00:00Do you remember that fake image of the pope in the puffy jacket?
00:03Or how about when Donald Trump recently shared those pictures of Swifties for Trump?
00:08Or how about that fake AI-generated picture that showed an explosion happening near the Pentagon
00:13last year? Some of these examples are obviously more concerning than others, but whether it's
00:18for funsies or mayhem, they all illustrate the same thing. Generative AI is getting really,
00:25really convincing. This tech is now adept, pervasive, readily accessible, and increasingly
00:31fast. And there are countless reasons to be concerned about how that might impact the trust
00:35that we place in photos, and how that trust, or lack thereof, could be used to manipulate us.
00:43We've already seen a glimpse of this. Generative AI is driving an increase in scams, and the
00:48internet is full of political deepfakes in the run-up to the US presidential election.
00:53Photographic evidence does not mean much in a world where anything, believably,
00:58could be faked. Watermarking is easy to remove, and detection-based methods, like the websites
01:05that you drop an image into and they can supposedly tell whether an image is real or AI-generated,
01:10are notoriously unreliable. So what's actually being done to protect people from being misled?
01:16Good news! There are a bunch of initiatives that are working on how to resolve this mess.
01:21One of the best-known is C2PA Authentication, something set up by the Coalition for Content
01:27Provenance and Authenticity, C2PA itself, and the Content Authenticity Initiative,
01:32which Adobe set up back in 2019. This system has the backing of huge tech companies like
01:38Microsoft, Google, OpenAI, Intel, Arm, and Truepick, and their solution is data. Specifically,
01:46metadata, which uses hard-to-remove cryptographic digital signatures to
01:50attach key information to an image about its journey before it reaches us as a viewer.
01:55It's kind of like a nutrition label, but for digital content. In theory, when this is attached
02:00to an image and we can see it, it should help us to determine what's real, what's fake, and if it
02:06is, how that fakery happened. Here's a rough breakdown of how this works. Step one, the C2PA
02:12and CAI create this technical standard, and then a bunch of companies all across the industry,
02:17from photography to image editing to image hosting, then have to agree to use and support
02:24that standard. Step two, camera hardware makers and editing app makers then agree to embed their
02:30products with these metadata credentials. That could be in the form of content credentials,
02:34like what Adobe uses, or under any other name really. The important thing is that it supports
02:39the C2PA technical standard, and everything works together in tandem. Step three, online platforms
02:47will then scan images uploaded into them for these metadata credentials, and then provide the
02:52information in that to their viewers. Or, alternatively, if you just have any picture that you want to
02:58check, if it carries some kind of content credentials, you should be able to do so via a separately
03:02hosted database. For example, if I was going to take a picture on a Leica M11P camera, which supports
03:08the C2PA standard, it should log all the important information, such as the camera settings, and the
03:15date and time, and even location of where that image was taken, and embed it into the file itself.
03:20I can then take that picture and put it into Photoshop to make any edits with it, and whatever
03:25has changed, including if generative AI tools were used to make those changes, will also be logged in
03:31that metadata. Even if I put a picture in there that didn't already carry some kind of C2PA standard
03:36metadata credentials, Photoshop will still embed that metadata into the image, so that it'll show
03:43if I used generative fill, or any of the other generative AI powered tools that Adobe has.
03:48Then, image hosting platforms, like social media generally, will then be able to scan that picture
03:53if I upload it, pull that information out, and provide it to their viewers, because it isn't
03:57visibly available on the image itself. In theory, if all of these steps are adhered to, we should be
04:04able to more easily tell which images are authentic, which ones have been manipulated, and which ones
04:10specifically are AI generated, or have been manipulated using generative AI tools. Which all
04:16sounds way, way easier on paper compared to how this is actually going. So, here's the bad news.
04:24Progress is extremely slow. The problem is interoperability, and it's taking years to get all
04:30necessary players for this on board. And if we can't get everyone on board, the system might be doomed
04:36to fail entirely. C2PA support is currently only available on a handful of cameras, including Sony's
04:43A1, A7S3, and A7IV, and Leica's aforementioned M11P. And while other brands like Nikon and Canon
04:51have pledged that they're going to support it, most have yet to meaningfully do so. Smartphones,
04:57the most accessible cameras for most people, are also lacking behind with any built-in C2PA support.
05:04It's a similar situation across editing apps. Adobe is implementing this across Photoshop and
05:09Lightroom, but while some other services like Capture One have said they're looking into
05:13traceability features like C2PA, most don't, or have yet to express any interest in doing so.
05:19And one of the biggest roadblocks to all of this is figuring out the best way to present that
05:24information to viewers. Facebook and Instagram are two of the biggest platforms that do check for
05:29this information and do flag some of that to their viewers, but Meta's early attempt also angered
05:35photographers rather than helped them because they were flagging everything with a made-with-AI label,
05:41even if it was edited using regular tools that didn't use generative AI, like the cloning tool.
