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TRUVACE RECORD VERSION
record: TRV-2026-2596
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T07:59:53.430451Z
status: published
lens: p_space
sector: science
headline: AI talking science: Experimental studies on the perception of AI-based chatbots as sources of science-based information
dek: AI-based chatbots offer new opportunities for communicating science-based information, but often fall short of established standards. We conducted two pre-registered experiments examining user perceptions of an AI-based chatbot providing information on nanoparticles in sunscreen. Study one (N = 508) tested whether a disclaimer about the chatbot's uncertain training data affected perceived source trustworthiness and information credibility. The results showed no significant effect of the disclaimer; perceptions w…
gain_title: (none)
problem_title: In an online experiment with 1,059 German adults, the same sunscreen-nanoparticle answers were rated less trustworthy (5.11 vs 5.64 out of 7) and less credible (4.96 vs 5.38) when attributed to an AI chatbot than to a scientist.
trace_subject: (none)
gain_reading: (none)
gain_evidence: (none)
problem_reading: In an online experiment with 1,059 German adults, the same sunscreen-nanoparticle answers were rated less trustworthy (5.11 vs 5.64 out of 7) and less credible (4.96 vs 5.38) when attributed to an AI chatbot than to a scientist.
problem_evidence: persons who received the information from an AI-based chatbot ascribed lower trustworthiness to the source (M = 5.11, SD = 1.12) than persons who received the information from a scientist (M = 5.64, SD = 0.98) | perceived the source of the information to be less credible (M = 4.96, SD = 1.37) than persons who received the information from a scientist (M = 5.38, SD = 1.21)
quick_read: Two pre-registered online experiments in Germany tested how people judge health information about nanoparticles in sunscreen when it comes from an AI chatbot. In the second study, 1,059 adults saw identical content attributed either to a chatbot called ChatAI or to a human scientist. The scientist was rated more trustworthy (5.11 for the chatbot vs 5.64 on a seven-point scale) and the information more credible (4.96 vs 5.38).

The first study, with 508 adults, tested a generic disclaimer warning that the chatbot's data sources were uncertain, similar to the one OpenAI uses for ChatGPT. It did not significantly change trust or credibility ratings. Participants' prior attitudes toward chatbots mattered far more than the warning did.

The results suggest that generic transparency labels are a weak way to shape trust in AI-delivered health information. The authors recommend pairing chatbot answers with cues of human expert oversight. The experiments used a single scripted chat about a low-risk topic, so they do not show how people react to real chatbot use or higher-stakes advice.
limitation: Participants only viewed a one-time scripted chat rather than using a real chatbot, the topic carried low perceived risk, and the online panel sample was German-speaking, relatively young and well educated.
tag: Evidence-backed problem
key_points: Study one (508 German adults, recruited October 2023) found the disclaimer had no significant effect on trustworthiness (p = .114) or credibility (p = .152). | The disclaimer's effect on perceived objectivity was statistically significant but below the researchers' pre-set threshold for a meaningful effect (Cohen's f = .10 vs .15). | Attitudes toward chatbots were the strongest predictor of trust in study one (Cohen's f = .55 for trustworthiness), ahead of frequency of chatbot use (.28). | Study two (1,059 adults, February 2024) used a 2 by 2 design: chatbot vs scientist, and a gradually unfolding chat vs a static block of text. | Scientists were seen as more objective than the chatbot, and perceived objectivity fully explained the credibility gap and mediated the trust gap. | Dynamic, chat-style delivery was rated as more objective, trustworthy and credible than static text, whether the source was a chatbot or a scientist. | Most participants held negative or undecided attitudes toward chatbots, yet the chatbot still earned substantial trust and credibility ratings.
rundown: Participants were asked to imagine a friend seeking advice about buying sunscreen with nanoparticles and then saw a chat history. The chatbot was named ChatAI; in study two the human source was a project called Science Chat with a named professor. The content was factually correct and identical across conditions, and it ended with a recommendation to use sunscreen with nanoparticles.

Samples were recruited through the panel provider GapFish with age and gender quotas approximating the German adult population. Study one kept 508 participants (mean age 49.83) and study two kept 1,059 (mean age 47.27) after excluding 104 inattentive or very fast respondents.

In study one, the disclaimer did not move ratings even when the analysis excluded the 55% of participants who failed the attention check. The authors offer three possible explanations: the information matched existing beliefs, the disclaimer was ignored, or it was too generic compared with specific warnings.

In study two, the source effect on trustworthiness was moderate (Cohen's f = .31) and smaller on credibility (f = .20). The authors say the gaps were rather modest and may narrow as people grow more familiar with AI tools, and they link the preference for humans to algorithm aversion.
sources:
- peer_reviewed | Journal of Science Communication | https://doi.org/10.22323/170720260228062648 | 2026-05-25
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