Concern 449 · Working draft · editorial review in progress

Political deepfake video

A political deepfake video makes a public figure appear to do or say something that was digitally invented.

Understanding the concern

Video often feels like eyewitness evidence. AI can produce a face, mouth movements or an entire scene that resembles a recording. The problem begins when someone presents that invention as a real event, especially when viewers have little time to check before voting or sharing it.

This differs from an openly labeled parody. The question is whether people are misled about what happened. A convincing image does not prove its own history. Newsrooms and election officials can compare the clip with original recordings, independent witnesses and the channel that first released it.

An example

Imagine a fabricated clip showing a candidate accepting a bribe the night before an election.

Illustrative unless identified as a documented case.

Words in plain English

AI
Software that learns patterns from examples or uses rules to perform tasks such as recognizing images or generating text. It can make mistakes and does not understand every situation as a person would.

Evidence and its limits

These sources explain the mechanism and election risks. The example is hypothetical and does not claim that a deepfake changed an election result.

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Broader frameworks and background

These resources provide context. They do not establish every claim in this concern.

People and organizations cited

Public writing, not endorsement, partnership, or affiliation.

International Committee of the Red Cross

A question to discuss

What evidence would we want before treating a surprising political video as real?

Keep track of different views, what needs checking, and any next step in your own discussion notes.

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Principles for the conversation

Before you finish · reflect together

Virtues and principles to consider

Virtues are qualities we practice in how we treat people and make choices. They are not scores for judging someone. Use these ideas to explore what a thoughtful response could look like.

Truthfulness

Truthfulness means making claims that match the evidence and being clear about what we do not know. It includes correcting mistakes rather than protecting a polished story.

Check sources, label guesses, and distinguish a trial result from a proven benefit. If AI helped produce a claim, someone still needs to take responsibility for checking it.

Ask together: What can we honestly say, and what still needs checking?

Meaningful conversation

Conversation means making room to understand and be understood. It is more than winning a debate or collecting quick agreement. People can explore a question together without starting from the same view.

Use a concrete example, invite different experiences, and ask what might change each person's mind. Let concerns and hopes sit together long enough to reveal choices that a simple yes-or-no argument would miss.

Ask together: What can we learn from each other before deciding?

Unity

Unity means working toward shared purposes while making room for real differences. It does not require everyone to have the same experience, beliefs, or opinion.

Look for a goal people can share, then explore disagreements about how to reach it. Make sure quieter or less powerful voices can influence the result.

Ask together: What purpose can we share while respecting our differences?

Editorial ratings

These are editorial judgments from the register, not measured probabilities or predictions about your situation.

Severity
Major · 4/5
Likelihood
Documented at scale · 5/5
Time horizon
Now
Register risk score
20
About the register and scoring →
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