AI assists in biodiversity conservation, ecosystem monitoring, and sustainable land management through data-driven insights and predictive analytics. In this chart we see the countries with a hight number of threatened plant species over time.

This perspective offers a real-time view of the worldwide news on life above water-related topics, providing us with a media perspective on the progress at the different fronts of SDG 15.

A SDG Live Report is what it is all about! Here, you can have a real-time perspective of the state of the world in regard to AI and sustainability, tracking some of the main issues to address in the near future.

AI has significantly impacted the progress of Sustainable Development Goal 15 (SDG 15), which focuses on protecting, restoring, and promoting sustainable use of terrestrial ecosystems, managing forests sustainably, combating desertification, halting and reversing land degradation, and halting biodiversity loss. Between 2015 and 2023, there have been 203,592 scientific publications exploring the role of AI in these areas. These studies highlight AI’s potential to monitor and manage natural resources more efficiently, analyze vast datasets for biodiversity conservation, and develop strategies to combat land degradation. AI technologies, such as remote sensing and machine learning, are used to track deforestation, assess ecosystem health, and predict the impacts of climate change on terrestrial habitats. Despite relatively low media exposure, with only 3,156 news articles, there is growing awareness of AI’s potential in environmental conservation. Furthermore, the development of 190 AI policies targeting SDG 15 demonstrates a commitment from policymakers to integrate AI into ecosystem management and conservation efforts, ensuring sustainable and resilient terrestrial ecosystems.

Looking ahead, the next 5 to 10 years are expected to see significant advancements in AI applications for terrestrial ecosystem management. AI-driven remote sensing technologies will become more sophisticated, allowing for real-time monitoring of forests and other critical habitats, enhancing efforts to combat illegal logging and poaching. Machine learning algorithms will be increasingly used to analyze complex ecological data, providing insights into species distribution, habitat connectivity, and the impacts of human activities on biodiversity. These advancements will facilitate more effective conservation planning and policy-making. Additionally, AI can support reforestation and land restoration projects by optimizing the selection of plant species and monitoring the progress of restoration efforts. As AI technologies continue to evolve, collaboration between governments, conservation organizations, and the private sector will be essential to ensure that AI-driven innovations are implemented ethically and effectively. This collaborative effort will accelerate progress towards SDG 15, promoting the sustainable use and restoration of terrestrial ecosystems and biodiversity conservation.

Here is your window to how AI is impacting above water life worldwide. This dashboard is configurable and can be integrated into other systems to bring actionable technology into the systems of research institutions, governments and enterprises that are willing to make a difference.

 

BIAS BOARD

Avoiding data bias in AI systems is crucial to ensure fair, accurate, and equitable outcomes, preventing the reinforcement of existing inequalities and enabling more trustworthy and inclusive technologies. Here you will see a dashboard analysing the bias related to the data ingested in this observatory for SDG 15.