Court Bans Use of 'AI-Enhanced' Video Evidence Because That's Not How AI Works
Court Bans Use of 'AI-Enhanced' Video Evidence Because That's Not How AI Works
This AI hype cycle has dramatically distorted society's views of what's possible with image upscalers.
A judge in Washington state has blocked video evidence that’s been “AI-enhanced” from being submitted in a triple murder trial. And that’s a good thing, given the fact that too many people seem to think applying an AI filter can give them access to secret visual data.
"Your honor, the evidence shows quite clearly that the defendent was holding a weapon with his third arm."
RIP Charlie Robinson
If you ever encountered an AI hallucinating stuff that just does not exist at all, you know how bad the idea of AI enhanced evidence actually is.
Everyone uses the word "hallucinate" when describing visual AI because it's normie-friendly and cool sounding, but the results are a product of math. Very complex math, yes, but computers aren't taking drugs and randomly pooping out images because computers can't do anything truly random.
You know what else uses math? Basically every image modification algorithm, including resizing. I wonder how this judge would feel about viewing a 720p video on a 4k courtroom TV because "hallucination" takes place in that case too.
Has this argument ever worked on anyone who has ever touched a digital camera? “Resizing video is just like running it through AI to invent details that didn’t exist in the original image”?
“It uses math” isn’t the complaint and I’m pretty sure you know that.
computers aren’t taking drugs and randomly pooping out images
Sure, no drugs involved, but they are running a statistically proven random number generator and using that (along with non-random data) to generate the image.
The result is this - ask for the same image, get two different images — similar, but clearly not the same person - sisters or cousins perhaps... but nowhere near usable as evidence in court:
computers can't do anything truly random.
Technically incorrect - computers can be supplied with sources of entropy, so while it's true that they will produce the same output given identical inputs, it is in practice quite possible to ensure that they do not receive identical inputs if you don't want them to.
Bud, hallucinate is a perfect term for the shit AI creates because it doesnt understand reality, regardless if math is creating that hallucination or not
No computer algorithm can accurately reconstruct data that was never there in the first place.
Ever.
This is an ironclad law, just like the speed of light and the acceleration of gravity. No new technology, no clever tricks, no buzzwords, no software will ever be able to do this.
Ever.
If the data was not there, anything created to fill it in is by its very nature not actually reality. This includes digital zoom, pixel interpolation, movement interpolation, and AI upscaling. It preemptively also includes any other future technology that aims to try the same thing, regardless of what it's called.
One little correction, digital zoom is not something that belongs on that list. It’s essentially just cropping the image. That said, “enhanced” digital zoom I agree should be on that list.
Suddenly thinking of someone using moon photos from their phone as evidence.
Digital zoom is just cropping and enlarging. You're not actually changing any of the data. There may be enhancement applied to the enlarged image afterwards but that's a separate process.
But the fact remains that digital zoom cannot create details that were invisible in the first place due to the distance from the camera to the subject. Modern implementations of digital zoom always use some manner of interpolation algorithm, even if it's just a simple linear blur from one pixel to the next.
The problem is not in how a digital zoom works, it's on how people think it works but doesn't. A lot of people (i.e. [l]users, ordinary non-technical people) still labor under the impression that digital zoom somehow makes the picture "closer" to the subject and can enlarge or reveal details that were not detectable in the original photo, which is a notion we need to excise from people's heads.
Hold up. Digital zoom is, in all the cases I'm currently aware of, just cropping the available data. That's not reconstruction, it's just losing data.
Otherwise, yep, I'm with you there.
See this follow up:
https://lemmy.world/comment/9061929
Digital zoom makes the image bigger but without adding any detail (because it can't). People somehow still think this will allow you to see small details that were not captured in the original image.
There's a specific type of digital zoom which captures multiple frames and takes advantage of motion between frames (plus inertial sensor movement data) to interpolate to get higher detail. This is rather limited because you need a lot of sharp successive frames just to get a solid 2-3x resolution with minimal extra noise.
If people don't get the second law of thermodynamics, explaining this to them is useless. EDIT: ... too.
