IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i19p14453-d1253039.html
   My bibliography  Save this article

Conversational AI Tools for Environmental Topics: A Comparative Analysis of Different Tools and Languages for Microplastics, Tire Wear Particles, Engineered Nanoparticles and Advanced Materials

Author

Listed:
  • Merve Tunali

    (Empa, Swiss Federal Laboratories for Materials Science and Technology, Technology and Society Laboratory, Lerchenfeldstrasse 5, 9014 Sankt Gallen, Switzerland)

  • Hyunjoo Hong

    (Empa, Swiss Federal Laboratories for Materials Science and Technology, Technology and Society Laboratory, Lerchenfeldstrasse 5, 9014 Sankt Gallen, Switzerland)

  • Luis Mauricio Ortiz-Galvez

    (Empa, Swiss Federal Laboratories for Materials Science and Technology, Technology and Society Laboratory, Lerchenfeldstrasse 5, 9014 Sankt Gallen, Switzerland)

  • Jimeng Wu

    (Empa, Swiss Federal Laboratories for Materials Science and Technology, Technology and Society Laboratory, Lerchenfeldstrasse 5, 9014 Sankt Gallen, Switzerland)

  • Yiwen Zhang

    (Empa, Swiss Federal Laboratories for Materials Science and Technology, Technology and Society Laboratory, Lerchenfeldstrasse 5, 9014 Sankt Gallen, Switzerland)

  • David Mennekes

    (Empa, Swiss Federal Laboratories for Materials Science and Technology, Technology and Society Laboratory, Lerchenfeldstrasse 5, 9014 Sankt Gallen, Switzerland)

  • Barbora Pinlova

    (Empa, Swiss Federal Laboratories for Materials Science and Technology, Technology and Society Laboratory, Lerchenfeldstrasse 5, 9014 Sankt Gallen, Switzerland)

  • Danyang Jiang

    (Empa, Swiss Federal Laboratories for Materials Science and Technology, Technology and Society Laboratory, Lerchenfeldstrasse 5, 9014 Sankt Gallen, Switzerland)

  • Claudia Som

    (Empa, Swiss Federal Laboratories for Materials Science and Technology, Technology and Society Laboratory, Lerchenfeldstrasse 5, 9014 Sankt Gallen, Switzerland)

  • Bernd Nowack

    (Empa, Swiss Federal Laboratories for Materials Science and Technology, Technology and Society Laboratory, Lerchenfeldstrasse 5, 9014 Sankt Gallen, Switzerland)

Abstract

Artificial intelligence gained a surge in popularity through the release of conversational artificial intelligence tools, which enable individuals to use the technology without any prior knowledge or expertise in computational science. Researchers, content writers, as well as curious minds may use these tools to investigate any topics in question. Environmental topics, as one of the current public concerns, are covered by many different kinds of media, indicating a broad public interest. To assess the possibility of using these tools in environmental-related content writing or research, we tested the capabilities of conversational artificial intelligence tools on selected environmental topics. In particular, we tested different tools (ChatGPT, Microsoft Bing, Google Bard) and different languages (English, Spanish, Korean, German, Turkish and Chinese) via using selected questions and compared the answers with each other. Our results suggest that conversational artificial intelligence tools may provide satisfactory and comprehensive answers; however, we found some of the statements debatable and texts still need to be reviewed by an expert. Selected tools may offer specific advantages, such as providing references, although certain issues may need to be checked for each tool. The usage of different languages may provide additional points within the content; however, this does not necessarily imply that these new facets arise solely from utilizing different languages, since new aspects may also be attributed to the ‘randomness of the generated answers’. We suggest asking the same question several times as the tools mostly generate random answers each time, especially for ChatGPT, to obtain a more comprehensive content.

