .. skin color" is a rather exaggerated statement. (For hair color I suppose you might be right ;)
Hard to say due to the lack of precision in the map in the lighter range, but if you think about how incredibly large China is, it stands to reason that your statement might be missing the mark a bit. Especially if you consider other Asian countries. (Which maybe you should, if comparing with "Europe" or "North America"..)
You don't get it. The importance you place on hair and skin color in telling people apart isn't following a set of objective, mathematical criteria, it's a set of priorities based on what you're used to. It is entirely possible someone from a different background thinks of hair- and skin color as irrelevant details, much like you would with a brown and white cow vs a black and white one.
Given a 1 in 10 ratio of blacks in the USA, I expect a similar ratio in porn. It might be different in South America. The algorithmic preference for maximal differences from another comment sounds like a good argument, anyhow.
Strong pink is probably the most common colour across all people for the most intimate parts of the genitals as AFAIK the inner folds and spread appearance of all types of vulva are pink. All tongues and palms are pink too [AFAIK], they probably feature highly in porn compared to in other images. If you were then looking at pictures of black women, say, and wanted to find the porn images then looking for certain pinks in those images would be a good first pass I feel [you'd probably get lots of false-positives for mouth pictures]. Even those with brown and black skin can flush pink when aroused too, that's got to feed in to the results. [Do men have pigmented glans penis? Not something I've ever really needed to know. [2]]
I also think there was a clearer bias towards mushroom shaped objects than O'Keef work. It made me wonder if nude men are considered more pornographic than men.
> It made me wonder if nude men are considered more pornographic than men.
In some places, definitely yes. The laws and regulations imposed by different countries, states, media companies, and other bodies, and how they are sometimes "over interpreted" when being careful not to trip over the rules, do vary but there is some bias towards not showing the penis at least.
In some contexts genitalia is banned but breasts and buttocks are fine leaving more room for a sexual-ish image of woman to be acceptably published. In other contexts genitalia can be show as long as it isn't in a obviously aroused state, but other shows of arousal (blushing, other body language, suggestive word choice, ...) are fine, which will likely bias against male genitalia being publishable unless close up (and in contexts where the question is even raised a close-up shot is less likely).
(Massive generalism here, but...) there is also a general opinion that the use of the female form can be defended as artistic more than the male - though I couldn't tell you if this is a symptom of other cultural biases or a cause of some of them.
Attitudes to sexual preference are going to factor in too: those anti-homosexual opinions/feelings (conscious or otherwise) are more likely to react strongly to images of male sexuality than female (the old joke "I support homosexuality as long as both the chicks are hot" has some basis in reality). This is more common in men in my experience, especially man of certain age ranges and backgrounds which are currently over represented in parts of the "traditional" media industry and other seats of influence, making the bias more visible.
All that and a number of other interrelated factors I don't have time to type out make it less common to see a full-body or otherwise genitalia-containing shot of a naked male than one of a naked female - so when one is shown it is more likely to illicit a stronger reaction.
(I avoided using examples of differences in the consumption of pornographic output between different sexualities, as there is a lot of reporting bias in studies in that area both in terms of what questions the studies ask, how truthful the subjects answer, and what gets selected for publication)
We're witnessing the beginning of an entirely new form of pornography. I can easily imaging a XYZ Porn website adding an "Artificial" or "Neural Dream" porn section.
Advertisement is not only marketing, it's also art. Even if ad agencies will fail to convince some porn site or condom producer to use such ad to generate news, they still can create social ad and submit it to advertising festivals.
Has anyone ever thought about using all of reddits porn subs for machine learning? There must be 10s (or even 100s) of thousand of images (kind of) neatly organized by gender, boob size, ass size, skin color, age, ...
Unusable on mobile. In portrait, the sidebar covers everything; in landscape, it still covers half the viewport, and touch panning works but resets the position of the graph to what I assume is center or origin on every drag.
Hate to seem harsh, but I felt it worth mentioning, since it's why I'm unable to give any more substantive feedback on the project.