It preemptively also includes any other future technology that aims to try the same thing
No it doesn't. For example you can, with compute power, for distortions introduced by camera lenses/sensors/etc and drastically increase image quality. For example this photo of pluto was taken from 7,800 miles away - click the link for a version of the image that hasn't been resized/compressed by lemmy:
The unprocessed image would look nothing at all like that. There's a lot more data in an image than you can see with the naked eye, and algorithms can extract/highlight the data. That's obviously not what a generative ai algorithm does, those should never be used, but there are other algorithms which are appropriate.
The reality is every modern photo is heavily processed - look at this example by a wedding photographer, even with a professional camera and excellent lighting the raw image on the left (where all the camera processing features are disabled) looks like garbage compared to exactly the same photo with software processing:
No computer algorithm can accurately reconstruct data that was never there in the first place.
What you are showing is (presumably) a modified visualisation of existing data. That is: given a photo which known lighting and lens distortion, we can use math to display the data (lighting, lens distortion, and input registered by the camera) in a plethora of different ways. You can invert all the colours if you like. It's still the same underlying data. Modifying how strongly certain hues are shown, or correcting for known distortion are just techniques to visualise the data in a clearer way.
"Generative AI" is essentially just non-predictive extrapolation based on some data set, which is a completely different ball game, as you're essentially making a blind guess at what could be there, based on an existing data set.
None of your examples are creating new legitimate data from the whole cloth. They're just making details that were already there visible to the naked eye. We're not talking about taking a giant image that's got too many pixels to fit on your display device in one go, and just focusing on a specific portion of it. That's not the same thing as attempting to interpolate missing image data. In that case the data was there to begin with, it just wasn't visible due to limitations of the display or the viewer's retinas.
The original grid of pixels is all of the meaningful data that will ever be extracted from any image (or video, for that matter).
Your wedding photographer's picture actually throws away color data in the interest of contrast and to make it more appealing to the viewer. When you fiddle with the color channels like that and see all those troughs in the histogram that make it look like a comb? Yeah, all those gaps and spikes are actually original color/contrast data that is being lost. There is less data in the touched up image than the original, technically, and if you are perverse and own a high bit depth display device (I do! I am typing this on a machine with a true 32-bit-per-pixel professional graphics workstation monitor.) you actually can state at it and see the entirety of the detail captured in the raw image before the touchups. A viewer might not think it looks great, but how it looks is irrelevant from the standpoint of data capture.
This is just smarter post processing, like better noise cancelation, error correction, interpolation, etc.
But ML tools extrapolate rather than interpolate which adds things that weren't there
offtopic: I like the picture on the left more. It feels more alive. Colder in color, but warmer in expression. Dunno how to say that. And I've been in a forest yesterday, so my perception is skewed.
In my first year of university, we had a fun project to make us get used to physics. One of the projects required filming someone throwing a ball upwards, and then using the footage to get the maximum height the ball reached, and doing some simple calculations to get the initial velocity of the ball (if I recall correctly).
One of the groups that chose that project was having a discussion on a problem they were facing: the ball was clearly moving upwards on one frame, but on the very next frame it was already moving downwards. You couldn't get the exact apex from any specific frame.
So one of the guys, bless his heart, gave a suggestion: "what if we played the (already filmed) video in slow motion... And then we filmed the video... And we put that one in slow motion as well? Maybe do that a couple of times?"
A friend of mine was in that group and he still makes fun of that moment, to this day, over 10 years later. We were studying applied physics.
That's wrong. With a degree of certainty, you will always be able to say that this data was likely there. And because existence is all about probabilities, you can expect specific interpolations to be an accurate reconstruction of the data. We do it all the time with resolution upscaling, for example. But of course, from a certain lack of information onward, the predictions become less and less reliable.
No computer algorithm can accurately reconstruct data that was never there in the first place.
Okay, but what if we've got a computer program that can just kinda insert red eyes, joints, and plums of chum smoke on all our suspects?
By your argument, nothing is ever real, so let's all jump on a chasm.
There's a grain of truth to that. Everything you see is filtered by the limitations of your eyes and the post-processing applied by your brain which you can't turn off. That's why you don't see the blind spot on your retinas where your optic nerve joins your eyeball, for instance.
