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Start with curiosity, not accusation—and check the claim before you challenge it. Trace the post to its source, confirm its date and context, compare it with credible independent reporting, and use an official election authority for voting rules. Then offer to look at the evidence together. If the exchange becomes personal or unproductive, pause.
Before you respond, verify what was shared
A family member can pass along false material while sincerely believing it. PEN America distinguishes misinformation, shared without knowing it is false, from disinformation, shared with intent to deceive. Unless you have evidence of intent, address the claim rather than labeling the person.
- Trace the source. Look for the earliest available post, account, outlet, or document. Check whether the post links to an identifiable source, rather than relying on a cropped screenshot or a repost. Indiana DHS and the Brennan Center recommend checking where political content came from. Indiana DHS guidance and Brennan Center guidance.
- Check date and context. Find when and where the image, video, or claim was first published, if that can be established. Older material can be recirculated as if it were current.
- Look for independent corroboration. Compare the claim with credible reporting and independent fact-checking, such as AP Fact Check or PolitiFact. For election dates, locations, eligibility, or procedures, consult the relevant official election authority rather than a social post or AI-generated summary. PEN America’s guides to verifying information offer further help.
- Use visual clues only as prompts to investigate. Odd shadows, distorted details, mismatched lip movements, or stiff expressions may deserve a closer look, but visual inspection alone cannot establish whether media is genuine or AI-generated.
Detection tools and provenance labels are not decisive. The Brennan Center cautions: “In general, voters should not depend on deepfake detection tools to verify or disprove the authenticity of political content because the tools have limited accuracy.” A provenance label can add context, but it should not replace source checking and corroboration; missing or invalid provenance does not prove that content is either authentic or fabricated. Brennan Center for Justice.
How to start the conversation
Indiana DHS puts the tone simply: “Start from a place of curiosity, not criticism.” Ask what the person thinks and where they saw the item before offering your own conclusion. For example: “Where did you come across this?” or “Can I show you what I found about that?” Indiana DHS also suggests a low-pressure opener: “That is interesting. I saw something different from …” Indiana DHS.
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Make checking the claim a shared task, not a test of who is smarter. You might say, “Would you be willing to compare this with the original source and an independent fact-check?” If you found a discrepancy, explain it briefly and point to one or two reliable sources. Avoid insults, assumptions about motives, or a barrage of links; those can shift the discussion away from whether the claim is supported.
Choose between a private note and a public correction
The right place to respond depends on what you are trying to accomplish. A private message can let a relative reconsider without being embarrassed in front of others. If the post is already spreading, a public correction may help bystanders see more accurate information. But replying can also draw extra attention to the original post. PEN America discusses both the potential value of a public response and this risk of amplification. PEN America.
- Prioritize the relationship: consider a private, respectful message.
- Prioritize bystanders: if the claim is circulating widely, a concise public correction with a credible source may be useful.
- Consider amplification: avoid engaging publicly if your reply is likely to increase visibility without correcting the record effectively.
When to pause
If the conversation becomes defensive, turns into a personal argument, or stops being constructive, step back. You can say that you are happy to compare sources another time, then share a reliable guide for later. You do not have to settle the disagreement in one conversation. PEN America recommends stepping away when engagement is no longer productive. PEN America.
What to expect from corrections and media literacy
There is no reliable promise that one correction will change a relative’s mind or that the change will last. The UK Government Office for Science’s evidence note, published 27 May 2025 and based on an expert roundtable held in March 2024, describes media literacy as useful for recognizing AI-generated disinformation but also notes limits in the evidence: one cited analysis found that belief corrections did not persist at follow-up, and the note does not establish a universally best intervention. UK Government Office for Science, AI and disinformation evidence note.
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A preregistered visual-media study likewise reports inconsistent earlier findings on whether specific advice works better than general advice; its authors say firm conclusions about the effectiveness of particular tips for identifying visual manipulation cannot be made. That is a reason to use visual clues cautiously, not to treat any checklist as a deepfake test. Study of advice for identifying visual manipulation.
Caltech’s 2026 account of a preregistered U.S. panel experiment describes testing AI-generated prebunking against five common myths about the 2024 U.S. election among more than 4,000 registered voters. That result concerns a specific intervention and study context; it does not show that a family conversation will have the same effect. California Institute of Technology, 2026.
AI systems are not dependable arbiters of election truth. In its analysis of tested systems, the Brennan Center reports that models could generate misleading election images and video, often failed to identify AI-generated content, and had uneven safeguards. It also found that systems sometimes pushed back against long-standing false election tropes. The findings do not support either the claim that AI always spreads lies or that it can reliably fact-check political content. Brennan Center analysis.
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How common are reported encounters with election misinformation?
The Electoral Commission’s report on England’s May 2026 elections found that 57% of respondents viewed political misinformation or disinformation as a problem. In that same survey, 44% said they had seen misinformation about party policies, 33% about individual candidates, and 20% about how elections work. Ten percent said they had seen deepfake photos, videos, or audio related to the elections, while 20% were unsure. These are findings about that survey and geography, not estimates for the United States or for AI misinformation prevalence generally. Electoral Commission, 2026 report.
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