How to Tell If a Video Is AI Generated
AI-generated videos are getting scarily good. But no matter how realistic they look, there are still tells — subtle signs in the video output that indicate artificial generation. Whether you’re vetting content for authenticity, moderating UGC, or just curious, here’s how to spot the difference.
Visual Artifacts That Give It Away
Even with highly advanced models, the visual output often contains flaws that break the illusion. Here’s what to look for:
🧍♂️ Human Movement & Expression
| Feature | Human | AI-Generated |
|---|---|---|
| Eye blinking | Natural, irregular | Too frequent or not at all |
| Facial symmetry | Naturally asymmetric | Often overly perfect |
| Lip sync | Matches speech closely | Slightly off or delayed |
| Hand gestures | Varied, fluid | Repetitive or unnatural |
| Micro-expressions | Subtle and context-aware | Missing or exaggerated |
🖐️ Hands, Fingers, Limbs
- AI still struggles with:
- Finger count inconsistencies (six fingers, bent wrong)
- Merging limbs during complex movement
- Stiff elbows or wrists
- Hand-object interaction (cups, phones, tools feel off)
🖼️ Background Weirdness
- Warped objects when the camera pans
- Flickering or melting edges
- Shadows that move incorrectly or don’t align
- Repeated background patterns (due to texture cloning)
Audio-Visual Desynchronization
Even if the face looks good, sync between sound and video is often a weak point in AI-generated content.
Look out for:
- Voices not matching the physical presence (tone, age, emotional depth)
- Voice lag (audio comes before or after lip movement)
- Environmental sounds that don’t reflect visuals (e.g. footsteps not matching the floor)
Inconsistency Across Frames
AI models often hallucinate inconsistencies between frames, especially with motion.
🔄 Watch for:
- Changing clothes mid-video without a cut
- Hair flickering or changing style
- Glasses or jewelry disappearing then reappearing
- Tattoos or skin marks vanishing between frames
These aren’t editing errors — they’re generation flaws.
Unnatural Eye Behavior
The eyes are often the hardest thing for AI to get right.
- Over-smooth eyeball movement (lacking saccades)
- Inconsistent gaze direction (especially when looking at a person or camera)
- Over-reflective or matte eyes, depending on the model
💡 Pro tip: Slow the video to 0.25x speed and focus on the eyes. You’ll see it.
Speech Patterns and Phrasing
Even when text-to-video is layered with AI voice synthesis, language models often default to odd cadences.
- Perfect grammar, but no rhythm
- Lack of filler words (“uh,” “like”) in casual speech
- Sentences that end abruptly or unnaturally
- Emotion mismatch — a cheerful tone during serious content
Deepfake vs Fully AI-Generated: Know the Difference
| Feature | Deepfake (Face Swap) | Fully AI-Generated Video |
|---|---|---|
| Base footage | Real human footage | Entirely synthetic |
| Body movement | Human | Often robotic or glitchy |
| Background | Real environment | AI-generated or composited |
| Limitations | Mostly face area | Whole scene may contain flaws |
This distinction helps you narrow down what kind of detection approach to use.
Detection Techniques You Can Use Right Now
While tools help, some quick manual techniques work surprisingly well:
- Pause randomly during motion – AI often reveals visual glitches during transitions.
- Zoom into extremities – ears, fingers, eyes, hairlines.
- Scrub frame-by-frame – pay attention to object interaction (hands on doorknobs, fingers on screens).
- Watch with no audio – visual flaws stand out more.
- Then watch with no visuals – test how “real” the audio sounds by itself.
Red Flags in Story or Context
Sometimes the content itself makes less sense than the visuals.
Look for:
- Events that feel "too generic" — overly sanitized scenes
- People with no backstory or metadata
- Crowds or busy scenes where no one interacts
- News-style footage with no verifiable source
If it looks like it should be real but no one else is talking about it — that’s a red flag.
Table: Quick AI Video Spotting Checklist
| Category | What to Look For |
|---|---|
| Faces | Blinking, asymmetry, weird smiles |
| Hands | Wrong fingers, floaty motions |
| Eyes | Glassy, robotic, flickering |
| Audio | Lip sync mismatch, robotic tone |
| Background | Melting, morphing, repetition |
| Consistency | Vanishing objects, changing features |
| Context | No source, oddly generic situations |
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Bonus: Hidden Signs from AI Video Generation Pipelines
If you know what generation model likely produced the video, you can guess its weak spots:
| Model Type | Known Artifacts |
|---|---|
| Text-to-video (e.g., Sora) | Unreal physics, object detachment |
| Frame interpolation-based | Ghosting in motion, warped edges |
| GAN-based avatars | Repetitive movements, over-smooth skin |
| 3D generative humans | Rigid poses, unnatural head turns |
These flaws aren’t always visible, but if you're familiar with their signatures, they’re easy to recognize.
Why It Matters: Not Just for Misinformation
- Brand protection – Don't let synthetic content hijack your reputation.
- Content moderation – Spotting fake testimonials or manipulated videos.
- Ethical media use – Ensuring consent in generative portrayals.
- Creative integrity – Distinguish human-crafted video from AI output in art, storytelling, and marketing.