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People who avoid AI chatbots often cite disinterest, privacy, or doubts about accuracy—not one shared anti-tech agenda. Criticism of social media likewise includes worries about loneliness, surveillance, misinformation, and effects on children, alongside recognition that these platforms can help people connect and organize. The evidence points to overlapping reservations, not a single organized movement or a wholesale public rejection of technology.
Is there one anti-tech movement?
“Anti-tech movement” is a useful frame for discussing technology skepticism, but the evidence summarized here does not establish a unified organization, common membership, leadership, or shared platform. Surveys document reasons some people do not use AI chatbots and attitudes toward social media; they do not show that these people belong to one movement.
Nor does skepticism mean that most people have rejected AI. In a February 2026 survey, about half of U.S. adults said they used AI chatbots, even as many expressed reservations about AI’s effects and oversight. Pew Research Center’s report on Americans’ views of AI captures that coexistence.
Why do some people avoid AI chatbots?
Pew Research Center surveyed 5,119 U.S. adults from February 17–23, 2026. Its questions about reasons for non-use went only to people who said they never used AI chatbots. The percentages below therefore describe chatbot non-users—not all U.S. adults. Pew’s report on why Americans don’t use chatbots distinguishes major and minor reasons.
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| Reason among U.S. chatbot non-users | Major reason | Minor reason | Major or minor |
|---|---|---|---|
| Lack of interest | 60% | 23% | 83% |
| Concern about how personal information would be used | 54% | 24% | 79% |
| Distrust of accuracy | 45% | 30% | 76% |
The combined figures are rounded and reflect the share of non-users who gave each answer. They show that reluctance can be practical, as well as rooted in concerns about what a chatbot does with information or whether its answers can be trusted. As Pew put it, “Six-in-ten non-adopters cite lack of interest as a major factor behind not using these tools.” That finding applies to chatbot non-users in this survey.
Some simply don’t see a need
Lack of interest was the most commonly cited reason in Pew’s survey. This matters because not using a tool does not necessarily signal a protest: a person may have no task that makes a chatbot seem useful, or may prefer to do things without one.
Rank #2
Privacy and security are distinct concerns
Among U.S. adults overall in the same February 2026 survey, 71% thought greater AI use would make their personal information less secure. That broader concern sits alongside the non-user finding about data use, but the two measures have different populations and should not be treated as interchangeable. Pew also found that 59% had little or no confidence in U.S. companies to develop and use AI responsibly.
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Some non-users cited distrust of accuracy. A chatbot can sound confident while producing an incorrect answer, so a person may judge it unsuitable for tasks where errors matter. The survey records this as a reason for non-use; it does not establish that every chatbot is inaccurate in every use.
Some people expect to keep opting out
Among U.S. adults who never used chatbots, 67% said they were not too or not at all likely to use one in the following 12 months, while 5% said they were extremely or very likely. These are stated expectations, not evidence of what respondents later did.
Do the reasons look similar in the UK?
The UK Department for Science, Innovation and Technology’s 2025/2026 public-engagement survey found several overlapping reasons among non-users of generative AI in its online sample:
- 44% preferred to do things without AI.
- 33% worried about privacy or security.
- 32% felt they did not know enough to use it.
- 31% worried it might be inaccurate.
These figures concern non-users in the online sample, not all UK adults. The report says the question was not included in its paper questionnaire. The results broadly echo the themes in the U.S. survey, but the populations and survey questions differ, so the percentages should not be pooled or compared as if they measured one group. The UK government’s DSIT Public Engagement Survey 2025/2026 provides the qualification.
What worries people about AI beyond personal use?
Reservations are not limited to an individual’s decision to use a chatbot. In Pew’s February 2026 U.S. survey, about two-thirds of adults thought AI was advancing too quickly. Many also lacked confidence in U.S. companies to develop and use it responsibly. These findings point to concerns about the pace and governance of AI, not just whether a tool is useful in a particular task. They do not establish that respondents oppose all AI or want its development to stop.
Why do people criticize social media?
A 2024 Abundance Institute report records concerns about social media’s effects on children, loneliness, surveillance, hate, and misinformation. It also records perceived benefits, including connection and activism. Taken together, those attitudes are mixed: people can value the ability to find community or mobilize around an issue while objecting to harms they associate with platforms.
The report’s inspected results do not provide enough information about field dates and methods to support broad claims about how representative these views are. They describe attitudes in that report, not the share of all users who have quit, reduced their use, or joined an anti-tech campaign. The Abundance Institute’s 2024 report on AI, social media, and anti-technology politics includes both sides of this picture.
Quick Recap
What the evidence can—and cannot—say
- It can show reasons and attitudes. Recent U.S. and UK surveys identify disinterest, privacy or security, low confidence in accuracy, and lack of knowledge among AI non-users.
- It can show skepticism alongside adoption. Many U.S. adults use chatbots, while substantial shares express concern about AI’s effects, pace, or responsible use.
- It cannot establish one coordinated movement. The cited material does not document shared membership, leadership, or a common program.
- It cannot explain social-media quitting rates. The available social-media evidence concerns perceived harms and benefits, not how many people have stopped using platforms or why particular individuals left.
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