IDEAS home Printed from https://ideas.repec.org/a/nat/natsus/v8y2025i2d10.1038_s41893-024-01489-2.html
   My bibliography  Save this article

Leveraging the collaborative power of AI and citizen science for sustainable development

Author

Listed:
  • Dilek Fraisl

    (International Institute for Applied Systems Analysis (IIASA)
    Citizen Science Global Partnership (CSGP))

  • Linda See

    (International Institute for Applied Systems Analysis (IIASA))

  • Steffen Fritz

    (International Institute for Applied Systems Analysis (IIASA)
    Citizen Science Global Partnership (CSGP))

  • Mordechai Haklay

    (University College London (UCL)
    Learning Planet Institute)

  • Ian McCallum

    (International Institute for Applied Systems Analysis (IIASA))

Abstract

Both artificial intelligence (AI) and citizen science hold immense potential for addressing major sustainability challenges from health to climate change. Alongside their individual benefits, when combined, they offer considerable synergies that can aid in both better monitoring of, and achieving, sustainable development. While AI has already been integrated into citizen science projects such as through automated classification and identification, the integration of citizen science approaches into AI is lacking. This integration has, however, the potential to address some of the major challenges associated with AI such as social bias, which could accelerate progress towards achieving sustainable development.

Suggested Citation

  • Dilek Fraisl & Linda See & Steffen Fritz & Mordechai Haklay & Ian McCallum, 2025. "Leveraging the collaborative power of AI and citizen science for sustainable development," Nature Sustainability, Nature, vol. 8(2), pages 125-132, February.
  • Handle: RePEc:nat:natsus:v:8:y:2025:i:2:d:10.1038_s41893-024-01489-2
    DOI: 10.1038/s41893-024-01489-2
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41893-024-01489-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1038/s41893-024-01489-2?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. Steffen Fritz & Linda See & Tyler Carlson & Mordechai (Muki) Haklay & Jessie L. Oliver & Dilek Fraisl & Rosy Mondardini & Martin Brocklehurst & Lea A. Shanley & Sven Schade & Uta Wehn & Tommaso Abrate, 2019. "Citizen science and the United Nations Sustainable Development Goals," Nature Sustainability, Nature, vol. 2(10), pages 922-930, October.
    2. Christian Janiesch & Patrick Zschech & Kai Heinrich, 2021. "Machine learning and deep learning," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(3), pages 685-695, September.
    3. Peng Xu & Geng Li & Yi Zheng & Jimmy C. H. Fung & Anping Chen & Zhenzhong Zeng & Huizhong Shen & Min Hu & Jiafu Mao & Yan Zheng & Xiaoqing Cui & Zhilin Guo & Yilin Chen & Lian Feng & Shaokun He & Xugu, 2024. "Fertilizer management for global ammonia emission reduction," Nature, Nature, vol. 626(8000), pages 792-798, February.
    4. Sarita Albagli & Allan Yu Iwama, 2022. "Citizen science and the right to research: building local knowledge of climate change impacts," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-13, December.
    5. Maryam Lotfian & Jens Ingensand & Maria Antonia Brovelli, 2021. "The Partnership of Citizen Science and Machine Learning: Benefits, Risks, and Future Challenges for Engagement, Data Collection, and Data Quality," Sustainability, MDPI, vol. 13(14), pages 1-19, July.
    6. Ricardo Vinuesa & Hossein Azizpour & Iolanda Leite & Madeline Balaam & Virginia Dignum & Sami Domisch & Anna Felländer & Simone Daniela Langhans & Max Tegmark & Francesco Fuso Nerini, 2020. "The role of artificial intelligence in achieving the Sustainable Development Goals," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    7. Rachel Adams & Ayantola Alayande & Zameer Brey & Brantley Browning & Michael Gastrow & Jerry John Kponyo & Dona Mathew & Moremi Nkosi & Henry Nunoo-Mensah & Diana Nyakundi & Victor Odumuyiwa & Olubunm, 2023. "A new research agenda for African generative AI," Nature Human Behaviour, Nature, vol. 7(11), pages 1839-1841, November.
    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. Jen-Yu Lee & Tien-Thinh Nguyen & Hong-Giang Nguyen & Jen-Yao Lee, 2022. "Towards Predictive Crude Oil Purchase: A Case Study in the USA and Europe," Energies, MDPI, vol. 15(11), pages 1-15, May.
