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Science Advances
Article . 2023 . Peer-reviewed
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Science Advances
Article . 2023
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https://dx.doi.org/10.5167/uzh...
Other literature type . 2023
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https://dx.doi.org/10.48550/ar...
Article . 2023
License: CC BY SA
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Preprint . 2024
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AI model GPT-3 (dis)informs us better than humans

Authors: Spitale, Giovanni; Biller-Andorno, Nikola; Germani, Federico;

AI model GPT-3 (dis)informs us better than humans

Abstract

Artificial intelligence (AI) is changing the way we create and evaluate information, and this is happening during an infodemic, which has been having marked effects on global health. Here, we evaluate whether recruited individuals can distinguish disinformation from accurate information, structured in the form of tweets, and determine whether a tweet is organic or synthetic, i.e., whether it has been written by a Twitter user or by the AI model GPT-3. The results of our preregistered study, including 697 participants, show that GPT-3 is a double-edge sword: In comparison with humans, it can produce accurate information that is easier to understand, but it can also produce more compelling disinformation. We also show that humans cannot distinguish between tweets generated by GPT-3 and written by real Twitter users. Starting from our results, we reflect on the dangers of AI for disinformation and on how information campaigns can be improved to benefit global health.

Country
Switzerland
Keywords

FOS: Computer and information sciences, 1000 Multidisciplinary, Multidisciplinary, Computer Science - Artificial Intelligence, Computer Science - Human-Computer Interaction, 610 Medicine & health, Social and Interdisciplinary Sciences, Human-Computer Interaction (cs.HC), Computer Science - Computers and Society, Artificial Intelligence (cs.AI), Artificial Intelligence, Computers and Society (cs.CY), 10222 Institute of Biomedical Ethics and History of Medicine, Humans, Social Media

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    164
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 1%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 0.1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
164
Top 1%
Top 1%
Top 0.1%
Green
gold