IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v11y2024i1d10.1057_s41599-024-02720-3.html
   My bibliography  Save this article

AI chatbots contribute to global conservation injustices

Author

Listed:
  • Danilo Urzedo

    (CSIRO – Environment Business Unit, EcoSciences Precinct)

  • Zarrin Tasnim Sworna

    (CSIRO – Environment Business Unit, EcoSciences Precinct)

  • Andrew J. Hoskins

    (CSIRO – Environment Business Unit, Australian Tropical Sciences and Innovation Precinct)

  • Cathy J. Robinson

    (CSIRO – Environment Business Unit, EcoSciences Precinct
    Northern Institute, Charles Darwin University)

Abstract

Artificial Intelligence (AI)-driven language models (chatbots) progressively accelerate the collection and translation of environmental evidence that could be used to inform planetary conservation plans and strategies. Yet, the consequences of chatbot-generated conservation content have never been globally assessed. Drawing on distributive, recognition, procedural, and epistemic dimensions of environmental justice, we interviewed and analysed 30,000 responses from ChatGPT on ecological restoration expertise, stakeholder engagements, and techniques. Our results show that more than two-thirds of the chatbot’s answers rely on the expertise of male academics working at universities in the United States, while largely ignoring evidence from low- and lower-middle-income countries (7%) and Indigenous and community restoration experiences (2%). A focus on planting and reforestation techniques (69%) underpins optimistic environmental outcomes (60%), neglecting holistic technical approaches that consider non-forest ecosystems (25%) and non-tree species (8%). This analysis highlights how biases in AI-driven knowledge production can reinforce Western science, overlooking diverse sources of expertise and perspectives regarding conservation research and practices. In the fast-paced domain of generative AI, safeguard mechanisms are needed to ensure that these expanding chatbot developments can incorporate just principles in addressing the pace and scale of the worldwide environmental crisis.

