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Area of Science:

  • Human-Computer Interaction
  • Information Science
  • Cognitive Psychology

Background:

  • Conversational agents powered by large language models (LLMs) are increasingly used for information retrieval.
  • Ensuring users can accurately assess the credibility of LLM-generated information is crucial due to potential factual inaccuracies.
  • Understanding factors influencing user credibility judgments is essential for mitigating misinformation.

Purpose of the Study:

  • To investigate how the presentation mode of information (conversational agent vs. static text) affects users' ability to detect inaccuracies.
  • To compare credibility judgments across different types of conversational agents (text-based, voice-based) and a static online encyclopedia.
  • To identify whether the conversational nature of LLM agents hinders accurate credibility assessment.

Main Methods:

  • Conducted two preregistered experiments involving participants rating the credibility of accurate and partially inaccurate information.
  • Information was presented via a dynamic text-based LLM agent, a voice-based agent, or a static text-based online encyclopedia.
  • Analyzed data using mediation analysis to understand the role of conversational nature in credibility judgments.

Main Results:

  • Participants were significantly better at detecting inaccuracies when information was presented as static text compared to both text-based and voice-based conversational agents.
  • This effect persisted regardless of whether the information sources were branded (e.g., ChatGPT, Alexa, Wikipedia) or unbranded.
  • Mediation analysis supported the hypothesis that the conversational format of LLM agents poses a threat to accurate credibility assessment.

Conclusions:

  • The presentation mode of information critically influences users' ability to discern factual accuracy.
  • Conversational interfaces, despite their dynamic nature, may inadvertently reduce users' critical evaluation of information.
  • Future research and design should consider the impact of presentation modality on combating misinformation effectively.