You can argue what objective reality is from within the limitations of human observation in the philosophy department, which is down the hall and to your left. That's not what we're talking about, here.
From a computer science standpoint you can absolutely mathematically prove the amount of data that is captured in an image and, like I said, no matter how hard you try you cannot add any more data to it that can be actually guaranteed or proven to reflect reality by blowing it up, interpolating it, or attempting to fill in patterns you (or your computer) think are there. That's because you cannot prove, no matter how the question or its alleged solution are rephrased, that any details your algorithm adds are actually there in the real world except by taking a higher resolution/closer/better/wider spectrum image of the subject in question to compare. And at that point it's rendered moot anyway, because you just took a higher res/closer/better/wider/etc. picture that contains the required detail, and the original (and its interpolation) are unnecessary.
Well that's a bit close minded.
Perhaps at some point we will conquer quantum mechanics enough to be able to observe particles at every place and time they have ever and will ever exist. Do that with enough particles and you've got a de facto time machine, albeit a read-only one.
So many things we believe to be true today suggest this is not going to happen. The uncertainty principle, and the random nature of nuclear decay chief among them. The former prevents you gaining the kind of information you would need to do this, and the latter means that even if you could, it would not provide the kind of omniscience one might assume.
Complexity relates nonlinearly to the amount of moving parts.
We might be able to spend an ungodly amount of energy to do that for one particle for an hour of its existence.
Being able to build a computer (in a wide sense) that can emulate in short time (less than human life) processes consistent of more energy than was spent on its creation - it's something else.
I think we need to STOP calling it "Artificial Intelligence". IMHO that is a VERY misleading name. I do not consider guided pattern recognition to be intelligence.
A term created in order to vacuum up VC funding for spurious use cases.
Optical Character Recognition used to be firmly in the realm of AI until it became so common that even the post office uses it. Nowadays, OCR is so common that instead of being proper AI, it’s just another mundane application of a neural network. I guess, eventually Large Language Models will be outside there scope of AI.
What is the definition of intelligence? Does it require sentience? Can a data set be intelligently compiled into interesting results without human interaction? Yes the term AI is stretched a bit thin but I believe it has enough substance to qualify.
I do not consider guided pattern recognition to be intelligence.
That's a you problem, this debate happened 50 years ago and we decided Intelligence is the right word.
How is guided pattern recognition is different from imagination (and therefore intelligence) though?
Your comment is a good reason why these tools have no place in the courtroom: The things you describe as imagination.
They're image generation tools that will generate a new, unrelated image that happens to look similar to the source image. They don't reconstruct anything and they have no understanding of what the image contains. All they know is which color the pixels in the output might probably have given the pixels in the input.
It's no different from giving a description of a scene to an author, asking them to come up with any event that might have happened in such a location and then trying to use the resulting short story to convict someone.
My Concious Cognative Correlator is the real shit.
You, and humans in general, are also just sophisticated pattern recognition and matching machines. If neural networks are not intelligent, then you are not intelligent.
This may be the dumbest statement I have yet seen on this platform. That's like equating a virus with a human by saying both things replicate themselves so they must be similar.
You can say what you like but absolutely zero true and full understand of what human intelligence actually is or how it works.
"AI", or whatever you want to call it, is not at all similar.
I agree. It's restricted intelligence (RI), at best, and even that can be argued against.
How long until we got upscalers of various sorts built into tech that shouldn't have it? For bandwidth reduction, for storage compression, or cost savings. Can we trust what we capture with a digital camera, when companies replace a low quality image of the moon with a professionally taken picture, at capture time? Can sport replays be trusted when the ball is upscaled inside the judges' screens? Cheap security cams with "enhanced night vision" might get somebody jailed.
I love the AI tech. But its future worries me.
It will wild out for the foreseeable future until the masses stop falling for it in gimmicks then it will be reserved for the actual use cases where it's beneficial once the bullshit ai stops making money.
Lol, you think the masses will stop falling for it in gimmicks? Just look at the state of the world.
