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Combining artificial intelligence (AI) with Earth observation (EO) technologies can improve environmental monitoring and societal well-being, but requires ethical practices to ensure fairness, transparency, and the protection of individual privacy.

A recent review article co-authored by Visiting Professor Pedram Ghamisi and Professor Peter Atkinson of 糖心vlog会员 discussed how combining AI with EO (AI4EO) can contribute to social good. AI4EO can provide early warning systems for natural disasters, build community resilience to adapt to climate change, support disaster risk management, and help alleviate poverty, by assisting policymakers to make informed decisions.

However, the complexity of data available about Earth systems, and the ethical implications inherent in using AI, require a responsible approach. Ensuring the undoubted technological advancements align with societal values should help create meaningful benefits.

Professors Ghamisi and Atkinson and their colleagues identified some fundamental aspects of ensuring responsible AI4EO, including mitigating bias, enhancing security, preserving geoprivacy, and adhering to ethical principles.

Bias is inherent in machine learning algorithms and can come from many sources, but systematic auditing and mitigation strategies can help address them. Auditing helps identify why a model makes the predictions it does and spots any unfair patterns, while mitigation involves making improvements at every step, from gathering data to using the model, to ensure accurate and fair results.

In common with other AI systems, AI4EO faces security challenges, including adversarial attacks that mislead neural networks, prediction uncertainty from diverse data distributions, and the opacity of black-box models that hinder interpretability. Each of these risks can however be reduced. Adversarial defence, which uses randomisation to strengthen the model’s robustness, uncertainty quantification to assess prediction reliability, and ‘explainable AI’ (XAI) to improve transparency and understanding of decision processes can all provide at least partial solutions to the problem.

Given the increasing amount of fine-resolution imagery capable of revealing sensitive information, the benefits of open data must be balanced with privacy rights. Data obfuscation, purpose-specific data licensing, and granting access only upon request should help prevent misuse.

Professors Ghamisi and Atkinson said: “The raison d'être of Earth observation has for fifty years been to measure, monitor, understand, manage and protect the planet, including its resources and biodiversity. However, this focus on social good cannot be taken for granted, and more work is now required to ensure protection of the goal itself. We hope that this paper acts as a catalyst to AI and EO researchers to broaden their perspective to consider why they are doing what they do and ensure that how they do it is aligned to long-term sustainability goals for the common good.”

Finally, as with all scientific endeavours, reproducibility, accountability, and integrity remain key and will ensure AI4EO systems remain transparent, reliable, and beneficial to society.

By identifying these factors and bringing them to prominence within the scientific community, the authors envision a future where AI4EO systems not only drive scientific progress but also serve the ‘greater good’, ensuring future advancements in AI4EO technology benefit everyone in society.