I thought of doing this but my bottleneck is scraping the images since I don't have terrabtytes of bandwidth and imgur would likely rate limit me. But given the data set my plan is/was to extract tags by mapping images to the sub Reddit they're posted in then categorize based on that
Contabo are 100Mbit but unmetered, ridiculously cheap.
Reddit's main issue is that you can only do one call (via OAuth) per second. I recommend using the new(ish) "thing" call where you can get up to 100 things at once, or alternatively rockets.cc, which occasionally falls apart but is pretty good
Some of these images and those from similar projects could be in an art gallery. They are art; provoking original, emotional, responses.
Most people hear about self-driving cars, but not about the fact that machines have already begun to emulate human creativity in the most intimate way. For a while, this secret assault on our uniqueness will stay among us.
Actually, no. Nothing produced in the 90's is the same as what's been done in the last few years. But please cite your best work and we'll have a look.
Regarding your dick joke, it's not really relevant. This is not interesting because it is pornographic.
The work of 90s as I know it (sorry, no references, I was quite young then, do not care to loop up at the moment), was taking some corpus (and not an English one) and letting a generative algorithm run on it. This was not a research but art, literature, and as such, actually could have been very regional.
Of course the current state of art is on the different level but in basic principles not very different and as such not very surprising as an form of art.
PS. it does not imply that no interesting results may grow out of this.
I disagree, because the machine is still using human generated input for creating these images. Not to take away from what's been created here because it's interesting to look at, but an image filter could be considered an attack on our uniqueness because it takes an existing human art work and can potentially create something more interesting, but most people wouldn't consider it an assault.
I get this is a "neural net", which makes people think these paintings are created by the terminator, but these images still have very real human inputs which is why we can relate to them.
What human input? I mean the pictures were taken by humans. But they weren't drawn by humans, they weren't meant to be art, and no one intended the output of the network to look the way it does. There is very little human input here.
If I pick a shell I find beautiful from the shore, did the beach create the shell, or did I?
Computer algorithms produce a lot of trash. Just because the human didn't wield a brush, as long as we're seeing filtered and tuned results, a human had a hand in creating these.
> already begun to emulate human creativity in the most intimate way
I'd argue that the creative entity here is @gabeeegoooh. The machine didn't make the (provocative) decision to synthesize NSFW images - that artistic stroke was painted by the fingers and mind that coded up the adversarial neural net.
Definitely. If creativity were merely the creation of interesting images, we'd have to call nature far more creative than any human artist. The Grand Canyon is beautiful, but we don't put up a plaque giving the Colorado River credit for its thoughtful use of form and color.
Calling the neural network creative is like crediting Van Gogh's brushes for Van Gogh's brushwork. It's a possible use for the word, but it's very different use than the one normally meant.
Van Gogh's brushes were simple tools used to render a direct expression of his intent.
These networks are more akin to a child. You teach her to paint, give her input and feedback. The result may be something emotionally moving that you could have not even conceived of.
Your opinion and mine are both surely subjective. However, it seems it will only become more difficult to split the hairs required to argue that machine learning creativity is fundamentally different from our own.
Brushes are not pure transmitters of intent the way that, say, Photoshop is. Brushes (and paints and most artistic tools) have an artistic character that makes its own contribution to the artwork. I also think you ignore the interplay between medium and artist, the way intent evolves both during the course of an artist's careeer and during the production of a single work.
I don't think I'm hair-splitting here. Creativity is something conscious entities do. Once we have conscious machines, they could well be creative. But until then, the creativity is the artists, even if they are using generative systems to create art.
And that's nothing new. Every landscape painter and photographer is using a generative system, nature, to find interesting things worth turning into art. Giving the neural networks credit is akin to crediting the haystacks rather than Monet.
More explicitly generative art, where humans set up systems to produce works, goes back hundreds of years. That interesting patterns can emerge out of randomness plus systems is obvious to anybody who has played Yahtzee. That we use more dice and more complicated systems does not change where authorship lies. Bigger systems may produce more novel outputs, but novelty and creativity aren't the same thing.
So, in what way would I be wrong if I called you a generative system?
I don't see any connection to consciousness whatsoever.