AI-based video codecs are on the way. This isn't necessarily a bad thing because it could be designed to be lossless or at least less lossy than modern codecs. But compression artifacts will likely be harder to identify as such. That's a good thing for film and TV, but a bad thing for, say, security cameras.
The devil's in the details and "AI" is way too broad a term. There are a lot of ways this could be implemented.
AI-based video codecs are on the way.
Arguably already here.
Look at this description of Samsungs mobile AI for their S24 phone and newer tablets:
AI-powered image and video editing
Galaxy AI also features various image and video editing features. If you have an image that is not level (horizontally or vertically) with respect to the object, scene, or subject, you can correct its angle without losing other parts of the image. The blank parts of that angle-corrected image are filled with Generative AI-powered content. The image editor tries to fill in the blank parts of the image with AI-generated content that suits the best. You can also erase objects or subjects in an image. Another feature lets you select an object/subject in an image and change its position, angle, or size.
It can also turn normal videos into slow-motion videos. While a video is playing, you need to hold the screen for the duration of the video that you want to be converted into slow-motion, and AI will generate frames and insert them between real frames to create a slow-motion effect.
Not all of those are the same thing. AI upscaling for compression in online video may not be any worse than "dumb" compression in terms of loss of data or detail, but you don't want to treat a simple upscale of an image as a photographic image for evidence in a trial. Sport replays and hawkeye technology doesn't really rely on upscaling, we have ways to track things in an enclosed volume very accurately now that are demonstrably more precise than a human ref looking at them. Whether that's better or worse for the game's pace and excitement is a different question.
The thing is, ML tech isn't a single thing. The tech itself can be used very rigorously. Pretty much every scientific study you get these days uses ML to compile or process images or data. That's not a problem if done correctly. The issue is everybody is both assuming "generative AI" chatbots, upscalers and image processers are what ML is and people keep trying to apply those things directly in the dumbest possible way thinking it is basically magic.
I'm not particularly afraid of "AI tech", but I sure am increasingly annoyed at the stupidity and greed of some of the people peddling it, criticising it and using it.
Cheap security cams with “enhanced night vision” might get somebody jailed.
Might? We've been arresting the wrong people based on shitty facial recognition for at least 5 years now. This article has examples from 2019.
On one hand, the potential of this type of technology is impressive. OTOH, the failures are super disturbing.
It's already being used for things it shouldn't be.
Probably not far. NVidia has had machine learning enhanced upscaling of video games for years at this point, and now they've also implemented similar tech but for frame interpolation. The rendered output might be 720p at 20FPS but will be presented at 1080p 60FPS.
It's not a stretch to assume you could apply similar tech elsewhere. Non-ML enhanced, yet still decently sophisticated frame interpolation and upscaling has been around for ages.
Nvidias game upscaling has access to game data and also training data generated by gameplay to make footage that is appealing to the gamers eye and not necessarily accurate. Security (or other) cameras don't have access to this extra data and the use case for video in courts is to be accurate, not pleasing.
Your comparison is apples to oranges.
The real question is could we ever really trust photographs before AI? Image manipulation has been a thing long before the digital camera and Photoshop. What makes these images we see actually real? Cameras have been miscapturing image data for as long as they have existed. Do the light levels in a photo match what was actually there according to the human eye? Usually not. What makes a photo real?
They can. But theres a reasonable level of trust that a security feed has been kept secure and not tampered with by the owner if he doesnt have a motive. But what if not even the owner know that somewhere in their tech chain, maybe the camera, maybe the screen, maybe the storage device, maybe all 3, the image was "improved". No evidence of tampering. We'll have the police blaming Count Rugen for a bank robbery he didnt do, but the camera clearly shows a six fingered man!
Jesus Christ, does this even need to be pointed out!??
Unfortunately it does need pointing out. Back when I was in college, professors would need to repeatedly tell their students that the real world forensics don't work like they do on NCIS. I'm not sure as to how much thing may or may not have changed since then, but based on American literacy levels being what they are, I do not suppose things have changed that much.
you might be referring to the CSI Effect
Yes. When people were in full conspiracy mode on Twitter over Kate Middleton, someone took that grainy pic of her in a car and used AI to “enhance it,” to declare it wasn’t her because her mole was gone. It got so much traction people thought the ai fixed up pic WAS her.
