Concern about deepfakes is justified, but it distracts from the fact that the overwhelming majority of misleading images involve no advanced technology at all.

The Categories, From Common to Rare

  1. Miscontextualized real photos. A genuine, unedited photograph presented as showing a different event, place or date. This is by far the most common form of image misinformation, and it requires no editing skill whatsoever.
  2. Misleading crops. Removing the person or object that changes the meaning entirely — the classic example being a crop that hides who someone is actually talking to.
  3. Selective editing. Brightness, colour, removal of a small object, or choosing the one frame in a burst where someone looks angry.
  4. Composites. Combining elements from different images.
  5. Synthetic generation. A wholly generated image of an event that never occurred.
  6. Deepfakes proper. Face or voice replacement in video, or synthetic video of a real person.

Note the shape of this list: effort increases going down, frequency decreases. Your verification habits should be weighted accordingly.

Context Beats Forensics

For a typical person evaluating a typical image, these questions catch far more than pixel analysis:

  • Where did it first appear, and when? A reverse image search revealing the same photo from three years ago settles most cases immediately.
  • Who is sharing it, and what's their record?
  • Does anyone else document the same event? Real events produce multiple independent images from different angles.
  • Does the caption make a claim the image alone can't support? Very often the photo is real and the *sentence* is the falsehood.
  • Does it feel designed to make you angry? Emotionally activating content spreads faster and is more likely to be manipulated or miscontextualized.

Technical Checks Worth Doing

  • Reverse image search — the single highest-value tool.
  • Check Content Credentials if present.
  • Look for compression inconsistency: a region that's noticeably sharper or softer than the rest, mismatched noise, or edges that are too clean.
  • Check shadows and reflections for physical consistency.
  • Beware detector tools' confidence. They give probabilities, produce false positives on legitimate edits, and fail on screenshots.

If You Are Targeted

Non-consensual manipulated imagery of real people is a serious harm, and increasingly illegal:

  • Document everything — URLs, screenshots, dates, account names — before reporting, since content often disappears.
  • Report to the platform under its synthetic or non-consensual imagery policy; most major platforms now have specific categories for this.
  • Seek legal advice. Many jurisdictions have introduced specific offences for non-consensual synthetic imagery, alongside existing defamation and harassment law.
  • Contact support organizations that specialize in this; you don't have to manage the process alone.

Protecting Your Own Images

You can't prevent misuse entirely, but you can raise the cost:

  • Limit high-resolution public photos of your face where you can.
  • Watermark images you publish professionally.
  • Keep originals with intact metadata — they're evidence of what the authentic version looks like.
  • Enable Content Credentials where your tools support it.
  • Review privacy settings on accounts where photos of you accumulate.

The realistic posture is neither panic nor complacency: assume images can be fabricated, verify anything consequential through sources rather than inspection, and treat provenance as the thing worth checking.