Can We Reliably Detect AI-Generated Images?

Visual clues are temporary

Unusual hands, repeated textures and broken text once made synthetic images easy to spot. Models improve quickly, and editing or compression can remove obvious artifacts. A checklist can support review, but it cannot prove origin by itself.

Context is often more revealing: Who published the image? Is there an earlier source? Do shadows, weather and event details match independent evidence?

Limits of detectors

AI classifiers estimate likelihood based on patterns in their training data. New generators, resizing and screenshots can reduce accuracy. False positives are especially harmful when a genuine image is labeled synthetic.

Detector scores should be one signal in a broader verification process, not a final verdict.

Provenance is promising

Signed capture credentials and edit histories can show where a file came from and how it changed. Provenance does not judge whether the scene is true, but it can provide a stronger chain of information than visual guessing alone.