    2. Henrik Skaug Sætra, 2021. "AI in Context and the Sustainable Development Goals: Factoring in the Unsustainability of the Sociotechnical System," Sustainability, MDPI, vol. 13(4), pages 1-19, February.
    3. Mostafa Bigdeli & Mahsa Akbari, 2024. "Machine-learning-based Classification of Customers’ Behavioural Model in Instagram," Paradigm, , vol. 28(2), pages 223-240, December.
    4. Xi Liu & Yugang He & Renhong Wu, 2024. "Revolutionizing Environmental Sustainability: The Role of Renewable Energy Consumption and Environmental Technologies in OECD Countries," Energies, MDPI, vol. 17(2), pages 1-21, January.
    5. Eduard Hartwich & Alexander Rieger & Johannes Sedlmeir & Dominik Jurek & Gilbert Fridgen, 2023. "Machine economies," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-13, December.
    6. Jinyi Li & Zhen Liu & Guizhong Han & Peter Demian & Mohamed Osmani, 2024. "The Relationship Between Artificial Intelligence (AI) and Building Information Modeling (BIM) Technologies for Sustainable Building in the Context of Smart Cities," Sustainability, MDPI, vol. 16(24), pages 1-38, December.
    7. Gianluca MISURACA & Colin van Noordt, 2020. "AI Watch - Artificial Intelligence in public services: Overview of the use and impact of AI in public services in the EU," JRC Research Reports JRC120399, Joint Research Centre.
    8. Martins, Flavio Pinheiro & De-León Almaraz, Sofía & Botelho Junior, Amilton Barbosa & Azzaro-Pantel, Catherine & Parikh, Priti, 2024. "Hydrogen and the sustainable development goals: Synergies and trade-offs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 204(C).
    9. Najla Alharbi & Bashayer Alkalifah & Ghaida Alqarawi & Murad A. Rassam, 2024. "Countering Social Media Cybercrime Using Deep Learning: Instagram Fake Accounts Detection," Future Internet, MDPI, vol. 16(10), pages 1-22, October.
    10. Rui Ma & Jia Wang & Wei Zhao & Hongjie Guo & Dongnan Dai & Yuliang Yun & Li Li & Fengqi Hao & Jinqiang Bai & Dexin Ma, 2022. "Identification of Maize Seed Varieties Using MobileNetV2 with Improved Attention Mechanism CBAM," Agriculture, MDPI, vol. 13(1), pages 1-16, December.
    11. Fabian Dvorak & Regina Stumpf & Sebastian Fehrler & Urs Fischbacher, 2024. "Generative AI Triggers Welfare-Reducing Decisions in Humans," Papers 2401.12773, arXiv.org.
    12. Sergio Genovesi & Julia Maria Mönig, 2022. "Acknowledging Sustainability in the Framework of Ethical Certification for AI," Sustainability, MDPI, vol. 14(7), pages 1-10, March.
    13. Tan Yigitcanlar & Rashid Mehmood & Juan M. Corchado, 2021. "Green Artificial Intelligence: Towards an Efficient, Sustainable and Equitable Technology for Smart Cities and Futures," Sustainability, MDPI, vol. 13(16), pages 1-14, August.
    14. Wang, Weilong & Xiao, Deheng & Wang, Jianlong & Wu, Haitao, 2024. "The cost of pollution in the digital era: Impediments of air pollution on enterprise digital transformation," Energy Economics, Elsevier, vol. 134(C).
    15. Kim, Myung Ja & Hall, C. Michael & Kwon, Ohbyung & Sohn, Kwonsang, 2024. "Space tourism: Value-attitude-behavior theory, artificial intelligence, and sustainability," Journal of Retailing and Consumer Services, Elsevier, vol. 77(C).
    16. ODEH, Joseph PhD, 2024. "Exploring AI Applications to Foster Healthy Shopping Habits in Nigerian Retail," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 8(3s), pages 5382-5393, November.
    17. Dylan Norbert Gono & Herlina Napitupulu & Firdaniza, 2023. "Silver Price Forecasting Using Extreme Gradient Boosting (XGBoost) Method," Mathematics, MDPI, vol. 11(18), pages 1-15, September.
    18. Ricardo Vinuesa & Soledad Le Clainche, 2022. "Machine-Learning Methods for Complex Flows," Energies, MDPI, vol. 15(4), pages 1-5, February.
    19. Qian, Yu & Xu, Zeshui & Qin, Yong & Gou, Xunjie & Skare, Marinko, 2023. "Measuring the varying relationships between sustainable development and oil booms in different contexts: An empirical study," Resources Policy, Elsevier, vol. 85(PB).
    20. Krzysztof Rusek & Agnieszka Kleszcz & Albert Cabellos-Aparicio, 2022. "Bayesian inference of spatial and temporal relations in AI patents for EU countries," Papers 2201.07168, arXiv.org.

    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:nat:natsus:v:8:y:2025:i:2:d:10.1038_s41893-024-01489-2. 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: http://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.