# 两场实验显示与聊天机器人对话约七分钟比事实清单更能削弱阴谋论信念

- 来源：The Decoder：AI News（RSS）
- 作者：Jonathan Kemper
- 发布时间：2026-09-05 20:39
- AIHOT 分数：61
- AIHOT 链接：https://aihot.news/items/cmtoe8dst01xlrohtrkqqeu8a
- 原文链接：https://the-decoder.com/seven-minutes-with-a-chatbot-beat-a-fact-sheet-at-reducing-conspiracy-beliefs-in-two-experiments

## AI 摘要

Carnegie Mellon、MIT 和 Cornell 的研究者在 Trump 遇刺未遂和 Charlie Kirk 枪击事件后的几天内各开展一次在线实验，用 Gemini（1.5 和 2.5 版本）进行平均约七分钟的证据型对话，Trump 实验保留 472 名参与者，Kirk 实验保留 1035 名。

## 正文

A brief conversation with a language model can reduce conspiracy beliefs right after a crisis, even when hard evidence is thin on the ground. The effect carries over to new events weeks later, according to researchers.

Within a week of the assassination attempt on Donald Trump in July 2024, about half of a representative US sample had heard the event was staged. Eleven percent believed it. After the murder of far-right activist Charlie Kirk in September 2025, theories about Mossad involvement, a "false flag" operation, and a government cover-up spread within days.

A new study from researchers at Carnegie Mellon, MIT, and Cornell tested whether short conversations with a large language model could weaken those narratives during that exact window. For both events, the answer was yes, and the effect extended beyond the event itself.

Two online experiments ran in the days after each attack

The researchers recruited US adults through a survey platform and used GPT-4o, now more than two years old, to filter for participants who expressed conspiracy beliefs about the event. The Trump experiment kept 472 participants, the Kirk experiment 1,035.

After measuring baseline beliefs, participants were randomly assigned to one of three conditions. One group had at least five rounds of back-and-forth with Google Gemini (version 1.5 from February 2024 in the first experiment, version 2.5 from June 2025 in the second), with the model told to reduce conspiracy beliefs through evidence-based conversation. A second group got a static fact sheet with source citations. The third had an irrelevant control chat about whether cats or dogs make better companions.

Both events happened after the training cutoff of the models used, so neither could draw on internal knowledge. The researchers built a curated fact base directly into the system prompt, split into confirmed facts, claims already debunked, and questions explicitly marked as open. In the Kirk experiment, web search was also allowed, but only to verify factual claims.

The dialogue beat a static fact sheet

The conversations averaged about seven minutes and reduced belief in the participant's own conspiracy theory in both experiments, against both the control condition and the fact sheet. Agreement with statements about a "cover-up or conspiracy" and "hidden or undisclosed factors" dropped too.

In both experiments, belief in the participant's own conspiracy theory dropped more after the LLM dialogue than after reading a static fact sheet. | Image: Costello et al.

Trust in the official explanation didn't increase in the Trump experiment. The authors think that's because no clear official explanation existed at the time. All anyone knew was that security had failed, and the shooter's motive was still unclear even when the study was written up.

In the Kirk experiment, where authorities had already shared details about the perpetrator, trust in the official explanation rose slightly compared to the control chat. The difference compared to the fact sheet wasn't significant. The Kirk dialogue also had no measurable effect on support for political violence.

The model shifted tactics based on how much was known

To figure out how the model persuaded people, the researchers broke its responses into individual sentences. The model clearly adapted to the available evidence.

For the Trump assassination attempt, the model leaned on epistemic humility, source criticism, and Socratic questioning, while it relied more on factual arguments for classic conspiracy theories. | Image: Costello et al.

For the Trump attempt, where almost nothing was known about the shooter's motive or background, the model used rational persuasion less often than with classic conspiracy theories. Instead, it acknowledged the limits of its own knowledge, urged caution about jumping to conclusions, asked Socratic questions meant to make users think about their own evidence, and pointed to credible sources.

For the Kirk assassination, where more information was available, the approach looked more like what it did with classic conspiracies, with more emphasis on the societal harms of conspiratorial thinking.

Debunking one event inoculated against the next

The debunking conversation spilled over into later events. Two months after the first Trump assassination attempt, another armed man was arrested on Trump's property. Participants who had gone through the debunking dialogue were less likely to believe that only a few powerful people would learn the truth or that it would be hidden from the public.

The effect persisted over time. Participants from the debunking group rated later events as less likely to involve a cover-up, though the difference did not hold for the Grand Blanc Township shooting. | Image: Costello et al.

Two and a half weeks after Kirk's murder, a shooting and arson attack hit a Church of Jesus Christ of Latter-day Saints in Grand Blanc Township, Michigan. The researchers surveyed their participants again eleven days later. The main analysis found no significant direct effect for this event.

A secondary analysis suggested part of the original effect was still visible in conspiracy narratives about the church attack. The transfer showed up more clearly in general conspiracy beliefs, with people who had talked to the model less likely to agree with common conspiracy narratives.

In effect, the debunking intervention worked as a kind of prebunking against future false claims. Unlike standard prebunking methods, where people are warned ahead of time and exposed to a weakened version of the misinformation, this effect happened without any advance preparation.

Getting people to talk to an LLM remains the hard part

The authors stress their work is a case study. There may be crises where the approach fails, and cases where an actual conspiracy exists and debunking would be wrong. They also point to their own earlier work showing that similar dialogues can work in reverse, convincing people of conspiracy narratives. For newly emerging conspiracies, the authors flag this as a potential abuse risk.

Of course, people have to be willing to talk to a language model about their beliefs in the first place. But when they do, even short conversations can make a measurable difference, even when there's little counter-evidence to work with.

The same team cut belief in established conspiracy theories by about 20 percentage points through conversations with GPT-4 two years ago, with effects still measurable two months later and for narratives that never came up in the dialogue. What's new here is the test on fresh events where facts were scarce.

Why conversation beats a fact sheet was the subject of a study with nearly 77,000 participants. Language models in dialogue were 41 to 52 percent more persuasive than a short text message, and the deciding factor was the sheer volume of sourced claims, not fancy conversational tactics. The same mechanism can be turned against people, as an unauthorized experiment by the University of Zurich on Reddit showed.

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