What is especially notable is that AI will soon reach a point that it will help stave off major global environmental crises–from attenuating climate change to mitigating the peril of endangered species. The burgeoning technology may even be integral to solving the challenges of disease containment. Projects in each of these crucial areas are already underway. Business leaders are currently working in environmental sustainability (be it green energy or epidemiology); and are optimistic about the amazing capabilities that will be afforded by AI. They are coming to understand that the technology will help overcome long-standing challenges. While formidable barriers to implementing AI still exist (including cost and regulatory approval), this does not deter the visionaries at the forefront of this field. Let’s talk about some of the most notable examples.

WildTrack uses a computer vision solution developed by a SAS called Footprint Identification Technology to monitor endangered species; and to do so non-invasively. The tool analyzes images of footprints of cheetahs, rhinos, and other endangered species to identify them, track them, and determine what threatens them.

Realizing the immense potential of AI to address environmental sustainability may be pivotal to making progress toward sustainable development goals…especially as it relates to the tight race with irreversible changes to our planet. This entails coming to terms with the stupendous computational power needed for accomplishing this ambitious task. The formidable data-gathering task is already being addressed with the explosion of Internet of Things (IoT), including cheap and ubiquitous sensors / cameras on the ground and satellites in orbit.

The ability to solve major global issues with AI depends on our ability to gather large data sources on these problems. Happily, we now have the capabilities necessary for this at our disposal. Through a synergy of IoT and what is called “deep learning”, society can achieve better monitoring and prevention of damage on Earth’s land, air, and water. The incredible combination of IoT and machine-learning can provide automated data-collection and perform highly-complex decision-making tasks, leading to the optimization of a wide array of important processes–from farming to storm watching.

As climate science becomes more sophisticated and the prediction of natural disasters becomes more urgent, scientists are discovering the true potential of AI. Cutting-edge machine-learning tech has created models that use satellite images to recognize and monitor different activities across the planet. This allows us to trace phenomena like glacier recession, droughts, deforestation, water-level changes, weather patterns, and encroaching urbanization. More effective disease detection, erosion monitoring, species identification, and animal migration tracking are all possible with AI. We can thereby detect the early-warning signs of, say, famine or disease…and even incipient poverty.

Both ecological and meteorological problems often involve highly-complex processes that scientists do not yet fully comprehend. When it comes to doing the necessary work to resolve these problems, resources are woefully limited. With advances in machine-learning, we can harness the incredible predictive power of AI to make better data-driven models–thereby augmenting our predictive capabilities. This pertains to such exigencies as water availability, ecosystem damage, and pollution trends.

AI applications are legion when it comes to environmental preservation. The technology is most helpful when the possible solution to a problem can be formulated via brute calculation and raw processing power. For example, when it comes to climate data, there is a wealth of structured data about temperature, sea levels, emissions levels, etc. However, there is also a lot of un-structured data–like form images, video, audio, and text. When it comes to analyzing massive amounts of un-structured data, machine learning is really the only viable solution. Evaluating massive amounts of data is also about noticing clues that may not be obvious to human eyes. Sometimes there is a tiny change that precipitates a larger problem, but mere humans often miss it because we are not highly attuned to anomalies when it comes to assaying very large data-sets. AI can rise to the occasion.

It’s all about bringing an algorithmic approach to problems that human intelligence may be inadequate to contend with. AI can even be used to develop optimization methods for wildlife conservation planning–an area with highly limited budgets and personnel. Moreover, we can use machine-learning to help protected areas fight the poaching of endangered animals; as AI-generated behavioral models of poachers can be created. Poacher route-prediction can then be used to optimize patrolling strategies, and thereby pre-empt this odious activity.

As the field of AI develops, so will our potential to protect the environment. From the land and air to both potable water and ocean water, AI is now a power that governments, companies, NGOs, and individuals can marshal in the endeavor to create a cleaner, healthier planet.