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Module: Visual Literacy - Images and Video

By SAUFEX Consortium • 23 January 2026

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A dramatic photo shows devastation from a recent disaster. You share it to raise awareness. Later, you learn the image is from a different disaster years earlier.

The photo is real, but the context is false. Visual manipulation isn’t just about fake images - it’s often about real images used deceptively.

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Why Visual Content Deceives

Humans process images faster than text. A powerful image creates emotional impact before rational thinking engages.

This makes visual content especially effective for manipulation:

  • Images feel more “real” than text descriptions
  • Strong visuals trigger emotional responses
  • We’re more likely to share compelling images
  • Visual verification takes more effort than reading

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Types of Visual Manipulation

Fabrication: Entirely fake images (traditional or AI-generated)

Manipulation: Real images altered through editing

Misleading context: Real images with false captions or context

Selective framing: Real but misleadingly cropped or angled images

Each requires different detection approaches.

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Fabrication and AI-Generated Images

Modern AI can create photorealistic images of events that never happened. Detection indicators include:

  • Unusual textures or patterns (especially in backgrounds)
  • Impossible lighting or shadows
  • Strange distortions in hands, teeth, or text
  • Overly perfect or symmetrical features
  • Inconsistent perspective or scale

But AI improves constantly - visual artifacts become harder to spot.

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Traditional Manipulation

Photoshop and similar tools can alter images. Look for:

  • Inconsistent lighting across the image
  • Unnatural edges or halos around objects
  • Cloned or repeated patterns
  • Mismatched shadows
  • Compression artifacts in one area but not others
  • Impossible reflections

Professional manipulation is difficult to detect without forensic analysis.

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The Context Problem

The most common form of visual deception uses real, unaltered images in false contexts:

  • Old photos presented as recent
  • Images from one location presented as another
  • Staged photos presented as candid
  • Screenshots from movies or games presented as real
  • Images cropped to remove important context

This is harder to detect because the image itself is genuine.

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Your most powerful tool is reverse image search:

Google Images: Upload or paste image URL to find where else it appears

TinEye: Specialized reverse image search, good for finding original sources

Yandex: Often finds images Google misses, especially from Russian sources

This reveals if an image has appeared before in different contexts or with different descriptions.

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Using Reverse Search Effectively

  1. Take screenshot or save the image

  2. Upload to reverse image search

  3. Look for earliest appearances

  4. Check if image appears in different contexts

  5. Verify the original source and caption

Even if an image is real, reverse search reveals when it’s being misused with false context.

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Video Verification Challenges

Video is harder to manipulate than still images, but not impossible:

  • Deepfakes can alter faces and voices
  • Editing can remove crucial context
  • Real footage can be mislabeled
  • Clips can be taken out of sequence
  • Selective editing changes meaning

For video, check the original source and look for longer, unedited versions.

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Reading Visual Clues

Learn to analyze images critically:

  • Text and signs: What language? What businesses or locations?
  • Clothing and uniforms: Do they match the claimed context?
  • Weather and vegetation: Does it match the claimed location and season?
  • Technology and vehicles: Do they match the claimed time period?
  • Cultural markers: Do details match the claimed context?

Inconsistencies reveal false contexts.

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Verification Best Practices

Before sharing dramatic visual content:

  1. Pause and question emotional response

  2. Run reverse image search

  3. Check if credible news outlets verified it

  4. Look for the original source

  5. Examine image for manipulation indicators

  6. Consider whether context could be false

  7. If uncertain, don’t share

Taking these steps reduces viral spread of visual deception.

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The Broader Challenge

As AI-generated and manipulated visuals become more sophisticated, verification becomes harder. This means:

  • Trust reputable sources that verify images
  • Be increasingly skeptical of standalone visual claims
  • Understand that seeing isn’t always believing anymore
  • Don’t rely on visual content alone for important claims

Visual literacy is increasingly critical as manipulation technology advances. Healthy skepticism and verification habits are your best defense.

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