Don't forget people thinking that scanlines in a news broadcast over Obama's suit meant that Obama was a HOLOGRAM and ACTUALLY A LIZARD PERSON.
I met a student at university last week at lunch who told me he is stressed out about some homework assignment. He told me that he needs to write a report with a minimum number of words so he pasted the text into chatGPT and asked it about the number of words in the text.
I told him that every common text editor has a word count built in and that chatGPT is probably not good at counting words (even though it pretends to be good at it)
Turns out that his report was already waaaaay above the minimum word count and even needed to be shortened.
So much about the understanding of AI in the general population.
I'm studying at a technical university.
I’m studying at a technical university.
AI is gonna fuck up an entire generation or more.
The layman is very stupid. They hear all the fantastical shit AI can do and they start to assume its almighty. Thats how you wind up with those lawyers that tried using chat GPT to write up a legal brief that was full of bullshit and didnt even bother to verify if it was accurate.
They dont understand it, they only know that the results look good.
The layman is very stupid. They hear all the fantastical shit AI can do and they start to assume its almighty. Thats how you wind up with those lawyers that tried using chat GPT to write up a legal brief that was full of bullshit and didnt even bother to verify if it was accurate.
Especially since it gets conflated with pop culture. Someone who hears that an AI app can "enhance" an image might think it works like something out of CSI using technosmarts, rather than just making stuff up out of whole cloth.
There's people who still believe in astrology. So, yes.
And people who believe the Earth is flat, and that Bigfoot and the Loch Ness Monster exist, and there are reptillians replacing the British royal family...
People are very good at deluding themselves into all kinds of bullshit. In fact, I posit that they're better even at it than learning the facts or comprehending empirical reality.
Good god, there are still people who believe in phrenology!
Of course, not everyone is technology literate enough to understand how it works.
That should be the default assumption, that something should be explained so that others understand it and can make better, informed, decisions. .
It's not only that everyone isn't technologically literate enough to understand the limits of this technology - the AI companies are actively over-inflating their capabilities in order to attract investors. When the most accessible information about the topic is designed to get non-technically proficient investors on board with your company, of course the general public is going to get an overblown idea of what the technology can do.
Its not actually worse than eyewitness testimony.
This is not an endorsement if AI, just pointing out that truth has no place in a courtroom, and refusing to lie will get you locked in a cafe.
Too good, not fixing it.
I’d love to see the “training data” for this model, but I can already predict it will be 99.999% footage of minorities labelled ‘criminal’.
And cops going “Aha! Even AI thinks minorities are committing all the crime”!
Tell me you didn't read the article without telling me you didn't read the article
Imagine a prosecution or law enforcement bureau that has trained an AI from scratch on specific stimuli to enhance and clarify grainy images. Even if they all were totally on the up-and-up (they aren't, ACAB), training a generative AI or similar on pictures of guns, drugs, masks, etc for years will lead to internal bias. And since AI makers pretend you can't decipher the logic (I've literally seen compositional/generative AI that shows its work), they'll never realize what it's actually doing.
So then you get innocent CCTV footage this AI "clarifies" and pattern-matches every dark blurb into a gun. Black iPhone? Maybe a pistol. Black umbrella folded up at a weird angle? Clearly a rifle. And so on. I'm sure everyone else can think of far more frightening ideas like auto-completing a face based on previously searched ones or just plain-old institutional racism bias.
just plain-old institutional racism bias
Every crime attributed to this one black guy in our training data.
According to the evidence, the defendant clearly committed the crime with all 17 of his fingers. His lack of remorse is obvious by the fact that he's clearly smiling wider than his own face.
clickity clackity
"ENHANCE"
AI enhanced = made up.
It's incredibly obvious when you call the current generation of AI by its full name, generative AI. It's creating data, that's what it's generating.
Everything that is labeled "AI" is made up. It's all just statistically probable guessing, made by a machine that doesn't know what it is doing.
