How do you tell if an image is actually AI generated? I keep running into this with photos submitted for content use. Some look slightly off but I can’t always put my finger on why. Are the visual tells still reliable, or has the gap between real and generated photography closed enough that you can’t trust your gut anymore?
The visual tells have shifted a lot. Hands and backgrounds are less reliable than they used to be. What holds up better: look at specular highlights on reflective surfaces, transitions between hair and background, and whether shadows are internally consistent. These are computationally expensive to get right. For practical purposes, human judgment alone isn’t enough. Running images through multiple tools and treating the results as a signal rather than a verdict is the more defensible approach.
honestly the gut check still works on low-quality generations but the better models are getting very hard to call. in my experience the tell is usually the lighting. real photos have one coherent light source story. a lot of AI images have lighting that doesn’t quite add up when you study it closely.
From an SEO standpoint, search engines are getting better at flagging AI-generated images and it’s starting to affect image search rankings. Not definitive proof of anything, but if a tool flags it and rankings drop, that’s two signals pointing the same direction.
I’ve been using this as a classroom exercise, having students try to identify AI images before and after seeing the tool results. The gap between confident and correct is usually pretty wide. It’s a useful lesson in calibrated uncertainty.
the meta-question here is whether ‘is this AI’ is even the right frame. a lot of generated images are used in ways where the origin doesn’t change the ethics of the use. the framing matters more than the detection.
We had this happen during a product launch. The system flagged an unusual transaction pattern and froze everything right when we needed access most. The appeal process is not designed for speed. It’s designed to protect the institution, which means you absorb the cost of their error.