Imagine in the year 1900 a black box existed with a slot to input paper on one side and output paper on the other. If all physics papers available at the time were fed into it, and out popped the special theory of relativity, how is that not creativity?
You might not see any connection, but it is nonetheless how people use the word. Human language is mainly about humans and their relation to the world.
If your black box contains Einstein, then yes, it's a creative act. If it contains an artificial consciousness, then yes, it's a creative act. But if it contains infinite monkeys typing randomly into LaTeX producing infinite physics papers, then no, that's not creativity, just the generation of novelty.
I could call a red rock-face "angry", and I could call a mountain lake "tranquil". But that's projecting emotional states onto the external world. Calling dice creative is projecting a cognitive state onto the world. Sure, it works fine as metaphor. But it's just analogy, not homology.
I've enjoyed your comments, they've helped me clarify my thoughts.
It seems we disagree on what creativity is. I strongly believe humans/consciousness are not essential elements in it. For starters:
1). No dictionary seems to link creativity and humanity
2). Einstein's insights are considered some of the greatest examples of original thinking ever, and would not be diminished, or less beneficial to society, if conjured by a black box.
3). By your definition, a machine could out do a human by a thousand fold in every possible task and still not be creative. I don't think there's any precedent or foundation that would make that a tenable position.
Glad to hear it. And I agree that we disagree on what creativity is. As to your points:
Dictionaries are written by humans. The human is always implied. One way to tell is by looking at synonyms: inventiveness, imagination, innovation, innovativeness, originality, individuality. All very huuman words.
If the theory of relativity came from a black box, then sure, it would still be a good theory, and we'd still benefit from it. That does not make the black box creative.
Conscious machines could indeed be creative. We are, after all, conscious machines. But creativity involves a shift in understanding, and nonconscious machines don't understand.
And the curation of the images, the selection of which to feature, is also a very important aspect. He didn't include some images the system did or could generate. While he personally may not have, it is absolutely possible that such a decision was made in order to communicate some idea. If you take a random object, and place it in a museum, that can be art simply by virtue of the fact that you are attempting to communicate something. Art is, in my opinion at least, an attempt to communicate (typically supra-lingual ideas, concepts, feelings, etc).
They have automated the surrealist movement. Which goes pretty much directly against the philosophy underlying the surrealist movement. Which the actual people involved with it would probably approve of, as they mostly all moved on from it anyway.
I am always blown away by how eerily similar these generated NN images are to the visuals experienced under psychedelic drugs. Moreso than any artist's depiction (and there have been plenty of those)... they just have the same "feel". Which of course leads one to the inescapable idea that there is a fundamental relationship here.
I've hypothesised something like this. Or rather dreams could be generative based on random input (or random 'memory key frames') rather than real input. This assumes that mostly what we 'see' when awake is actually generated by the brain based on incomplete and noisy sampling of the real world.
I think that's pretty much the standard theory nowadays.
If I understand my pop-science correctly, our subjective visual field is actually made of images synthesised from objects we have recognised.
When we are awake, this mostly matches the real world because we select those objects to match data coming from the eyes. But when we dream or hallucinate, the synthesis circuits fire based on other inputs -- such as noise.
OK - does anyone know, how close are we to these trained neural nets passing the turing test for human creativity? Because I feel like we're going to pass it in my lifetime.
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[ 3.1 ms ] story [ 241 ms ] threadhttps://gitlab.com/open_nsfw/open_nsfw.gitlab.io/tree/master...
If you were on safari before, it should be working now.
Just confirmed the fixes are live.
If we get to where we can simulate human neural nets (and identify the "scary" neurons) then we could perform gradient descent against those. That's an interesting concept. I don't know if that's been visited in SF, but it has potential. Imagine a set of not-so-random squiggles that causes uncontrollable fear to its beholder.
So when I was back in high school I was playing around with one of the Kai art programs (I forget which one actually) that let you generate different patterns. I couldn't explain why but the patterns that were kind of regular-ish and curvy/abstract (anything that looked like cells under a microscope or those with a honeycomb-like structure) made me deeply, anxiously, almost panic-attack level uncomfortable. This startled me when it happened the first time. There was nothing at all I could logically connect it to.