The fact that it made it that far is really scary.
I'm starting to think that yes, we are going to have some new middle ages before going on with all that "per aspera ad astra" space colonization stuff.
Aren't we already in a kind of dark age?
People denying science, people scared of diseases and vaccination, people using anything AI or blockchain as if it were magic, people defending power-hungry, all-promising dictators, people divided over and calling the other side barbaric. And of course, wars based on religion.
Seems to me we're already in the dark.
Aren’t we already in a kind of dark age?
A bit over 150 years ago, slavery was legal (and commonplace) in the United States.
Sure, lots of shitty stuff in the world today... but you don't have to go far back to a time when a sherif with zero evidence relying on unverified accusations and heresy would've put up a "wanted dead or alive" poster with a drawing of the guy's face created by an artist who had never even laid eyes on the alleged murderer.
Oh for sure. We are already in a period that will have some fancy name in future anthropology studies but the question is how far down do we still have to go before we see any light.
Aren’t we already in a kind of dark age?
In the sense of actually making things in the backbone of our civilization becoming a process and knowledge heavily centralized and removed from most people living their daily lives, yes.
Via many small changes we've come to the situation where everybody uses Intel and AMD or other very complex hardware, directly or in various mechanisms, which requires infrastructure and knowledge more expensive than most nation-states to produce.
People no more can make a computer usable for our daily processes via soldering something together using TTL logic and elements bought in a radio store, and we could perform many tasks via such computers, if not for network effect. We depend on something even smart people can't do on their own, period.
It's like tanks or airplanes or ICBMs.
A decent automatic rifle or grenade or a mortar can well be made in a workshop. Frankly even an alternative to a piece of 50s field artillery can be, and the ammunition.
What we depend on in daily civilian computing is as complex as ICBMs, and this knowledge is even more sparsely distributed in the society than the knowledge of how ICBMs work.
And also, of course, the tendency for things to be less repairable (remember the time when everything came with manuals and schematics?) and for people to treat them like magic.
This is both reminiscent of Asimov's Foundation (only there Imperial machines were massive, while Foundation's machines were well miniaturized, but the social mechanisms of the Imperial decay were described similarly) and just psychologically unsettling.
Why not make it a fully AI court and save time if they were going to go that way. It would save so much time and money.
Of course it wouldn't be very just, but then regular courts aren't either.
In the same vein Bloomberg just did a great study on ChatGPT 3.5 ranking resumes and it had an extremely noticeable bias of ranking black names lower than the average and Asian/white names far higher despite similar qualifications.
Archive source: https://archive.is/MrZIm
Perfect, a drop-in replacement!
You forgot the /s
Me, testifying to the AI judge: "Your honor I am I am I am I am I am I am I am I am I am"
AI Judge: "You are you are you are you are you are you..."
Me: Escapes from courthouse while the LLM is stuck in a loop
Honestly, an open-source auditable AI Judge/Justice would be preferable to Thomas, Alito, Gorsuch and Barrett any day.
Be careful what you wish for.
This actually opens an interesting debate.
Every photo you take with your phone is post processed. Saturation can be boosted, light levels adjusted, noise removed, night mode, all without you being privy as to what's happening.
Typically people are okay with it because it makes for a better photo - but is it a true representation of the reality it tried to capture? Where is the line of the definition of an ai-enhanced photo/video?
We can currently make the judgement call that a phones camera is still a fair representation of the truth, but what about when the 4k AI-Powered Night Sight Camera does the same?
My post is more tangentially related to original article, but I'm still curious as what the common consensus is.
Every photo you take with your phone is post processed.
Years ago, I remember looking at satellite photos of some city, and there was a rainbow colored airplane trail on one of the photos. It was explained that for a lot of satellites, they just use a black and white imaging sensor, and take 3 photos while rotating a red/green/blue filter over that sensor, then combining the images digitally into RGB data for a color image. For most things, the process worked pretty seamlessly. But for rapidly moving objects, like white airplanes, the delay between the capture of red/green/blue channel created artifacts in the image that weren't present in the actual truth of the reality being recorded. Is that specific satellite method all that different from how modern camera sensors process color, through tiny physical RGB filters over specific subpixels?
