<story><title>Image Synthesis from Yahoo&apos;s open_nsfw</title><url>https://open_nsfw.gitlab.io/</url></story><parent_chain><item><author>aab0</author><text>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&amp;#x27;re doing gradient ascent on confidence of classification, not simply trying to find a plausible input, but the &lt;i&gt;maximal&lt;/i&gt; input. There&amp;#x27;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.)&lt;p&gt;And since Yahoo needs to detect porn of all races and there&amp;#x27;s plenty of black porn out there, it would be odd if their porn detector had such a huge gaping hole in it.</text></item><item><author>niftich</author><text>This is absolutely fascinating.&lt;p&gt;It&amp;#x27;s mesmerizing to see this NSFW detection applied in reverse, and it&amp;#x27;s even more interesting to observe your mind react to the generated images. You can see the sort-of-&lt;i&gt;mons pubis&lt;/i&gt; patterns, the maybe-pubic hair, the perhaps-breasts and the suspiciously phallic appendages, complete with realistic colors.&lt;p&gt;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 &amp;#x27;bias&amp;#x27; in datasets?</text></item></parent_chain><comment><author>rmc</author><text>&amp;gt; &lt;i&gt;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&lt;/i&gt;&lt;p&gt;To people who are used to them. i.e. to you.&lt;p&gt;I&amp;#x27;m Irish, and can tell many Irish accents apart. But I&amp;#x27;ve had people from England not being able to hear the difference between Irish accents, thinking they all just sounded Irish.&lt;p&gt;I&amp;#x27;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.</text></comment>
<story><title>Image Synthesis from Yahoo&apos;s open_nsfw</title><url>https://open_nsfw.gitlab.io/</url></story><parent_chain><item><author>aab0</author><text>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&amp;#x27;re doing gradient ascent on confidence of classification, not simply trying to find a plausible input, but the &lt;i&gt;maximal&lt;/i&gt; input. There&amp;#x27;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.)&lt;p&gt;And since Yahoo needs to detect porn of all races and there&amp;#x27;s plenty of black porn out there, it would be odd if their porn detector had such a huge gaping hole in it.</text></item><item><author>niftich</author><text>This is absolutely fascinating.&lt;p&gt;It&amp;#x27;s mesmerizing to see this NSFW detection applied in reverse, and it&amp;#x27;s even more interesting to observe your mind react to the generated images. You can see the sort-of-&lt;i&gt;mons pubis&lt;/i&gt; patterns, the maybe-pubic hair, the perhaps-breasts and the suspiciously phallic appendages, complete with realistic colors.&lt;p&gt;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 &amp;#x27;bias&amp;#x27; in datasets?</text></item></parent_chain><comment><author>HSO</author><text>&amp;gt; &lt;i&gt;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&lt;/i&gt;&lt;p&gt;Hair color, yes, but facial feature variability? I think your perception of more variability in European faces than Chinese ones says more about where&amp;#x2F;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.</text></comment>