The best way I can describe it is that I get that deep stomach-fluttery feeling that comes with being really nervous and apprehensive, but without any of the emotional content of anxiety at all.
I forgot about that experience for a long time, until the first Google 'Deep Dream' images were released. Turns out that the Internet has given this a name - trypophobia (fear of holes). The regular, not-quite-identifiable quality to the images is what seems to do it to me.
Even now, my stomach is fluttering like I'm about to go on a scary roller coaster. Again though, this comes with no emotional panic. I'm not upset by it, it isn't self-reinforcing like anxiety is. It's just a really odd feeling. A very strong 'get away from this' feeling.
I've read the hypothesis that this comes from an instinct to avoid danger, such as beehives and poisonous creatures and that makes a lot of sense (not totally sure from memory though so I might be getting it wrong; I need to find the study I'm thinking of).
So I don't doubt that at least for some people it's possible to synthesize images that provoke a strong physiological response that could make them flee.
Sort of related: Instead of visually producing fear, you can also do it with sound.
Research "Binaural beats: Gates of Hades" I literally threw my headphones off at like 25secs.
I know you could literally mix trypophobia images and Gates of Hades to produce a waterboarding like response.
(now I really wish someone did a Beksiński + photos mixer... there's ~240 samples just on that site)
Google "giger nsfw" if you want to see his more sexual creations.
You'll have to translate from polish, but they do send internationally. The email contract is at art@bosz.com.pl
Fun fact: with prints, without seeing the original pictures in his home town you miss out on his notes of what substances did he ingest while painting. (sometimes attached or on the frames if I remember correctly)
It's mesmerizing to see this NSFW detection applied in reverse, and it's even more interesting to observe your mind react to the generated images. You can see the sort-of-mons pubis patterns, the maybe-pubic hair, the perhaps-breasts and the suspiciously phallic appendages, complete with realistic colors.
Interestingly, all exposed skin suggests that the training dataset for the NSFW detection was skewed towards caucasians, given how the synthesized images are near-completely devoid of skin tones other than light pink. Perhaps this is a good visual indication of unintentional 'bias' in datasets?
We already have a huge amount of homemade porn by people all across the world, but the dataset is not very well labeled compared to professional mainstream porn and that will impact the research.
In other posts I've seen, generative networks produced biases unrelated to what people consider NSFW such as brighter lip color, so I think restricting features related to anything above the neck or below the knees from impacting the CNNs would be helpful.
It's the easiest cheapest way nowadays to sound insightful.
Edit: I think I came across harsher than I meant to. All I meant was that we could have simply said I wonder how it deals with different skin tones. Instead, we get into race and biases etc.
Interesting that regarding universities being sued for lack of cc in their free online content everyone was up in arms, but mention the word race and everyone goes on high alert.
Really, my curiosity stems from being new to how neural networks work -- naively, I've grown accustomed to processes where the outputs reflect the input, and at first blush to me, supposing a varied dataset, this didn't appear to be the case. Those who replied to me provided persuasive arguments as to why the hues of the synthesized images may not necessarily imply that the training dataset wasn't that varied after all.
It's a valid point you made, it was just the wording that pushed a button.
Skin tone would indeed have been a more appropriate term to use.
[edit, removed a parenthetical as it undermined my point]
Some bias exists probably in every dataset.
Now the interesting things is that from what culture roam this dataset was acquired from considering that operating markets of Yahoo are US, Europe, Japan?
Does it resemble demographics of these markets? Or does it represent the desires of these markets?
More importantly is there are a good validation set of subtle examples of something being NSFW and SFW? Especially considering that the subject is mostly defined as I do not know to how to define it I definitely know it when I see it.
when running the experiments, i noticed the neural net responds much more strongly to contrast than color. this is consistent with previous work where the the first layers of a conv net isolate colors in a few filters. i wouldn't read too much into this
And since Yahoo needs to detect porn of all races and there's plenty of black porn out there, it would be odd if their porn detector had such a huge gaping hole in it.
phrasing!
I couldn't resist.