Even with conventional photography, even analog film, there's image artifacts that derive from how the photo is taken, rather than what is true of the subject of the photograph. Bokeh/depth of field, motion blur, rolling shutter, and physical filters change the resulting image in a way that is caused by the camera, not the appearance of the subject. Sometimes it makes for interesting artistic effects. But it isn't truth in itself, but rather evidence of some truth, that needs to be filtered through an understanding of how the image was captured.
Like the Mitch Hedberg joke:
I think Bigfoot is blurry, that's the problem. It's not the photographer's fault. Bigfoot is blurry, and that's extra scary to me.
So yeah, at a certain point, for evidentiary proof in court, someone will need to prove some kind of chain of custody that the image being shown in court is derived from some reliable and truthful method of capturing what actually happened in a particular time and place. For the most part, it's simple today: i took a picture with a normal camera, and I can testify that it came out of the camera like this, without any further editing. As the chain of image creation starts to include more processing between photons on the sensor and digital file being displayed on a screen or printed onto paper, we'll need to remain mindful of the areas where that can be tripped up.
The crazy part is that your brain is doing similar processing all the time too. Ever heard of the blindspot? Your brain has literally zero data there but uses "content-aware fill" to hide it from you. Or the fact, that your eyes are constantly scanning across objects and your brain is merging them into a panorama on the fly because only a small part of your field of vision has high enough fidelity. It will also create fake "frames" (look up stopped-clock illusion) for the time your eyes are moving where you should see a blur instead. There's more stuff like this, a lot of it manifests itself in various optical illusions. So not even our own eyes capture the "truth". And then of course the (in)accuracy of memory when trying to recall what we've seen, that's an entirely different can of worms.
Fantasitc expansion of my thought. This is something that isn't going to be answered with an exact scientific value but will have to decided based on our human experiences with the tech. Interesting times ahead.
We can currently make the judgement call that a phones camera is still a fair representation of the truth
No you can't. Samsung's AI is out there now and it absolutely will add data to images and video in order to make them look better. Not just adjust an image but actually add data...on it's own. If you take an off angle photo and then tell it to straighten it it will take your photo, re-orient, and then "make up" what should have been in the corner. It will do the same thing for video. With video it also has the ability flat out add frames in order to do the slow-motion effect or smooth out playback if the recording was janky.
Samsung has it out there now so Apple and rest of the horde will surely be quick in rolling it out.
Computational photography in general gets tricky because it relies on your answer to the question "Is a photograph supposed to reflect reality, or should it reflect human perception?"
We like to think those are the same, but they're not. Your brain only has a loose interest in reality and is much more focused on utility. Deleting the irrelevant, making important things literally bigger, enhancing contrast and color to make details stand out more.
You "see" a reconstruction of reality continuously updated by your eyes, which work fundamentally differently than a camera.Applying different expose settings to different parts of an image, or reconstructing a video scene based on optic data captured over the entire video doesn't capture what the sensor captured but it can come much closer to representing what the human holding the camera perceived.
Low light photography is a great illustration of this, because we see a person walk from light to dark and our brains will shamelessly remember what color their shirt was and that grass is green and update your perception, as well as using a much longer "exposure" time to capture more light data to maintain color perception in low light conditions, even though we might not have enough actual light to make those determinations without clues.I think most people want a snapshot of what they perceived at the moment.
I like the trend of the camera capturing the image, and also storing the "plain" image. There's also capturing the raw image data, which is basically a dump of the cameras optic sensor data. It's basically what the automatic post processing is tweaking, and what human photographers use to correct light balance and stuff.There's different types of computational photography, the ones which ensures to capture enough sensor data to then interpolate in a way which accurately simulates a different camera/lighting setup are in a way "more realistic" than the ones which heavily really on complex algorithms to do stuff like deblurring. My point is essentially that the calculations done has to be founded in physics rather than in just trying to produce something artistic.