Suggested Citation

  • Merve Tunali & Hyunjoo Hong & Luis Mauricio Ortiz-Galvez & Jimeng Wu & Yiwen Zhang & David Mennekes & Barbora Pinlova & Danyang Jiang & Claudia Som & Bernd Nowack, 2023. "Conversational AI Tools for Environmental Topics: A Comparative Analysis of Different Tools and Languages for Microplastics, Tire Wear Particles, Engineered Nanoparticles and Advanced Materials," Sustainability, MDPI, vol. 15(19), pages 1-16, October.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:19:p:14453-:d:1253039
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/19/14453/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/19/14453/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Eva A. M. van Dis & Johan Bollen & Willem Zuidema & Robert van Rooij & Claudi L. Bockting, 2023. "ChatGPT: five priorities for research," Nature, Nature, vol. 614(7947), pages 224-226, February.
    2. Martin Mullins & Martin Himly & Isabel Rodríguez Llopis & Irini Furxhi & Sabine Hofer & Norbert Hofstätter & Peter Wick & Daina Romeo & Dana Küehnel & Kirsi Siivola & Julia Catalán & Kerstin Hund-Rink, 2023. "(Re)Conceptualizing decision-making tools in a risk governance framework for emerging technologies—the case of nanomaterials," Environment Systems and Decisions, Springer, vol. 43(1), pages 3-15, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ghio, Alessandro, 2024. "Democratizing academic research with Artificial Intelligence: The misleading case of language," CRITICAL PERSPECTIVES ON ACCOUNTING, Elsevier, vol. 98(C).
    2. Evangelos Katsamakas & Oleg V. Pavlov & Ryan Saklad, 2024. "Artificial intelligence and the transformation of higher education institutions," Papers 2402.08143, arXiv.org.
    3. Alin ZAMFIROIU & Denisa VASILE & Daniel SAVU, 2023. "ChatGPT – A Systematic Review of Published Research Papers," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 27(1), pages 5-16.
    4. Shahad Al-Khalifa & Fatima Alhumaidhi & Hind Alotaibi & Hend S. Al-Khalifa, 2023. "ChatGPT across Arabic Twitter: A Study of Topics, Sentiments, and Sarcasm," Data, MDPI, vol. 8(11), pages 1-19, November.
    5. Roberto Araya, 2023. "Connecting Classrooms with Online Interclass Tournaments: A Strategy to Imitate, Recombine and Innovate Teaching Practices," Sustainability, MDPI, vol. 15(10), pages 1-25, May.
    6. Ching-Sheng Lin & Chung-Nan Tsai & Shao-Tang Su & Jung-Sing Jwo & Cheng-Hsiung Lee & Xin Wang, 2023. "Predictive Prompts with Joint Training of Large Language Models for Explainable Recommendation," Mathematics, MDPI, vol. 11(20), pages 1-12, October.
    7. Nuortimo, Kalle & Harkonen, Janne & Breznik, Kristijan, 2024. "Global, regional, and local acceptance of solar power," Renewable and Sustainable Energy Reviews, Elsevier, vol. 193(C).
    8. Ali, Omar & Murray, Peter A. & Momin, Mujtaba & Dwivedi, Yogesh K. & Malik, Tegwen, 2024. "The effects of artificial intelligence applications in educational settings: Challenges and strategies," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
    9. Peres, Renana & Schreier, Martin & Schweidel, David & Sorescu, Alina, 2023. "On ChatGPT and beyond: How generative artificial intelligence may affect research, teaching, and practice," International Journal of Research in Marketing, Elsevier, vol. 40(2), pages 269-275.
    10. Evangelos Katsamakas & Oleg V. Pavlov & Ryan Saklad, 2024. "Artificial Intelligence and the Transformation of Higher Education Institutions: A Systems Approach," Sustainability, MDPI, vol. 16(14), pages 1-22, July.
    11. Fabio Motoki & Valdemar Pinho Neto & Victor Rodrigues, 2024. "More human than human: measuring ChatGPT political bias," Public Choice, Springer, vol. 198(1), pages 3-23, January.
    12. Herhausen, Dennis & Bernritter, Stefan F. & Ngai, Eric W.T. & Kumar, Ajay & Delen, Dursun, 2024. "Machine learning in marketing: Recent progress and future research directions," Journal of Business Research, Elsevier, vol. 170(C).
    13. Chiarello, Filippo & Giordano, Vito & Spada, Irene & Barandoni, Simone & Fantoni, Gualtiero, 2024. "Future applications of generative large language models: A data-driven case study on ChatGPT," Technovation, Elsevier, vol. 133(C).
    14. Feng, Jianghong & Ning, Yu & Wang, Zhaohua & Li, Guo & Xiu Xu, Su, 2024. "ChatGPT-enabled two-stage auctions for electric vehicle battery recycling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 183(C).
    15. Yanwei You & Yuquan Chen & Yujun You & Qi Zhang & Qiang Cao, 2023. "Evolutionary Game Analysis of Artificial Intelligence Such as the Generative Pre-Trained Transformer in Future Education," Sustainability, MDPI, vol. 15(12), pages 1-12, June.
    16. Roslyn Cameron & Heinz Herrmann & Alan Nankervis, 2024. "Mapping the evolution of algorithmic HRM (AHRM): a multidisciplinary synthesis," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    17. Christopher J. Lynch & Erik J. Jensen & Virginia Zamponi & Kevin O’Brien & Erika Frydenlund & Ross Gore, 2023. "A Structured Narrative Prompt for Prompting Narratives from Large Language Models: Sentiment Assessment of ChatGPT-Generated Narratives and Real Tweets," Future Internet, MDPI, vol. 15(12), pages 1-36, November.
    18. Ma, Xiaoyue & Huo, Yudi, 2023. "Are users willing to embrace ChatGPT? Exploring the factors on the acceptance of chatbots from the perspective of AIDUA framework," Technology in Society, Elsevier, vol. 75(C).
    19. Giordano, Vito & Spada, Irene & Chiarello, Filippo & Fantoni, Gualtiero, 2024. "The impact of ChatGPT on human skills: A quantitative study on twitter data," Technological Forecasting and Social Change, Elsevier, vol. 203(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:19:p:14453-:d:1253039. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.