Hair color, yes, but facial feature variability? I think your perception of more variability in European faces than Chinese ones says more about where/how you grew up than about the actual variability. To someone who grew up in an Asian monoculture, without exposure to media with European faces, all Europeans would look alike too.
Context: I grew up in southern india and spent most of my early years there, but travelled out to the northern India in the mid twenties. I can now say, I can see facial feature variations in the NE India folks(these folks have facial similarity with chinese) I see around now (I currently live in the south)
I'm instead sure about this because of a funny incident that happened to my mother just a few years ago. She was standing near a pizzeria when a chinese waitress stepped out and said (translating from italian, sorry if I make some mistakes):
waitress: "Take away?" my mother: "What?" waitress: "Take away?" my mother:"No, I haven't ordered anything" waitress: "You Italians! You look all alike!"
EDIT: formatting
So nah, it's not funny.
As I've explained in https://news.ycombinator.com/item?id=12759089, different races have different sets of facial features which are used for facial recognition (because they vary more). Now, when programming the NN, what if you only told it to look for the set of facial features you thought was important? It's very easy to let unconscious biases seep into your code.
I thought that «race» is a social construct not a scientific one and thus can't be relied on as a deciding factor in a scientific experiment or endeavor like face detection.
"The cross-race effect (sometimes called cross-race bias, other-race bias or own-race bias) refers to the tendency to more easily recognize members of one's own race."
This premise is not well grounded in facts as evidence can show that some people esp. racially unaware, uneducated or desensitized don't fall into this category. To support their claim, they cite a US-only study which can't be sufficient to extrapolate for all humanity as a universal fact since we all know that US society is divided along racial line and it's deeply ingrained into people's minds from childhood.
It's like their caste system and with a highly cultural not scientific element to it.
Color me skeptic about this theory.
Traffic laws are also social constructs. Yet we can build machines to follow them.
No. Some cultures on Earth define "race" with various, conflicting standards. Some don't even have that concept.
The Roman empire spanned swathes of North Africa and had major centres there and traded with subsaharan Africa. And traded with the 'orient' all the way to China.
Their writings don't make racial classifications. They don't even remark much on skin colour or other features.
Visual features were known, but not considered that significant. And later in the empire people from all over the world became Romans via citizenship and what we now call "race" never factored into it.
Exactly.
To people who are used to them. i.e. to you.
I'm Irish, and can tell many Irish accents apart. But I've had people from England not being able to hear the difference between Irish accents, thinking they all just sounded Irish.
I've literally been in a group of Europeans in Africa, and Africans mixing up several of the women there, because they were all relatively tall, slim build, with longish straight brown hair.
[1]: https://en.wikipedia.org/wiki/Out-group_homogeneity
This is false. Each individual has a preferred set of facial features that are used to distinguish faces, and this set is usually dependent on our race and/or where we grow up. People of some races look alike to us because they have lesser variability in this set, but may have more variability in a different set of facial features that our mind is not used to looking for.
A face recognition NN would be biased this way only if the training set was biased, or if it was only taught one set of features.
There's a good explanation of this at http://lawcomic.net/guide/?p=3285
You might be surprised to learn that to Chinese people, westerners all look more or less the same. To Africans, white people look more or less the same. Our biological hardware is great at distinguishing minute differences in things (especially people) we are very familiar with, while we automatically start generalizing about things we are less familiar with.
For comparison: a metal fan may be able to distinguish a dozen distinctly different styles of Norwegian Black Metal, while to outsiders it's all loud white noise made by people dressed like undead clowns.
Yes, I would definitely be surprised if Chinese people thought a pale-skinned Irish woman with shocking red hair looked more or less the same as an olive skinned mediterranean brunette.
The fact of the matter is, the greatly reduced range of hair and skin color in the Chinese is a legitimate reason to think they look more "the same" than a European/Westerner. There is undisputably greater diversity in appearance in Europe than China.
North to south I think it's pretty clear that skin colour goes from light to much darker than Europe.
Europe ranges from 1-14
"Western" ranges from 1-23
China ranges from 12-17
Am I interpreting the image incorrectly? Doesn't it confirm my assertion that China has a smaller range of skin tone?