05:47Meanwhile, X, which is already completely saturated with all of these AI-generated images and deepfakes,
05:53hasn't implemented any kind of verification system, C2PA or otherwise. And that's despite
05:59having joined the C2PA back in 2021 before Elon Musk had purchased the platform. He had this to
06:05say at the 2023 AI Safety Summit.
06:08So some way of authenticating would be good. So yeah, that sounds like a good idea, we should probably do it.
06:18There you go.
06:19But nothing has actually materialized yet. There is this recurring argument that we shouldn't be
06:24concerned about the direction that generative AI is going to take us because this is nothing new.
06:30Photoshop has been able to manipulate images for 35 years, but do you know how f***ing hard it is to
06:35manually edit a photo like that in one of these apps? I looked up YouTube tutorials on how I would
06:41be able to do this and even if I wanted to add a lion to a picture, the videos giving me demonstrations
06:46for that are 10-11 minutes long. If I wanted to do that on a new Pixel or Samsung phone though, I can
06:53just tap an area and tell it to add a lion. It's already going to take all of those complicated
06:58nuisances like perspective and lighting into consideration. And even if, cool, you follow a
07:04tutorial and you do create a very realistically edited image in Photoshop, that's just one picture.
07:11These AI editing apps that are now free and on our phones can do that in seconds. And even if
07:17the first one doesn't look as good, you can just keep going until it looks right. And none of this
07:21even takes into consideration just how expensive this kind of software can be. Adobe stops just
07:27short of basically asking for your first born child and you have to dodge all of their really
07:32complicated cancellation policies. But even if you use a free alternative like GIMP, you're still
07:38going to need access to a desktop computer or a laptop. Which not everyone has now that we live
07:43in a world where smartphones can do just about everything. Meanwhile, it's taken barely a couple
07:48of years from generative AI apps to go from spitting out distorted Cronenberg-esque mashups
07:55with 17 fingers to creating something that's actually quite authentically believable. Something
08:01that takes texture and lighting into account and with no skill at all. In seconds. It's much easier
08:08to dismiss things like photojournalism in a world where anything could not be real. You can't always
08:15expect that people are going to do the right thing and now anyone with a smartphone, hypothetically,
08:21could churn out highly manipulated images at a speed and scale we've never had to experience
08:27before. And yeah, you're going to get some people that are going to argue, well, with Photoshop
08:31having existed, we shouldn't be trusting online images to begin with. And that might be the way
08:36forward. But do you really want to live in a world like that? Where you can't trust any picture that
08:41you see online? I don't. That sounds horrifying. And look, I don't want this to necessarily be a
08:48doomsday argument. This is just one possibility of where generative AI could be taking us.
08:54But even if we take a step back and we look at some of the far less serious implications,
08:59it's still incredibly f***ing annoying. Platforms like Pinterest that used to be really, really good
09:03for referencing materials for artists or finding haircuts or makeup examples that you're going to
09:09give to your stylist, right? You can't really use them anymore because the entire site is just
09:13populated with AI generated images and none of them are really flagged to indicate that that's
09:18the case. Even if, by some miracle, we woke up tomorrow in a tech landscape where all of this
09:23is working, the online platforms, camera makers and editing app providers are all on board and
09:28cooperating together, this system might still not actually solve the issue at hand. Denialism is a
09:35potent and potentially insurmountable obstacle in all of this and it doesn't matter if you're
09:40going to supply people with evidence that something is real if they're simply going to
09:45ignore it. And just to rub some additional salt into all of our wounds right now, despite the
09:51issues these systems are already facing, a cryptographic labeling solution is realistically
09:57our best hope to reliably identify authentic manipulated and AI generated content at scale
10:05and even then they were never supposed to be a bulletproof solution. The companies that created
10:10systems like ctpa authentication completely understand that bad actors exist and just because
10:16something is difficult to be tampered with doesn't mean it's impossible. Meanwhile, doctoring images
10:22with good or bad intentions is now the easiest and most accessible it has ever been. We're going
10:29to have to live with that and it could leave us in a precarious situation. Nations all around the world
10:35are struggling to introduce regulations that can police the more harmful aspects of this stuff
10:40without accidentally infringing on things like artistic expression or parody or, more importantly,
10:46free speech. And it's highly unlikely that AI companies are going to pump the brakes on
10:50development while we're figuring out how we can get to grips with it. As a result, we're dangerously
10:56close to living in a reality where we have to be wary about being deceived by every single image
11:02put in front of us. Thanks for watching! Speaking of which, can you guess which one of these objects
11:08is AI generated? How about this one?
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