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Fascinating philosophical question: if an AI observes a stream of bytes but doesn't decode a camera's output into an image -- and yet can raise an alarm if the
by fernly 3y ago
Fascinating philosophical question: if an AI observes a stream of bytes but doesn't decode a camera's output into an image -- and yet can raise an alarm if the camera is aimed at a certain class of subject -- does the AI "see" the camera image?
They should have named the system "Blindsight"[1].
Apple has a serious corporate concern about proposed legal requirements to detect and report child porno[2], while other legal requirements try to protect user privacy. This appears to be an attempt to say, "We can detect your CP image storage without ever actually looking at your stored images."
[1] https://en.wikipedia.org/wiki/Blindsight https://en.wikipedia.org/wiki/Blindsight
[2] https://en.wikipedia.org/wiki/Regulation_to_Prevent_and_Combat_Child_Sexual_Abuse https://en.wikipedia.org/wiki/Regulation_to_Prevent_and_Comb...
- deleted 3y ago[deleted]
- troops_h8r 3y agoYou might like the scifi novel of the same name by Peter Watts
- escapecharacter 3y agoThe real conclusion from your question is that the AI never “sees” the image even if it did decode it.
- messe 3y agoAnd how do you draw that conclusion?
- nextworddev 3y agoWhat does it mean to “see”? Are we assuming that eyes are involved?
- holoduke 3y agoThe AI doesnt decode the image with a human written decoder. But it decodes with learned model parameters. So it still decodes.
- jerpint 3y agoModels never « see » anything to begin with, it’s all matrices. And since we ditched convents, locality doesn’t even matter anymore (almost). RGB is just convenient for humans, nothing says it’s optimal for deep learning
- IIAOPSW 3y agoYeah, real humans see with a fourier transform in a highly optimized basis for projecting 3d down to the 2d retina. Not cold soulless math like those machines! http://www.math.utah.edu/~bresslof/publications/01-3.pdf http://www.math.utah.edu/~bresslof/publications/01-3.pdf
- goldenkey 3y agoMuch hardware and software for codecs use wave basis as well. https://en.wikipedia.org/wiki/Discrete_cosine_transform https://en.wikipedia.org/wiki/Discrete_cosine_transform
- astrange 3y agoHumans see more than 8-bit RGB. Humans can see light polarization and stereo disparity, but more importantly we can interact with things we look at. XYZ is the "most optimal" 3-channel colorspace but it's a simple transformation from RGB, so it doesn't matter - the model can learn it if it wants to.
- SilasX 3y agoThat sounds like a variant of the Chinese Room problem: if a non-Chinese speaker follows a rule book to text-chat in Chinese with someone on the other side, does s/he, in actuality, “speak Chinese”? https://en.m.wikipedia.org/wiki/Chinese_room https://en.m.wikipedia.org/wiki/Chinese_room
- pault 3y agoNo, the book does.
- unlikelymordant 3y agoOr perhaps the book + human system does
- winternewt 3y agoOr perhaps it's the universe speaking Chinese with itself. The chain of cause and effect stretches 13.8 billion light years.
- readyplayeremma 3y agoExcept the person in the room also had to write the book by looking at examples of Chinese.
- malf 3y agoObligatory four-letter comic: https://www.smbc-comics.com/comic/the-chinese-room https://www.smbc-comics.com/comic/the-chinese-room
- quickthrower2 3y agoIt is worth doing some ML courses to understand what is going on. I am beginning this journey, and it takes a lot of the magic out of it. Really what is happening is just mathematical operations: a lot of matrix multiplications, some simple non-linear functions (because linear algebra alone cannot represent all logic), some statistical stuff to stop the numbers getting out of control. Importantly there are millions or billions of "magic numbers" that get updated as the model learns called parameters. Whether you train the network on representation A of the image, or representation B of the image, doesn't change much philosophically. It is just a function f(x) applied before the function g(x, parameters), so you get g(f(X), parameters). Now you could argue, well it might mean "something". After all you can reduce our brains to being a big mathematical functions. Possibly. But I think in this case it is too simple. The AI is just looking at a slightly different representation. Similar to changing VS code from/to dark mode for humans, or something like that. And the modellers might be changing representations all the time anyway as they tinker with things.
- raverbashing 3y agoYeah but this is an ML 101 view of the thing, so let me put it this way The topology of the (real) input data is part of the dimensionality reduction needed for the identification to work, especially at a given number of parameters Understanding how the data is connected in the input (there are image lines and they form a "shape") helps a lot and CNNs used this to their advantage Maybe a very powerful RNN could deduce this by itself, but it is wasted processing. GPT also uses the input topology to its favour when it uses tokens, process text sequentially, etc
- quickthrower2 3y agoIf this is the case, and I believe you, then this implies: "bytes are NOT all you need". You need a good representation of your image for the network to work well. It might so happen that one of the popular formats, maybe JPEG does a good job. But a dedicated ML person could do better most likely. This is probably what you would classically call "feature engineering"? And this is all hyperparameter search stuff in a way.
- 3y ago
- fernly 3y agoYeah, yeah, we know it is all matrices and numbers. But the Apple group seems to be asserting that there is a difference, > We also demonstrate ByteFormer's ability to perform inference with a hypothetical privacy-preserving camera which avoids forming full images by consistently masking 90% of pixel channels, while still achieving 71.35% accuracy on ImageNet. So the way this algorithm smooshes the matrices is "privacy-preserving" because it doesn't actually take in all the bytes. Just some of them. So it is not an invasion of your privacy, if your phone checks all your stored photos for child pornography, because it never actually _looks_ at the images. It just _peeks_ at a bit of them.
- XorNot 3y agoWhich is a hardcore effort to pretend the issue was something to do with looking at images, and not indiscriminate motivated surveillance. No one cares about software touching their bytes: they should care a lot about software which is built with the null hypothesis of "this person has child pornography, notify the authorities".
- vasco 3y agoIf I ask to see just a bit of your private documents - I can choose the corner of the document, let's say, the top left - and I can inferr with 70% accuracy who you're getting services from, did I respect your privacy? This seems a bit like smoke and mirrors. Either scan the image or not! Inference from partial images is super cool research for example to deal with corrupted image files, but not for privacy imo.
- orbital-decay 3y agoDo you "see" the image projected onto your eye's retina, if you just observe a massively parallel stream of electric stimuli going through your optic nerve, but never decode it into a cluster of pixels and the internal reconstruction of the scene in your brain is nothing like that? (wait until you know that there are single-pixel compressive sensing cameras that bypass the wasteful image reconstruction phase, directly mapping the raw signal to the output representation...)
- nico 3y agoYou might want to read about Daniel Kish and maybe listen to the Batman story on NPR They raise the philosophical question of what does it mean to see According to brain scan of Daniel Kish, it seems that despite being blind, he can actually see through echolocation Reference: https://www.npr.org/2015/11/20/455906507/how-can-you-see-without-seeing https://www.npr.org/2015/11/20/455906507/how-can-you-see-wit...
- eloisius 3y agoWouldn’t the transformer just be learning a jpeg decoder at some point?
- ravenstine 3y agoHow does the human brain "see" the signal impulses that pass through the optic nerve?