Futuring the forests
The rainforests of South America, despite their immense ecological importance, are increasingly under threat from illegal logging and other destructive activities. Monitoring these vast and remote areas poses a significant challenge. While satellite surveillance offers some capability, it has notable limitations, and on-the-ground patrols are inherently constrained by the sheer size and inaccessibility of the terrain. Enter the drones: equipped with advanced cameras and motion sensors, they provide a game-changing solution. These aerial devices silently navigate through the forest canopy, detecting even the faintest signs of illegal activities. By integrating Artificial Intelligence (AI), data collected by drones can be analysed within seconds, delivering real-time reports of emerging threats, such as new logging roads, and enabling rapid responses to address these issues before they escalate.
AI’s full potential emerges when combined with human expertise.
For instance, in the Peruvian Amazon, Indigenous activists utilise a tailored version of MapBuilder software to meticulously document the state of their forest territories. This system merges satellite data with observations from local patrols, producing a comprehensive and undeniable record of threats. As advocacy group Global Forest Watch notes, this approach "transforms abstract threats into tangible realities that can be addressed and acted upon." Indigenous leader Ranin Koshi succinctly underscores the transformative power of technology: “Technology allows us to reaffirm and guarantee our rights for our future generations.” This collaboration between technology and traditional knowledge exemplifies a forward-looking strategy for forest conservation.
AI’s ability to process and present vast amounts of information can be used to educate the public about environmental challenges and solutions. For example, real-time data visualisations of deforestation or wildlife migration patterns can be shared with global audiences to raise awareness and galvanise action. Making AI-generated insights accessible through interactive platforms can inspire more people to engage with conservation efforts.
The deployment of AI in environmental contexts must though be guided by ethical considerations. For instance, when AI is used to monitor endangered species or Indigenous lands, it is essential to safeguard data privacy and ownership. Transparent protocols and equitable partnerships are critical to avoiding exploitation while ensuring AI serves the greater good.
Tracking down the hunters … and the hunted
Protecting endangered species often involves confronting two elusive entities: the animals - and the individuals threatening their existence. AI has proven invaluable in tracking both.
For example, in India, conservationists employ AI to analyse camera trap images, creating an extensive database of individual tigers. This database enables authorities to trace the origins of tiger pelts that surface on the black market.
The capacity of AI to process and interpret vast quantities of wildlife data from diverse sources - including camera traps, citizen science observations, and field research - offers unprecedented insights. AI algorithms can identify and monitor individual animals across remote habitats, such as snow leopards in the Himalayas or marine mammals in the open ocean. These insights are critical for shaping effective conservation strategies.
In Africa, the stakes are equally high. Wildlife rangers in Uganda and South Africa now leverage drone technology combined with AI systems developed by researchers at the University of Southern California. These tools predict poachers' movements with remarkable accuracy, enabling rangers to intercept them before they strike. This proactive approach has saved countless rhinos and elephants, ensuring these iconic species have a fighting chance against extinction.
AI could empower global citizens to contribute to conservation efforts more effectively. For example, user-friendly apps that leverage AI could enable individuals to report illegal logging, track wildlife, or monitor local environmental changes in real time. By aggregating such data, AI could create a crowdsourced global picture of ecological health, encouraging broader participation in environmental stewardship.
AI's potential is maximised when it serves as a bridge between diverse groups: scientists, governments, Indigenous communities, and citizens. Developing more accessible AI tools that cater to a wide range of users can ensure that underrepresented voices, particularly those of Indigenous and local communities, play a central role in conservation efforts. These communities often possess invaluable traditional knowledge, and AI can complement their insights, creating a holistic approach to environmental protection.
A farming revolution
AI’s capacity to process extensive data from varied sources, analyse it, and deliver actionable insights in seconds has transformative implications for agriculture. Small-scale farmers, who often lack access to advanced resources, now benefit from expert-level guidance through AI-driven tools. This democratisation of technology is revolutionising farming practices worldwide.
In the Khammam district of Telangana state, India, a groundbreaking initiative involving 7,000 chili farmers exemplifies this shift. This project, a collaboration between the World Economic Forum India’s Centre for the Fourth Industrial Revolution and governmental agencies, utilised AI for soil analysis, nutrient management, pest prediction, quality control, and marketing. Farmers accessed these insights via a chatbot in their native Telugu, making the information accessible and actionable. The results were transformative.
