Political campaigns across the United States have entered a new digital era during the 2026 midterm elections.
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campaigns → enter → elections
It is now being used as an active tool in political campaigns.
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It → use → campaigns
From realistic fake audio recordings targeting candidates just hours before polling begins to automated tools that create and target AI-generated video ads, the technology is making it harder for voters to decide what information they can trust.
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they → target → information
Election monitors and political strategists are struggling to deal with an online environment where genuine campaign material is becoming increasingly difficult to separate from computer-generated content.
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material → struggle → content
Public concern about the impact of AI-generated media has reached high levels.
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concern → generate → levels
A survey by the Bipartisan Policy Center found that
77 per cent of voters were deeply concerned about the use of artificial intelligence to spread false information or influence public opinion during this election cycle.
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cent → find → cycle
The findings show that voters across the political spectrum share these concerns, with majorities from both major parties identifying deepfakes and automated persuasion as serious threats to fair elections.
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majorities → show → elections
These concerns have also started changing campaign strategies.
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concerns → start → strategies
Axios reported last week that Democratic groups had launched a
$4 million advertising campaign across four competitive House of Representatives districts.
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groups → report → districts
The campaign was designed to test whether voters support stricter rules for artificial intelligence.
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voters → design → intelligence
Deepfakes blur the line between real and fake
One of the biggest changes in the 2026 midterms is how easily people can now create realistic fake content.
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people → blur → content
In earlier election cycles, changing digital images or recordings required special technical skills and expensive computer systems.
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changing → change → skills
Today, widely available software allows campaign workers or outside groups to copy a politician's voice or create convincing videos using simple written instructions.
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workers → allow → instructions
During the autumn campaign season, AI-generated content appeared in several closely contested races.
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content → generate → races
Fake audio recordings designed to sound like candidates making controversial statements were shared through messaging apps.
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recordings → design → apps
Some were released shortly before important debates, giving fact-checkers little time to check them before they spread further.
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they → release → them
Fake videos have also become part of negative political campaigns.
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videos → become → campaigns
Instead of using traditional edited footage, some AI-generated advertisements show completely fictional scenes.
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advertisements → use → scenes
These videos may depict candidates taking part in unpopular activities or appearing alongside controversial public figures.
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candidates → depict → figures
The spread of such material has created more work for election officials and news organisations.
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spread → create → officials
Fact-checkers now have to spend time checking whether audio recordings and videos are genuine before examining the political claims they contain.
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they → have → claims
This has slowed down political reporting and made it harder to respond quickly to misleading content.
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it → slow → content
Machine learning changes how campaigns target voters
Apart from creating public-facing fake content, political campaigns are also using machine-learning systems to improve how they reach voters.
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they → change → voters
These tools analyse large amounts of information, including shopping habits, social media activity and past voting records.
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tools → analyse → habits
They can then create messages aimed at specific groups of people.
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They → create → people
Traditional political advertising usually targets broad groups based on factors such as age or location.
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advertising → target → age
AI tools can go much further by creating personalised messages for smaller groups and even individual voters.
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tools → go → groups
Algorithms can produce thousands of different versions of an advertisement in real time, changing the words, images and emotional tone to match what a particular voter is likely to respond to.
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voter → produce → what
This allows campaigns to test different messages and quickly identify which ones work best.
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ones → allow → messages
Political teams can run hundreds of online advertisements at the same time and stop using ineffective versions within minutes.
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teams → run → minutes
They can make these decisions by tracking how people respond to the advertisements.
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people → make → advertisements
However, researchers warn that this type of automated targeting could increase political divisions.
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type → warn → divisions
When different groups receive completely different political messages, voters may end up seeing very different versions of the same issue.
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voters → receive → issue
This could create separate information bubbles and make it harder for people to understand opposing views.
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people → create → views
Voters struggle to identify AI-generated content
The growing use of AI-generated material in political discussions has left many voters unsure about the information they see and hear.
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they → struggle → information
As fake videos become more realistic, signs that once exposed digital editing are becoming harder to spot.
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that → become → editing
These included unusual lighting, strange eye movements and distorted background sounds.
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These → include → lighting
Election security experts warn that the growing gap between AI technology and tools designed to detect fake content has created another problem.
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gap → warn → problem
It is known as the "liar's dividend".
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It → know → dividend
This happens when politicians or public figures can deny genuine but embarrassing recordings by falsely claiming that they were created using artificial intelligence.
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they → happen → intelligence
…and 4 more, not listed.