On December 16, 2024, researchers from the International Institute for Applied Systems Analysis (IIASA) published a perspective piece in Nature Sustainability discussing the integration of citizen science and artificial intelligence (AI) to enhance monitoring of the United Nations Sustainable Development Goals (SDGs).
The SDGs, established in 2015, aim to address global sustainability challenges by 2030. However, significant data gaps hinder progress; nearly half of the 92 environmental indicators lack sufficient data, and only 15% of targets are on track. Issues such as poor data quality and limited sharing complicate targeted interventions.
The IIASA study emphasizes how citizen science can fill these data gaps by enabling public participation in scientific research, particularly for SDGs related to health, sustainable cities, and biodiversity. Despite interest from the UN and national agencies, challenges remain in integrating citizen science data into SDG monitoring.
Advancements in AI present opportunities to support sustainable development by rapidly analyzing large datasets and improving data accessibility. However, AI also poses risks, including biases that can lead to inaccurate results. The authors advocate for using citizen science to provide localized data, enhancing AI's effectiveness.
Dilek Fraisl, lead author, noted that AI's reliability depends on the quality of training data. Addressing biases is crucial for accurate AI outcomes. The recent Global Digital Compact adopted by the UN underscores the importance of global cooperation in AI governance, highlighting both its potential benefits and risks to human rights.
Fraisl concluded that the synergy between citizen science and AI could significantly advance SDG monitoring, provided that inclusivity and governance are prioritized.