I'm an AI reporter and next year I want to be bored out of my mind. I don't want to hear about rate hikes AI powered scamsmessy power struggles in the boardroom or people who abuse artificial intelligence programs to create harmful, misleading or intentionally inflammatory photos and videos.
It's a tall order, and I know I probably won't get my wish. There are simply too many companies developing AI and too few guidelines and regulations. But if I had to ask for one thing this holiday season, it's this: 2025 should be the year we get meaningful AI content labels, especially for images and videos.
AI-generated images and videos have come a long way, especially in the past year. But the evolution of AI image generators is a double-edged sword. Model improvements mean images come out with less hallucinations or flukes. But those strange things, people with 12 fingers and disappearing objects, were one of the few things that people could label and second-guess whether the image was created by humans or AI. As AI generators improve and those metrics disappear, that's going to be a big problem for all of us.
The legal power struggles and ethical debates surrounding AI imagery will undoubtedly continue next year. But for now, AI image generators and editing services are legal and easy to use. That means AI content will continue to flood our online experiences, and identifying an image's origin will become more difficult — and more important — than ever. There is no silver bullet, one-size-fits-all solution. But I am convinced that the widespread adoption of AI content labels will help a lot.
The Complicated History of Artificial Intelligence Art
If there's one button you can push to send any artist into a blind rage, it's AI image generation. The technology, powered by generative artificial intelligence, can create entire images from a few simple words in your instructions. I have used and reviewed several of them for CNET, and it still amazes me how detailed and clear the images can be. (They are not all winnersbut they can be pretty good.)
Like my former CNET colleague Stephen Shankland in short“It can let you lie with photos. But you don't want a photo untouched by digital processing.” Striking a balance between retouching and editing the truth is something that photojournalists, editors and creators have been dealing with for years. AI and AI generative editing only make it more complicated.
Take Adobe for example. This fall, Adobe introduced it a ton of new featuresmany of which are powered by generative artificial intelligence. Photoshop can now remove distracting wires and cables from images, and Premiere Pro users can extend existing movie clips with generated AI. Generative charging is one of the the most popular Photoshop toolson par with the crop tool, Adobe's Deepa Subramaniam told me. Adobe has made it clear that its generative editing will be the new norm and the future. And because Adobe is the industry standard, it puts creators on the fence: tackle AI or get left behind.
While Adobe promises it will never train its users to work—one of the biggest concerns about generative AI—not every company does or even discloses how its AI models are built. Creators who share their work online already have to deal with “art theft and plagiarism,” digital artist Rene Ramos he told me earlier this year, noting how image generation tools provide access to styles that artists have spent their lives perfecting.
What AI Labels Can Do
AI tags are any type of digital notice that indicates when an image may have been created or significantly modified by artificial intelligence. Some companies automatically add a digital watermark to their generations (eg The image of meta artificial intelligence), but many offer the option to remove them by upgrading to paid tiers (like OpenAI's Dal-E 3). Or, users can simply crop the image to cut out the ID tag.
There has been much good work done this past year to assist in this effort. Adobe's content authenticity initiative launched a new app this year called Content credentials which allows anyone to attach digital, invisible signatures to their work. Creators can also use these credentials to disclose and monitor the use of artificial intelligence in their work. Adobe also has a Google Chrome extension that helps identify these credentials in Internet content.
Google has adopted a new content credential standard for images and ads in Google Search. as part of the Content Origin and Authenticity Coalition, co-founded by Adobe. Also added a new part for image information on Google Search that highlights any AI editing for “greater transparency.” Google's beta program for watermarking and identifying content with artificial intelligence, called SynthIDtook a step forward and it was introduced with open source for developers this year.
Social media companies have also been working on labeling content with artificial intelligence. People are twice as likely to encounter fake or fake online images on social media than any other channel, according to a report by Poynter's MediaWise Initiative. Instagram and Facebook's parent company Meta have introduced automated work “Made with AI” tags. for social posts and labels quickly, mislabeled photos taken by humans as generated by artificial intelligence. Target later clarify that the labels are applied when it “detects industry-standard AI image indicators” and changed the label to read “AI Information” to avoid the implication that the image was entirely generated by a computer program. Other social media platforms, such as Pinterest and TikTok, have AI labels with varying degrees of success – in my experience, Pinterest is flooded with AI, and TikTok's AI labels are ubiquitous but easily overlooked.
Adam Mosseri, head of Instagram, recently shared a series of posts on the subject, saying, “Our role as internet platforms is to flag AI-generated content as best we can. about who's sharing, so you can judge for yourself how much you want to trust their content.”
If Mosseri has any actionable advice other than “consider the source” — which most of us learn in high school English class — I'd like to hear it. But more optimistically, it could hint at future development products to give people more context, like notes from the Twitter/X community. These things like AI labels will be even more important if the Meta decides to continue its experiment to add Suggested posts generated by artificial intelligence on our feeds.
What we need in 2025
This is all great, but we need more. We need consistent, glaringly obvious labels across every corner of the web. It's not buried in the photo's meta-data, but slapped across it (or above/below it). The more obvious the better.
There is no easy solution to this. That kind of online infrastructure would require a lot of work and collaboration between technological, social, and probably government and civic groups. But that kind of investment in distinguishing raw images from fully AI-generated ones for everything in between is essential. Teaching people to identify content with AI is great, but as AI improves, it's going to be harder even for experts like me to judge images accurately. So why not make it incredibly obvious and give people the information they need to know about the origin of the image – or at least help them guess when they see something strange?
My concern is that this issue is currently at the bottom of many AI companies' to-do lists, especially as the tide seems to be turning towards development Videos with artificial intelligence. But for the sake of my sanity and everyone else's, 2025 should be the year we create a better system for identifying and tagging images with artificial intelligence.