Generative AI tools can enhance climate literacy but must be checked for biases and inaccuracies

Atkins, Carmen, Girgente, Gina, Shirzaei, Manoochehr and Junghwan Kim, (2024). Generative AI tools can enhance climate literacy but must be checked for biases and inaccuracies. communications earth and environment, 226 (2024)-n/a

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  • Sub-type Journal article
    Author Atkins, Carmen
    Girgente, Gina
    Shirzaei, Manoochehr
    Junghwan Kim
    Title Generative AI tools can enhance climate literacy but must be checked for biases and inaccuracies
    Appearing in communications earth and environment
    Publication Date 2024-04-30
    Place of Publication Berlin
    Publisher Springer Nature
    Start page 226 (2024)
    End page n/a
    Language eng
    Abstract In the face of climate change, climate literacy is becoming increasingly important. With wide access to generative AI tools, such as OpenAI’s ChatGPT, we explore the potential of AI platforms for ordinary citizens asking climate literacy questions. Here, we focus on a global scale and collect responses from ChatGPT (GPT-3.5 and GPT-4) on climate change-related hazard prompts over multiple iterations by utilizing the OpenAI’s API and comparing the results with credible hazard risk indices. We find a general sense of agreement in comparisons and consistency in ChatGPT over the iterations. GPT-4 displayed fewer errors than GPT-3.5. Generative AI tools may be used in climate literacy, a timely topic of importance, but must be scrutinized for potential biases and inaccuracies moving forward and considered in a social context. Future work should identify and disseminate best practices for optimal use across various generative AI tools.
    Copyright Holder author(s)
    Copyright Year 2024
    Copyright type Creative commons
    DOI 10.1038/s43247-024-01392-w
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    Created: Fri, 27 Sep 2024, 04:09:02 JST by Haideh Beigi on behalf of UNU INWEH