This week’s articles explore some of the technological innovations making their way in the development and humanitarian sector.
This week, we’re looking at some of the trendy technological innovations that are changing the way development and humanitarian actors are supporting vulnerable populations around the world. The articles not only expound on the benefits of the implementation of such technologies, but the implications for relevant actors such as beneficiaries, donors, or governments.
Catherine Cheney at Devex presents a variety of views around the growing adoption and promotion of medical cargo drones, which can support vulnerable and isolated populations in a more timely and effective way. She also discusses the role of donors in developing local capacity for more sustainable adoption.
“Amid the ongoing discourse, experts tell Devex donors should focus on ensuring competition for contracts, building local capacity for medical cargo drones, and supporting safe regulatory environments that drones for delivery require to succeed.”
Sarah Favrichon (GIZ), Lukas Borkowski, and Jennifer Henderson (Viamo), showcase their work in Madagascar, where they have introduced a mobile audio game to smallholder farmers aimed at educating them about climate change and microinsurance.
“In the gameplay, players walk through seven cropping seasons in a series of listen-then-make a choice steps. In each season, the virtual farmers attend an annual agriculture fair, where the learning and decision-making are framed within the conversational dialogue between peers and friends. […] At the end of the game, players indicate if they want to be contacted to sign up for the climate risk microinsurance.”
This article explains the work that Thinking Machines and iMMAP has been undertaking in Colombia to gather data about Venezuelan migrants through satellite imagery. Their goal is to detect the growing set of migrant settlements more rapidly and guide organizations like UNICEF and the World Food Program in deploying aid.
“[…] we plan to train a machine learning model to identify similar communities elsewhere in Colombia. If we can develop an accurate model, we can run it every quarter to produce quarterly maps of possible informal settlements across urban centres and areas along the Colombian-Venezuelan border. Organizations like iMMAP can then send field personnel to validate newly detected settlements. We also plan to explore ways of estimating the number of families and houses in each settlement, and their pace of growth over time.”
In this article, a set of experts at McKinsey compiles some of the use cases of AI in the domain of social good and maps them to the 17 Sustainable Development Goals (SDGs). Interestingly, even though the potential for impact is huge, important challenges related to implementation capacity, data accessibility, and scale-up remain to be addressed.
“From the modest library of use cases that we have begun to compile, we can already see tremendous potential for using AI to address the world’s most important challenges. While that potential is impressive, turning it into reality on the scale it deserves will require focus, collaboration, goodwill, funding, and a determination among many stakeholders to work for the benefit of society.”
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