I was wondering that exact same thing. If I take a portrait photo on my Android phone, it instantly applies a ton of filters. If I had taken a picture of two people, and then one of those people murders the other shortly afterwards, could my picture be used as evidence to show they were together just before the murder? Or would it be inadmissible because it was an AI-doctored photo?
You'd think it would be obvious you can't submit doctored evidence and expect it to be upheld in court.
If only it worked that way in practice eh.
We found these marijuanas in his pocket, they were already in evidence bags for us even.
The model that can separate the fact from fiction and falsehood will be worth far more than any model creating fiction and falsehood.
For example, there was a widespread conspiracy theory that Chris Rock was wearing some kind of face pad when he was slapped by Will Smith at the Academy Awards in 2022. The theory started because people started running screenshots of the slap through image upscalers, believing they could get a better look at what was happening.
Sometimes I think, our ancestors shouldn’t have made it out of the ocean.
Just for now, soon this practice will be normalized and widely used, after all we are in the late capitalism stage and all violations are relativized
“Just so we’re clear guys, fake evidence is not allowed”
We do not need AI pulling a George Lucas.
AI can make any blurry criminal look like George Lucas with the right LoRAs.
Used to be that people called it the "CSI Effect" and blamed it on television.
Funny thing. While people worry about unjust convictions, the "AI-enhanced" video was actually offered as evidence by the defense.
"When we enhance the image and place a knife in the defendant's hand..."
During Kyle Rittenhouse's trial the defense attorney objected to using the pinch to zoom feature of an iPad because it (supposedly) used AI. This was upheld by the judge so the prosecution couldn't zoom in on the video.
This is the best summary I could come up with:
A judge in Washington state has blocked video evidence that’s been “AI-enhanced” from being submitted in a triple murder trial.
And that’s a good thing, given the fact that too many people seem to think applying an AI filter can give them access to secret visual data.
Lawyers for Puloka wanted to introduce cellphone video captured by a bystander that’s been AI-enhanced, though it’s not clear what they believe could be gleaned from the altered footage.
For example, there was a widespread conspiracy theory that Chris Rock was wearing some kind of face pad when he was slapped by Will Smith at the Academy Awards in 2022.
Using the slider below, you can see the pixelated image that went viral before people started feeding it through AI programs and “discovered” things that simply weren’t there in the original broadcast.
Large language models like ChatGPT have convinced otherwise intelligent people that these chatbots are capable of complex reasoning when that’s simply not what’s happening under the hood.
The original article contains 730 words, the summary contains 166 words. Saved 77%. I'm a bot and I'm open source!
Yeah, this is a really good call. I'm a fan of what we can do with AI, when you start looking at those upskilled videos with a magnifying glass... It's just making s*** up that looks good.
How does this work when you have a shitty Samsung that turns a pic of a pic of the moon into the Moon by adding details that weren't there?
Here is an alternative Piped link(s):
Piped is a privacy-respecting open-source alternative frontend to YouTube.
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Nor evidence, for that matter
Sure, no algorithm is able to extract any more information from a single photo. But how about combining detail caught in multiple frames of video? Some phones already do this kind of thing, getting multiple samples for highly zoomed photos thanks to camera shake.
Still, the problem remains that the results from a cherry-picked algorithm or outright hand-crafted pics may be presented.
Depends on implementation, if done properly and if they don't try to upscale and deblur too much then that kind of interpolation between multiple frames can be useful to extract more detail. If it's a moving subject then this type of zoom can create false results because the algorithm can't tell the difference and will think it's an optical artifact. For stationary subjects and photographers it can be useful
Wait, when did that become ok to do in The first place
They told the AI it was going to get locked up with the viruses because they had evidence it was generating CSAM.
But I thought AI was just magic, and could do anything...
enhance
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Think about how they reconstructed what the Egyptian Pharoahs looks like, or what a kidnap victim who was kidnapped at age 7 would look like at age 12. Yes, it can't make something look exactly right, but it also isn't just randomly guessing. Of course, it can be abused by people who want jurys to THINK the AI can perfectly reproduce stuff, but that is a problem with people's knowledge of tech, not the tech itself.
Unfortunately, the people with no knowledge of tech will then proceed to judge if someone is innocent or guilty.
