A Lesson for Tech from the Newest Nobel Peace Prize Winners
by Emmalina Glinskis, Global Program Manager at Cloud to Street
On December 10th, the Nobel Peace Prize will be officially awarded to The World Food Programme, the humanitarian organization addressing hunger and advancing food security in more than 80 countries. Their work has shaped the lives of millions — on any given day, thousands of their trucks, ships, and planes are en route globally, responding on the ground in the most difficult environments imaginable and ensuring people have access to their most basic needs when emergency strikes.
The award is much deserved, and their work is needed now more than ever. Violence, the coronavirus pandemic, and increasing disasters exacerbated by climate change are contributing to global hunger in proportions unprecedented in recent history. In 2019, close to 750 million people faced severe levels of food insecurity. That’s nearly one in ten people in the world, and the trend has only been increasing in the past five years.
At Cloud to Street, as flood analytics data providers committed to serving the underserved, we are truly inspired to have learned so much from WFP, whom we’ve been directly supporting as they respond to extreme flood events around the world. Without the service delivery and commitment of country offices from Sri Lanka to Niger, the real impact of our support for rapid flood response and relief would truly never be realized.
Their mission is an inspiration, we believe, for all data providers in AI, machine learning, earth observation, and tech spaces. It has taught us that no success comes from user delivery being the last mile. It takes hard, messy work to understand what the needs are of those most vulnerable to flooding and most decentralized from decision-making processes. It means translating raw outputs of impacts and flood extents into meaningful insights for coordinating response, answering who is vulnerable and exposed, how are communities more at risk, which livelihoods are the most in need right from when the floods first strike to well after it recedes. Otherwise, it’s easy to pat our backs and say “job well done” by sending over a map, or a tool, or a report. But if we don’t connect with those on the receiving end, work with them to shape data support outcomes from their inception, or question our assumptions made in every piece of data delivered, then we won’t even come close to doing what needs to be done.
Tech for good tends to think big — “we’re going to eradicate this big world problem” or “our technology has the potential to transform lives.” But we’ve learned that the biggest opportunity for change comes from taking a back seat and listening first to the needs of those you intend to support. What are their biggest obstacles or communication blocks? How is data informally shared, and how can data providers seamlessly plug into standard operating procedures? Where are the spaces where these decisions are made? How can large scale analytics operate on the same level of analysis as household-level data collection on the ground to support actual humanitarian outcomes? There is so much we have to learn in any new place we work — the user is first hundred miles, and then some. That was the subject of our December 3rd Understanding Risk panel with collaborators at the World Food Programme, the Red Cross Red Crescent Climate Centre, and the International Research Institute for Climate and Society at Columbia University—and that is the work we will continue to do.
WFP has taught us these skills from day one. In November 2019, the Republic of Congo had one of the most destructive floods in recent history strike the northern section of the country. WFP reached out to us to understand the extent of the damages, since many of the communities were still inaccessible. At Cloud to Street, we got to work immediately employing high-resolution optical data and random forest classifiers to map the extent of the flood waters in key settlements that were inundated, providing the best snapshot we could give to confirm the devastation at hand as the situation unfolded. But, immediately, new questions arose: How can I best access these communities — boat, plane, truck? Where have the existing refugees in the communities fled to? How much crop was damaged to the point of crisis? Who of the most vulnerable were exposed to the flooding, and where? How can they access their next meal?
It became clear that a map is just a starting point, opening the doors to questions and further insights that could directly support WFP’s global mission, down to individual homes, families, and communities. We got to work on understanding food security even after the worst of peak flooding was over, building our own machine learning algorithm for croplands when global datasets couldn’t delineate between flooded agriculture and damaged agriculture. We took this data a step further, collaborating with groups carrying out household economy analyses in the field to input our agricultural damage data into models that produced detailed statistics for the poorest wealth groups in Congo as well as those with the most nutritional reliance on the very agriculture that was wiped out.
“My partners very much appreciated the data, as they don’t have this kind of data at the moment…I showed them your slides on water levels and crop impacts after peak flooding, and we can make a parallel between areas where waters have remained high for longer and areas where food insecurity rates areas the highest.” — Ophelie Lobjois, Operational Information Management and Reporting Officer, World Food Programme, Republic of Congo
With just a map and nothing else, our work would not have been able to help the World Food Programme in Congo secure $12.5 million in multilateral aid for flood response and recovery and more precisely target over 180,000 civilians in flood-affected communities with both in-kind assistance and cash-based transfers. We had to listen. We had to test assumptions, and we had to get creative. Plain and simple: flooding is and will continue to be a direct threat to food security and peaceful stability. Chronic floods may only worsen in the next three decades due to sea-level rise, increasing exposure to 300 million inhabitants worldwide. Data providers should and can do better with those we seek to support. No matter the innovation, we must learn from those doing the hardest of jobs first. We are so proud to continue our learning with this year’s well deserved Nobel Peace Prize Laureate, the World Food Programme.
Emmalina Glinskis is a Global Program Manager working to deliver Cloud to Street’s near-real time flood data to diverse users and stakeholders worldwide, translating the science to relevant country-wide action, planning, and response.
