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, N/A-N/A
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Sub-type Journal article Author Atkins, Carmen
Girgente, Gina
Shirzaei, Manoochehr
Junghwan KimTitle 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 N/A Publisher Springer Nature Start page N/A 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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