Fostering the ethical use of Artificial Intelligence in the Geosciences

A set of practical and actionable recommendations for the ethical application of Artificial Intelligence (AI) in the geosciences is presented by the Task Group on AI Ethics in Geosciences under the IUGS Commission on Geoethics. While geoscientists have long used statistical and machine learning methods, the rapid adoption of frontier and generative AI introduces amplified risks alongside opportunities for scientific discovery and productivity. AI holds immense potential to support the UN Sustainable Development Goals (SDGs), for example by predicting natural resource locations, enhancing understanding of deep geological time, and assisting with natural hazard prediction such as earthquakes and landslides.

However, the rapid development and deployment of AI, combined with high-profile ethical concerns, demands clear, actionable guidance. Current high-level ethical frameworks, such as those from UNESCO, lack the practical detail needed for implementation in the geosciences. This report addresses that gap by providing guidance for academic, industry, governmental, and non-governmental geoscientists, society leaders, and policymakers.

The methodology adopted a robust approach informed by Critical Realism—encouraging attention to hidden structures and power dynamics—and Virtue Ethics—focusing on the character of a “good and wise geoscientist.” The investigation combined a literature review, longitudinal analysis of deployed AI systems, and counterfactual future thinking, all triangulated against the UNESCO Recommendations on AI Ethics and the International Science Council (ISC) AI Analytical Framework.

Eight key themes were identified to address current and anticipated ethical challenges in the geosciences. These recommendations aim to foster a responsible, just, and sustainable integration of AI that serves the public good and upholds scientific integrity:

• Use AI Responsibly: Treat AI as a tool to support, not replace, geoscientist judgment, avoiding fully autonomous decisions that impact people or ecosystems.
• Promote Transparency and Explainability: Ensure research is open, traceable, and reproducible, with clear disclosure of data sources, limitations, and uncertainties, particularly for “black box” models.
• Consider Bias and Fairness: Use diverse, representative datasets and actively address biases that could affect marginalized or Indigenous communities.
• Obtain Informed Consent and Protect Personal Data: Explicit consent is required for AI training data, and a privacy-by-design approach should be applied, especially for sensitive information.
• Practice Participatory Design and Community Engagement: Engage meaningfully with communities affected by AI outputs, following the principle “Nothing about us without us.”
• Advocate for Environmental Protection: Weigh the environmental costs of AI (energy, water, e-waste) against its scientific benefits, promoting sustainable practices such as energy-efficient algorithms.
• Integrity in Science, Publishing, and Education: Disclose AI use in research, verify AI-generated assertions, and ensure AI does not undermine critical thinking or scientific honesty.
• Consider Geopolitics: International institutions should remain neutral, avoiding endorsement of cloud platforms that centralize data and risk eroding data sovereignty or reinforcing inequities (“algorithmic colonization”).

The report (https://www.geoethics.org/_files/ugd/5195a5_5dcf66f87cca492c958319c3f4cdeffb.pdf) proposes a high-level roadmap for continuous improvement, including practical ethical impact and risk assessments. These recommendations serve as a call to action to safeguard geosciences and ensure responsible stewardship of the Earth.