Opportunities and limitations of the ChatGPT Advanced Data Analysis plugin for hydrological analyses

Dylan J. Irvine; Landon J. S. Halloran; Philip Brunner

doi:10.1002/hyp.15015

Opportunities and limitations of the ChatGPT Advanced Data Analysis plugin for hydrological analyses

Dylan J. Irvine, Landon J. S. Halloran, Philip Brunner

Research Institute for Environment and Livelihoods

Research output: Contribution to journal › Comment/debate › peer-review

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Abstract

Artificial intelligence (AI) tools, such as ChatGPT, have already changed the way that many industries operate. Much of the recent discussion surrounding AI tools has focused on their ability to generate text and the associated ethical concerns. Recent developments with the ChatGPT Code Interpreter, now called the Advanced Data Analysis plugin, demonstrate that AI's growing abilities in the generation, translation and adaptation of computer scripts also offer significant potential to change the way that data analyses are conducted. We demonstrate the new capabilities of ChatGPT, providing four worked examples of prompt-based generation of Python scripts to analyse hydrological datasets. Our examples include (1) converting R functions to Python to perform baseflow separation, (2) converting MATLAB functions to Python to ‘web scrape’ temperature data, (3) creating a correlation matrix of major ion groundwater data, and (4) presenting boxplots of river flow data. We discuss the significant opportunities, current limitations and concerns relating to the use of ChatGPT in hydrological data analyses.

Original language	English
Article number	e15015
Pages (from-to)	1-5
Number of pages	5
Journal	Hydrological Processes
Volume	37
Issue number	10
DOIs	https://doi.org/10.1002/hyp.15015
Publication status	Published - Oct 2023

Bibliographical note

Funding Information:
The text of this article was written without the assistance of AI. The data analyses were facilitated using either ChatGPT-3.5, or ChatGPT-4 (i.e., the paid version). We would like to thank HPToday Editor Prof. James McNamara for helpful feedback and discussion. DJI would like to thank the many researchers for the discussions on the ethical use of AI tools. Open Access is facilitated through Charles Darwin University through the Council of Australian University Librarians (CAUL).

Publisher Copyright:
© 2023 The Authors. Hydrological Processes published by John Wiley & Sons Ltd.

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10.1002/hyp.15015

88579448-oaFinal published version, 704 KBLicence: CC BY

https://onlinelibrary.wiley.com/doi/abs/10.1002/hyp.15015

Cite this

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title = "Opportunities and limitations of the ChatGPT Advanced Data Analysis plugin for hydrological analyses",

abstract = "Artificial intelligence (AI) tools, such as ChatGPT, have already changed the way that many industries operate. Much of the recent discussion surrounding AI tools has focused on their ability to generate text and the associated ethical concerns. Recent developments with the ChatGPT Code Interpreter, now called the Advanced Data Analysis plugin, demonstrate that AI's growing abilities in the generation, translation and adaptation of computer scripts also offer significant potential to change the way that data analyses are conducted. We demonstrate the new capabilities of ChatGPT, providing four worked examples of prompt-based generation of Python scripts to analyse hydrological datasets. Our examples include (1) converting R functions to Python to perform baseflow separation, (2) converting MATLAB functions to Python to {\textquoteleft}web scrape{\textquoteright} temperature data, (3) creating a correlation matrix of major ion groundwater data, and (4) presenting boxplots of river flow data. We discuss the significant opportunities, current limitations and concerns relating to the use of ChatGPT in hydrological data analyses.",

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note = "Funding Information: The text of this article was written without the assistance of AI. The data analyses were facilitated using either ChatGPT-3.5, or ChatGPT-4 (i.e., the paid version). We would like to thank HPToday Editor Prof. James McNamara for helpful feedback and discussion. DJI would like to thank the many researchers for the discussions on the ethical use of AI tools. Open Access is facilitated through Charles Darwin University through the Council of Australian University Librarians (CAUL). Publisher Copyright: {\textcopyright} 2023 The Authors. Hydrological Processes published by John Wiley & Sons Ltd.",

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Opportunities and limitations of the ChatGPT Advanced Data Analysis plugin for hydrological analyses

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