Suggested Citation

  • Danilo Urzedo & Zarrin Tasnim Sworna & Andrew J. Hoskins & Cathy J. Robinson, 2024. "AI chatbots contribute to global conservation injustices," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-8, December.
    • Handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-02720-3
    DOI: 10.1057/s41599-024-02720-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41599-024-02720-3
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/s41599-024-02720-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Forrest Fleischman & Eric Coleman & Harry Fischer & Prakash Kashwan & Marion Pfeifer & Vijay Ramprasad & Claudia Rodriguez Solorzano & Joseph W. Veldman, 2022. "Restoration prioritization must be informed by marginalized people," Nature, Nature, vol. 607(7918), pages 5-6, July.
    2. Miryam Naddaf, 2023. "ChatGPT generates fake data set to support scientific hypothesis," Nature, Nature, vol. 623(7989), pages 895-896, November.
    3. Rebecca K. Runting & Stuart Phinn & Zunyi Xie & Oscar Venter & James E. M. Watson, 2020. "Opportunities for big data in conservation and sustainability," Nature Communications, Nature, vol. 11(1), pages 1-4, December.
    4. M. Hino & E. Benami & N. Brooks, 2018. "Machine learning for environmental monitoring," Nature Sustainability, Nature, vol. 1(10), pages 583-588, October.
    5. Lynn H. Kaack & Priya L. Donti & Emma Strubell & George Kamiya & Felix Creutzig & David Rolnick, 2022. "Aligning artificial intelligence with climate change mitigation," Nature Climate Change, Nature, vol. 12(6), pages 518-527, June.
    6. Roberta Kwok, 2019. "AI empowers conservation biology," Nature, Nature, vol. 567(7746), pages 133-134, March.
    7. Andrea Gaggioli, 2023. "Ethics: disclose use of AI in scientific manuscripts," Nature, Nature, vol. 614(7948), pages 413-413, February.
    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. Fábio Grigoletto & Fernanda Antunes de Oliveira & Caio Caradi Momesso & Ibrahim Kamel Rodrigues Nehemy & João Emílio de Almeida Junior & Vinícius de Avelar São Pedro & Roberto Greco & Mário Aquino Alv, 2023. "Technological Affordance and the Realities of Citizen Science Projects Developed in Challenging Territories," Sustainability, MDPI, vol. 15(8), pages 1-15, April.
    2. Michael J. Weir & Thomas W. Sproul, 2019. "Identifying Drivers of Genetically Modified Seafood Demand: Evidence from a Choice Experiment," Sustainability, MDPI, vol. 11(14), pages 1-21, July.
    3. Evgeny Burnaev & Evgeny Mironov & Aleksei Shpilman & Maxim Mironenko & Dmitry Katalevsky, 2023. "Practical AI Cases for Solving ESG Challenges," Sustainability, MDPI, vol. 15(17), pages 1-15, August.
    4. Galaz, Victor & Centeno, Miguel A. & Callahan, Peter W. & Causevic, Amar & Patterson, Thayer & Brass, Irina & Baum, Seth & Farber, Darryl & Fischer, Joern & Garcia, David & McPhearson, Timon & Jimenez, 2021. "Artificial intelligence, systemic risks, and sustainability," Technology in Society, Elsevier, vol. 67(C).
    5. Yi Bao & Zhou Huang & Han Wang & Ganmin Yin & Xiao Zhou & Yong Gao, 2023. "High‐resolution quantification of building stock using multi‐source remote sensing imagery and deep learning," Journal of Industrial Ecology, Yale University, vol. 27(1), pages 350-361, February.
    6. Leal Filho, Walter & Wall, Tony & Rui Mucova, Serafino Afonso & Nagy, Gustavo J. & Balogun, Abdul-Lateef & Luetz, Johannes M. & Ng, Artie W. & Kovaleva, Marina & Safiul Azam, Fardous Mohammad & Alves,, 2022. "Deploying artificial intelligence for climate change adaptation," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    7. Anne-Laure Ligozat & Julien Lefevre & Aurélie Bugeau & Jacques Combaz, 2022. "Unraveling the Hidden Environmental Impacts of AI Solutions for Environment Life Cycle Assessment of AI Solutions," Sustainability, MDPI, vol. 14(9), pages 1-14, April.
    8. Yiwen Zeng & Rebecca K. Runting & James E. M. Watson & Luis Roman Carrasco, 2022. "Telecoupled environmental impacts are an obstacle to meeting the sustainable development goals," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(1), pages 76-82, February.
    9. Fernando Garrigós-Simón & Silvia Sanz-Blas & Yeamduan Narangajavana & Daniela Buzova, 2021. "The Nexus between Big Data and Sustainability: An Analysis of Current Trends and Developments," Sustainability, MDPI, vol. 13(12), pages 1, June.
    10. Behnam Zakeri & Katsia Paulavets & Leonardo Barreto-Gomez & Luis Gomez Echeverri & Shonali Pachauri & Benigna Boza-Kiss & Caroline Zimm & Joeri Rogelj & Felix Creutzig & Diana Ürge-Vorsatz & David G. , 2022. "Pandemic, War, and Global Energy Transitions," Energies, MDPI, vol. 15(17), pages 1-23, August.
    11. Kimberly R. Hall & Ranjan Anantharaman & Vincent A. Landau & Melissa Clark & Brett G. Dickson & Aaron Jones & Jim Platt & Alan Edelman & Viral B. Shah, 2021. "Circuitscape in Julia: Empowering Dynamic Approaches to Connectivity Assessment," Land, MDPI, vol. 10(3), pages 1-24, March.
    12. Puertas, Rosa & Guaita-Martinez, José M. & Marti, Luisa, 2023. "Analysis of the impact of university policies on society's environmental perception," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
    13. Frederico M. Bublitz & Arlene Oetomo & Kirti S. Sahu & Amethyst Kuang & Laura X. Fadrique & Pedro E. Velmovitsky & Raphael M. Nobrega & Plinio P. Morita, 2019. "Disruptive Technologies for Environment and Health Research: An Overview of Artificial Intelligence, Blockchain, and Internet of Things," IJERPH, MDPI, vol. 16(20), pages 1-24, October.
    14. Shivam Gupta & Jazmin Campos Zeballos & Gema del Río Castro & Ana Tomičić & Sergio Andrés Morales & Maya Mahfouz & Isimemen Osemwegie & Vicky Phemia Comlan Sessi & Marina Schmitz & Nady Mahmoud & Mnen, 2023. "Operationalizing Digitainability: Encouraging Mindfulness to Harness the Power of Digitalization for Sustainable Development," Sustainability, MDPI, vol. 15(8), pages 1-37, April.
    15. Molly E. Brown, 2021. "Metrics to Accelerate Private Sector Investment in Sustainable Development Goal 2—Zero Hunger," Sustainability, MDPI, vol. 13(11), pages 1-6, May.
    16. Juan Carlos Perdomo, 2023. "The Relative Value of Prediction in Algorithmic Decision Making," Papers 2312.08511, arXiv.org.
    17. Takahiro Kubo & Saeko Terada & Shinya URYU & Taro Mieno & Diogo Veríssimo, 2023. "Authors’ response to Unjournal evaluations of "Banning wildlife trade can boost demand for unregulated threatened species"," The Unjournal Evaluations 2023-63, The Unjournal.
    18. Max Ajl, 2023. "Peripheral Labour and Accumulation on a World Scale in the Green Transitions," Social Sciences, MDPI, vol. 12(5), pages 1-10, May.
    19. Qahtan, Talal F. & Alade, Ibrahim O. & Rahaman, Md Safiqur & Saleh, Tawfik A., 2023. "Mapping the research landscape of hydrogen production through electrocatalysis: A decade of progress and key trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    20. Diane A. Isabelle & Mika Westerlund, 2022. "A Review and Categorization of Artificial Intelligence-Based Opportunities in Wildlife, Ocean and Land Conservation," Sustainability, MDPI, vol. 14(4), pages 1-22, February.

    More about this item

    Statistics

    Access and download statistics

    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:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-02720-3. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: https://www.nature.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.