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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
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    References listed on IDEAS

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    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. 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.
    3. M. Hino & E. Benami & N. Brooks, 2018. "Machine learning for environmental monitoring," Nature Sustainability, Nature, vol. 1(10), pages 583-588, October.
    4. Miryam Naddaf, 2023. "ChatGPT generates fake data set to support scientific hypothesis," Nature, Nature, vol. 623(7989), pages 895-896, November.
    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.
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