Edit: The definition of "Western" appears to be very vague, but for reference I referenced at the rough vague shape of the United States to determine the 1-23 figure.
But my point is only to say that your statement of "greatly reduced range of .. skin color" is a rather exaggerated statement. (For hair color I suppose you might be right ;)
Hard to say due to the lack of precision in the map in the lighter range, but if you think about how incredibly large China is, it stands to reason that your statement might be missing the mark a bit. Especially if you consider other Asian countries. (Which maybe you should, if comparing with "Europe" or "North America"..)
Someone else posted this: http://lawcomic.net/guide/?p=3285
Strong pink is probably the most common colour across all people for the most intimate parts of the genitals as AFAIK the inner folds and spread appearance of all types of vulva are pink. All tongues and palms are pink too [AFAIK], they probably feature highly in porn compared to in other images. If you were then looking at pictures of black women, say, and wanted to find the porn images then looking for certain pinks in those images would be a good first pass I feel [you'd probably get lots of false-positives for mouth pictures]. Even those with brown and black skin can flush pink when aroused too, that's got to feed in to the results. [Do men have pigmented glans penis? Not something I've ever really needed to know. [2]]
FWIW https://open_nsfw.gitlab.io/nsfw/prob_0001_1000_10.0_0.04__1... doesn't look especially "caucasian" (ie white European) to me. There seems to be a good mix of pretty coffee-y colours to me that I'd associate with Asia.
>Perhaps this is a good visual indication of unintentional 'bias' in datasets? //
So, maybe it's a colour-of-genitals bias rather than a dataset bias?
[1] http://www.iflscience.com/health-and-medicine/why-are-your-n...
[2] http://www.interestingarticles.com/mens-health-issues/penis-...
That's not true for palms.
In some places, definitely yes. The laws and regulations imposed by different countries, states, media companies, and other bodies, and how they are sometimes "over interpreted" when being careful not to trip over the rules, do vary but there is some bias towards not showing the penis at least.
In some contexts genitalia is banned but breasts and buttocks are fine leaving more room for a sexual-ish image of woman to be acceptably published. In other contexts genitalia can be show as long as it isn't in a obviously aroused state, but other shows of arousal (blushing, other body language, suggestive word choice, ...) are fine, which will likely bias against male genitalia being publishable unless close up (and in contexts where the question is even raised a close-up shot is less likely).
(Massive generalism here, but...) there is also a general opinion that the use of the female form can be defended as artistic more than the male - though I couldn't tell you if this is a symptom of other cultural biases or a cause of some of them.
Attitudes to sexual preference are going to factor in too: those anti-homosexual opinions/feelings (conscious or otherwise) are more likely to react strongly to images of male sexuality than female (the old joke "I support homosexuality as long as both the chicks are hot" has some basis in reality). This is more common in men in my experience, especially man of certain age ranges and backgrounds which are currently over represented in parts of the "traditional" media industry and other seats of influence, making the bias more visible.
All that and a number of other interrelated factors I don't have time to type out make it less common to see a full-body or otherwise genitalia-containing shot of a naked male than one of a naked female - so when one is shown it is more likely to illicit a stronger reaction.
(I avoided using examples of differences in the consumption of pornographic output between different sexualities, as there is a lot of reporting bias in studies in that area both in terms of what questions the studies ask, how truthful the subjects answer, and what gets selected for publication)
Eg you make an ad that looks innocent, but that would fool your brain into thinking it's sexual if you just scan the page containing it?
Hate to seem harsh, but I felt it worth mentioning, since it's why I'm unable to give any more substantive feedback on the project.
Reddit's main issue is that you can only do one call (via OAuth) per second. I recommend using the new(ish) "thing" call where you can get up to 100 things at once, or alternatively rockets.cc, which occasionally falls apart but is pretty good
Whatever Piaget stage prog rock is, AI has reached it.
Most people hear about self-driving cars, but not about the fact that machines have already begun to emulate human creativity in the most intimate way. For a while, this secret assault on our uniqueness will stay among us.
