Flood forecasting, biodiversity protection, robotics and AI for wildfire prediction; and more
AI for Good
The Leading UN Platform on AI – Global Summit 2025: July 8-11 | Geneva, Switzerland
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Flood forecasting at Google: The AI Solution for Global Impact
Flooding is one of the most widespread and costly forms of natural disaster primarily affecting developing countries and communities, resulting in disproportionate adverse consequences for human life. According to the World Meteorological Organization (WMO), floods are the deadliest natural hazards, and have been increasing exponentially both in frequency and intensity over the last decade. Flood forecasting comes up as an important strategy to reduce the damage of flooding and the communities’ vulnerabilities, as early warnings can save people’s lives.
In this AI for Good Discovery session, Grey Nearing, a Research Scientist at Google, discussed the company’s lood forecasting system and the opportunities for AI to improve flood predictions.
Floods have a greater impact on people than any other type of natural disaster across the globe. However, there is significant evidence that early warnings can effectively save lives and reduce economic losses.
“The world lacks high quality flood forecasts, and we are trying to fill that hole to the best of our ability”, said Nearing.
In 2018, Google has started developing a flood forecasting system that gathers rainfall data from a range of sources, including weather forecasts, satellites, and ground stations. This system uses multiple weather forecasting models from various sources, including government and private entities, to improve the accuracy of flood forecasting, which is especially important due to the inherent uncertainty in weather forecasts.
Read the full blog here.
Watch the video here.
AI in action: Protecting biodiversity and aiding conservation efforts
According to the Intergovernmental Panel on Climate Change (IPCC) report released in last year, global warming increasingly threatens ecosystems and species, and is expected to have severe and widespread impacts on global biodiversity.
“We are in the middle of the sixth extinction,” says Tanya Berger-Wolf, Professor at The Ohio State University.
As the world is losing species at an unprecedented rate, experts face the challenge of finding out what species are in danger and at what rate they are declining. However, the conservation status of monitored species is often data deficient. For example, The International Union for Conservation of Nature (IUCN), also called the “biodiversity monitor of the world”, tracks around 160 000 species, but lacks data for about 20 000 of them.
Apart from the problems linked to data collection, experts also face the challenges of data interpretation. This process, being mostly executed by humans, is very costly and time consuming, and therefore not effective because experts lack time and resources. Moreover, experts are concerned about misuse of information regarding climate change on the Internet.
Read the full blog here.
Watch the full video here.
Revolutionizing Collaborative Research
Advancements in AI have the potential to revolutionize healthcare by improving our ability to generate evidence that promotes better health decisions and better care. One of the most promising collaborative efforts in this area is the Observational Health Data Sciences and Informatics (OHDSI) initiative, which brings together a diverse group of stakeholders from around the world to conduct large-scale studies on health data. With over 3000 researchers from 80 countries and health records on 928 million unique patients, OHDSI is leveraging the power of AI to overcome the biases inherent in medical literature and produce evidence that can inform the treatment of conditions such as hypertension and COVID-19.
The AI for Good Discovery session “Drawing reproducible conclusions from observational clinical data” delves into the exciting work being undertaken by OHDSI to enhance health outcomes through data-driven, collaborative research.
Observational research is a technique used to collect real world evidence. With little to no interference by the researcher, subjects can be observed in their most natural setting. Instead of conducting experiments, observational research looks back at already available data.
However, there is a need for large data bases as there is too little evidence data to draw upon. “We are increasingly relying on AI”, says Dr. George Hripcsak, Chair and Vivian Beaumont Allen Professor of Biomedical Informatics at Columbia University, and Leader of the OHDSI coordination center. But even with a large number of test persons, concerns about the veracity of data and various biases can arise.
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According to Dr. Hripcsak, reliable evidence thus requires a new tool: the community. This can take various forms, such as creating data networks that adhere to community standards, implementing community best practices, or sharing evidence through open-source tools that are accessible to the community.
Read the full blog here.
Watch the full video here.
Robotics and AI to predict and fight wildfires
With global warming, wildfires are becoming more frequent and intense. Current risk management systems are insufficiently equipped to cope with the increasing number of fires. In tackling blazes, firefighters are often confronted with collapsing structures, toxic smoke, and uneven steep grounds. In this context, new technologies such as AI-powered robots and drones have the great potential to revolutionize firefighting.
“The target use case for intelligent robots and AI is diverse. From wildfires that threaten historical landmarks and communities around the world, it is the humans we most hope to protect,” said Kirk McKinzie, President at McKinzie Smart Technologies.
Several different types of robots can be integrated into the firefighter’s mission. Shark Robotics is one company that has already designed six different robots. “Our goal is to intervene close to the danger to protect humans, their environments and the companies,” explains Manon Vermenouze, Director of Communications, Public Affairs, and CSR at Shark Robotics.
Their first robot, Colossus, “can transport equipment, […] evacuate wounded people […] and climb stairs”, says Manon. It was famously used at the Notre-Dame Cathedral Fire in April 2019. Its cameras and sensors “can be the eye and the arm of firefighters.”
Read the full blog here.
Watch the full video here.
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This edition of AI for Good Insider | Blog was curated by AI for Good Digital Communication Consultant, Alexandra Bustos Iliescu.