Over an 18-month period, participants saw a 20% increase in chili production per acre, reduced pesticide and fertilizer usage, enhanced product quality, and improved marketability. Net incomes doubled, underscoring the tangible benefits of AI-driven farming solutions. Encouraged by these outcomes, state authorities plan to scale the program to half a million farmers, covering five crops. This initiative not only enhances productivity but also fosters sustainability and resilience in agriculture.
The deployment of AI in environmental conservation should be guided by principles of transparency, equity, and ethics.
As we rely on AI to interpret complex datasets and make predictions, it’s crucial to ensure that these systems are free from biases and are designed to support sustainable and equitable practices. For instance, when AI is used in agriculture, its solutions should prioritise not only productivity but also long-term soil health and biodiversity.
Using AI to model future scenarios
Beyond immediate applications, AI can play a pivotal role in modelling future environmental scenarios.
By integrating climate data, biodiversity trends, and human activity patterns, AI could provide detailed projections of ecosystem changes. These models can inform long-term policy decisions, helping to identify proactive solutions to mitigate negative impacts on vulnerable environments.
Can AI really talk to animals?
Ecoacoustics, the study of environmental sounds, represents a pioneering frontier in ecological monitoring.
By deploying hypersensitive underwater microphones, or hydrophones, researchers can capture the faintest sounds within marine ecosystems.
An AI system known as SurfPerch, developed by scientists from the University of Bristol and University College London, in collaboration with Google’s DeepMind, analyses these soundscapes to identify and track marine species. This data provides critical insights into the health of coral reefs, which occupy just 0.1% of the ocean’s surface, yet support 25% of marine life.
Interestingly, SurfPerch’s effectiveness owes much to its training on birdsong libraries. Despite their apparent differences, fish and bird vocalisations share enough underlying patterns for AI to learn and refine its recognition capabilities.
This self-improving model exemplifies AI’s ability to adapt and excel in complex environments, offering hope for preserving fragile ecosystems.
Whale song
The Cetacean Translation Initiative (Project CETI) is harnessing AI to decode the communication of whales. By analysing extensive recordings from whale-mounted tags, underwater robots, and other sources, researchers aim to map out patterns in whale communication.
While translating whale songs into human language remains a distant goal, this endeavour could revolutionise our understanding of interspecies communication and deepen respect for marine life.
The ethical implications of such advancements warrant careful consideration, but the conservation benefits are undeniable.
What About AI’s energy consumption?
While AI holds immense promise, its energy demands raise serious concerns. A single query on ChatGPT, for instance, consumes 10 times more electricity than a standard Google search.
Projections suggest that AI could double data centre carbon emissions by 2030, potentially exacerbating global energy challenges at a time when reducing consumption is paramount.
However, there is a counterpoint. Leading tech companies, including Google and Microsoft, are investing heavily in renewable energy to power their operations. Moreover, AI itself offers solutions to optimise energy use. For instance, Google applied DeepMind’s AI expertise to its data centres, reducing cooling energy consumption by an astonishing 40%. This breakthrough cut overall data centre energy use by 15%, demonstrating AI’s potential to drive efficiency. Experts predict similar gains across various sectors.
AI can optimise energy usage in buildings by adjusting systems based on real-time weather and occupancy data. Even refrigerators can be programmed to provide precise cooling tailored to their contents, minimising waste.
As AI continues to evolve, its role in curbing energy consumption and mitigating its own environmental footprint will become increasingly critical.
The role of Open-Source AI
Encouraging open-source AI initiatives in environmental fields could accelerate innovation while ensuring that technological advances are widely shared. Open-source models allow researchers and organisations, particularly those with limited funding, to adapt and implement AI solutions for their specific needs. This democratisation of AI could significantly expand its impact.
Anticipating and addressing unintended consequences
Finally... while AI is a promising tool, it’s essential to remain vigilant about its unintended consequences. For instance, increased reliance on AI-driven technologies could inadvertently exacerbate inequalities if access is limited to wealthy organisations or nations.
Additionally, over-reliance on AI might sideline the human intuition and experience that remain vital in nuanced decision-making processes.
In summary, AI is a catalyst for transformative change in environmental conservation, but its application must be guided by inclusivity, transparency, and sustainability to ensure that its benefits are universally realised.
The intersection of AI and environmental stewardship is not just about solving current problems; it’s about reimagining how humanity interacts with the natural world in the long term.
Carl Dodd, Property Revolutions Ltd.