[0] https://en.wikipedia.org/wiki/Penis_Landscape
With a bunch of Giger images plus a bunch of porn as input the output would probably be fairly indistinguishable from Giger originals.
Now for a newer generation playing with a real ding is perhaps a little more intriguing.
Regarding your dick joke, it's not really relevant. This is not interesting because it is pornographic.
Of course the current state of art is on the different level but in basic principles not very different and as such not very surprising as an form of art.
PS. it does not imply that no interesting results may grow out of this.
I get this is a "neural net", which makes people think these paintings are created by the terminator, but these images still have very real human inputs which is why we can relate to them.
Computer algorithms produce a lot of trash. Just because the human didn't wield a brush, as long as we're seeing filtered and tuned results, a human had a hand in creating these.
I'd argue that the creative entity here is @gabeeegoooh. The machine didn't make the (provocative) decision to synthesize NSFW images - that artistic stroke was painted by the fingers and mind that coded up the adversarial neural net.
Calling the neural network creative is like crediting Van Gogh's brushes for Van Gogh's brushwork. It's a possible use for the word, but it's very different use than the one normally meant.
These networks are more akin to a child. You teach her to paint, give her input and feedback. The result may be something emotionally moving that you could have not even conceived of.
Your opinion and mine are both surely subjective. However, it seems it will only become more difficult to split the hairs required to argue that machine learning creativity is fundamentally different from our own.
I don't think I'm hair-splitting here. Creativity is something conscious entities do. Once we have conscious machines, they could well be creative. But until then, the creativity is the artists, even if they are using generative systems to create art.
And that's nothing new. Every landscape painter and photographer is using a generative system, nature, to find interesting things worth turning into art. Giving the neural networks credit is akin to crediting the haystacks rather than Monet.
More explicitly generative art, where humans set up systems to produce works, goes back hundreds of years. That interesting patterns can emerge out of randomness plus systems is obvious to anybody who has played Yahtzee. That we use more dice and more complicated systems does not change where authorship lies. Bigger systems may produce more novel outputs, but novelty and creativity aren't the same thing.
I don't see any connection to consciousness whatsoever.
Imagine in the year 1900 a black box existed with a slot to input paper on one side and output paper on the other. If all physics papers available at the time were fed into it, and out popped the special theory of relativity, how is that not creativity?
If your black box contains Einstein, then yes, it's a creative act. If it contains an artificial consciousness, then yes, it's a creative act. But if it contains infinite monkeys typing randomly into LaTeX producing infinite physics papers, then no, that's not creativity, just the generation of novelty.
I could call a red rock-face "angry", and I could call a mountain lake "tranquil". But that's projecting emotional states onto the external world. Calling dice creative is projecting a cognitive state onto the world. Sure, it works fine as metaphor. But it's just analogy, not homology.
It seems we disagree on what creativity is. I strongly believe humans/consciousness are not essential elements in it. For starters:
1). No dictionary seems to link creativity and humanity
2). Einstein's insights are considered some of the greatest examples of original thinking ever, and would not be diminished, or less beneficial to society, if conjured by a black box.
3). By your definition, a machine could out do a human by a thousand fold in every possible task and still not be creative. I don't think there's any precedent or foundation that would make that a tenable position.
Dictionaries are written by humans. The human is always implied. One way to tell is by looking at synonyms: inventiveness, imagination, innovation, innovativeness, originality, individuality. All very huuman words.
If the theory of relativity came from a black box, then sure, it would still be a good theory, and we'd still benefit from it. That does not make the black box creative.
Conscious machines could indeed be creative. We are, after all, conscious machines. But creativity involves a shift in understanding, and nonconscious machines don't understand.
https://www.youtube.com/watch?v=oYp5XuGYqqY
fascinating stuff
If I understand my pop-science correctly, our subjective visual field is actually made of images synthesised from objects we have recognised.
When we are awake, this mostly matches the real world because we select those objects to match data coming from the eyes. But when we dream or hallucinate, the synthesis circuits fire based on other inputs -- such as noise.
Especially considering that the subject is mostly defined as I do not know to how to define it but I definitely know it when I see it.