In the past decade, the increasing availability of data and computational resources led to the merger of traditional statistics, computer science and visualization under the broad umbrella of data science.
New algorithms are emerging, new intelligent systems, and with them, new applications. Past the hype of digital marketing, data scientists today apply their tools to address social and humanitarian issues, working both on non-profit and on commercial platforms.
DataKind is a non-profit that brings together volunteer data scientists and social change organizations who do not have the knowledge, or the resources, to benefit from data science. In one of their projects, they teamed up with The World Bank Global Facility for Disaster Reduction and Recovery (GFDRR) and set a framework of applying satellite image analysis and convolutional neural networks to aid disaster relief.
In another project, DataKind work with the Raffles’ Banded Langur Working Group to protect the critically endangered Banded Leaf Monkey, native in Singapore. Aside to mapping the home range and geolocating the activities of the monkeys, DataKind volunteers set up an app (Tinder for monkeys) to crowdsource training data for a machine learning algorithm that will estimate the monkeys’ population size.
Earthrise media use artificial intelligence to source local stories about climate change and environmental degradation from the abundance of available satellite imagery. They apply visualization tools and create infographics to support investigative journalism and education from space, covering topics from flooding to draught to waste management.
On the commercial front, machine learning algorithms and data analysis tools are making their way into environmental monitoring, change detection, agriculture, energy efficiency, urban design and geospatial analysis in multiple scales. And as it happens with every tool, their application for good or evil depends on our creativity, our attitude and our involvement.