SAS is proud to be part of the Data for Good movement, which encourages using data in meaningful ways to solve humanitarian issues around poverty, health, human rights, education and the environment. From preventing life-threatening illnesses to protecting endangered species to rebuilding after natural disasters, organizations across the globe are harnessing data to make a difference. Applying data for social good has led to new and creative ways to address global issues, and we’ve gathered a few of these stories here.
The International Institute for Applied Systems Analysis (IIASA) conducts research into global change issues that affect our sustainability. Through our exciting partnership, we’re bringing together our AI expertise and IIASA’s scientific systems analysis to see the impact of deforestation in the Amazon rainforest with new eyes. Home to more than 2,000 animal and plant species, the Amazon is at risk as humans encroach on its remaining wilderness areas. More than 800 square kilometers are being destroyed every month as forests are cleared for timber extraction, crop production and infrastructure development – ultimately affecting water bodies, soil erosion, biodiversity and climate change.
We’re asking you to see what technology can’t. Our AI platform is already analyzing and making sense of millions of satellite images that show the magnitude of damage in the rainforests. But artificial intelligence can’t do it alone. We need your help to identify signs of deforestation that the model hasn’t learned to detect. Your participation, whether you identify deforestation in just one or 100 images, will allow us to fine-tune AI models that can detect changes in the Amazon and alert conservation and government organizations responsible for protecting it.
WildTrack identifies and monitors endangered species by analyzing digital images of animal footprints. With the help of SAS technology, WildTrack researchers are exploring how artificial intelligence and crowdsourced footprint data from all over the world could help find answers to global conservation questions. Where are these animals migrating to? How many are left? Artificial intelligence could add the ability to adapt through progressive learning algorithms and tell a more complete story.
To date, WildTrack is monitoring several different endangered species, including the black rhino, white rhino, Bengal tiger, Amur tiger, lowland and Baird’s tapirs, and polar bears. With deep learning, a computer can be trained to perform humanlike tasks such as identifying footprint images and recognizing patterns in a similar way to indigenous trackers. But with the added ability to apply these concepts at a much larger scale and more rapid pace. Analytics really underpins the whole thing, potentially giving insights into species populations that WildTrack never had before.
As a first responder after a devastating earthquake in Nepal, the International Organization for Migration (IOM) needed to provide shelter to thousands of displaced families. Over 45,000 families occupied more than 200 tent camps that sprang up, scrambling for safe shelter as the torrential rains of monsoon season approached. IOM needed to find large amounts of sheet metal fast to start rebuilding homes.
SAS was able to help IOM quickly access global trade data that the UN collects every year. Decades of trade data from more than 200 countries was analyzed within minutes. IOM had answers about the area’s top producers and exporters of fabricated metal, and a purchase order for the materials was quickly placed. Data collection and analysis were key to giving people a sense of safety, stability and hope. SAS is excited about helping relief agencies understand what’s possible using analytics.
GatherIQ™ starts with you.
GatherIQ is a Data for Good app from SAS that uses analytics to support the efforts of nonprofits, partners and a growing community of citizens curious about making a difference. GatherIQ introduces you to the 17 Global Goals set by the United Nations for a better world. The free app lets the next generation of problem solvers learn about the goals and take personal action to help achieve them.
Data for Good in the Spotlight