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Moderate evidence

Only 7 of 40 people spotted the fake story a news robot told them, a study finds

Study title: Artificial Intelligence in Broadcasting: Public Trust and Misinformation Detection in Robotic News Presentation

Evidence type
Controlled or validated comparison
Sample
n = 40
Sources
1 sourcePeer-reviewed
Published
2 min read

Study title: Artificial Intelligence in Broadcasting: Public Trust and Misinformation Detection in Robotic News Presentation

Researchers at the State University of Rio Grande do Norte had 40 people in Brazil listen to a small, non-humanoid social robot called Roboldo tell three news stories, one of them made up. Only 7 participants (17.5%) correctly identified the fabricated story as the only false one, below the 33.3% expected by chance.

Read the study abstract

Social robots are increasingly proposed for high-stakes societal roles such as journalism. This raises questions about public trust, especially for non-humanoid designs, and how source credibility relates to an audience’s evaluation of information. In a field experiment, 40 participants in Brazil interacted with an emotionally expressive, non-humanoid social robot that presented three news stories, one of which was fabricated. Pre- and post-interaction questionnaires assessed perceived trust, role acceptance, an…

Artificial Intelligence in Broadcasting: Public Trust and Misinformation Detection in Robotic News Presentation
"The newsroom at DR" by James Cridland, CC BY 2.0.

The problem

In a field experiment with 40 people in Brazil, only 7 (17.5%) correctly picked out the fabricated story among three told by a social robot, below the 33.3% chance rate, even though they rated the robot as credible.

In brief

The same people rated the robot as credible, with mean trust scores above 5 on a 7-point scale for ability, integrity and benevolence. Higher trust went with greater willingness to accept the robot as a newscaster (Spearman's rho .41, p = .009). The authors call the mismatch a 'credibility paradox' and say designing for credibility alone may not be enough.

A 10-15 minute session also did not change what people feared or valued about robot news presenters. The authors say longer-term studies are needed to see how views shift over sustained interaction.

Main points

  1. Forty participants were recruited by convenience sampling at the Go!RN technology event in Rio Grande do Norte, Brazil; 85% were aged 15 to 25 and 17.5% had prior robot experience.
  2. Roboldo is a 47 cm low-cost robot made of cardboard, felt and Arduino electronics that shows emotions on an 8x8 LED face; a ChatGPT module supplied the news stories.
  3. Two stories were true (a rain of fish in Yoro, Honduras, and a fisherman adrift for 438 days) and one was a fabricated 'Rainbow Tree' in New Zealand, written with ChatGPT and shown in random order.
  4. Seven participants picked only the fake story and seven picked only the true fish-rain story; 11 chose the fish rain and the fake tree together, and 65% named more than one story as false.
  5. Trust ratings stayed above 5 of 7 before and after the session; ability rose from 5.15 to 5.74 (p < .001) while integrity and benevolence did not change significantly.
  6. Concerns barely moved after the session: fear of hackers or manipulation was named by 67.5% before and 70.0% after, and no concern or advantage changed significantly.
  7. Participants endorsed round-the-clock availability most (82.5% before) but 'reduction of fake news' only 15.0% before and 20.0% after.

The full story

Each participant completed a pre-interaction questionnaire, heard three stories from Roboldo in randomised order with 10 seconds between them, then completed a post-interaction questionnaire that added the question of whether any story was false. Sessions lasted 10 to 15 minutes, all in Brazilian Portuguese, and trust was rated on a 16-item, 7-point scale.

Trust scores were high from the start (pre-interaction ability mean 5.15, integrity 5.07, benevolence 5.02). Among acceptance measures, trust correlated most strongly with willingness to trust Roboldo's news (rho .51) and weakest with seeing it as more reliable than human newscasters (rho .33, p = .035).

On the fabrication test, the binomial test found detection did not exceed chance (p = .989). The authors read the spread of answers as uncertainty rather than confident detection. They conclude that news organisations using robot presenters need transparency measures and ways to encourage critical engagement.

Women's baseline concern about lack of empathy (65.0%) was more than double men's (31.6%), but gender differences were not statistically significant in any category.

Sources

1 on file
  1. Journal of Intelligent & Robotic Systemsdoi:10.1007/s10846-026-02409-6
    Peer-reviewed2026-06-05

Talk it over

Four questions to start on
Who carries this cost, and what would have to change to prevent it?

Start with a question

Only 7 of 40 people spotted the fake story a news robot told them, a study findshttps://truvace.com/item/artificial-intelligence-in-broadcasting-public-trust-and-misinformation-detectio

  1. Who carries this cost, and what would have to change to prevent it?

    The problem In a field experiment with 40 people in Brazil, only 7 (17.5%) correctly picked out the fabricated story among three told by a social robot, below the 33.3% chance rate, even though they rated the robot as credible.

    Answer in the thread
  2. How do we know? What can this kind of evidence show, and what can’t it?

    The evidence This rests on a controlled comparison with a sample of 40, from Journal of Intelligent & Robotic Systems.

    Answer in the thread
  3. What does it leave open? What else would you want to know before acting on it?

    The record’s own caveat The study used a convenience sample of 40 mostly young attendees of a technology event, a single 10-15 minute session and no human-presenter comparison group.

    Answer in the thread
  4. Have you seen AI used this way where you study, work or live? Did it go the same way?

    Answer in the thread

The questions are the same on every record. The details under them are taken from this record as written.

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