The Rockefeller Foundation Establishes Atlas AI - New Startup to Generate Actionable Intelligence on Global Development Challenges
Atlas AI appoints Victoria Coleman as CEO, most recently CTO of Wikimedia Foundation
NEW YORK, Feb. 6, 2019 /PRNewswire/ -- The Rockefeller Foundation today marked the public launch of Atlas AI, a social enterprise established by the Foundation and a team of Stanford University professors to develop data products to support global development. Atlas AI works at the intersection of development economics, crop science, remote sensing, and artificial intelligence to generate detailed insights on poverty, crop yield and economic trends across Sub-Saharan Africa. Earlier this week, Atlas AI named Victoria Coleman, previously Chief Technology Officer of the Wikimedia Foundation, as the organization's first Chief Executive Officer.
A B-Corporation founded in partnership with The Rockefeller Foundation in 2018, Atlas AI uses machine learning algorithms and a rich array of ground truth data to estimate economic activity and crop yield from satellite imagery. Atlas AI validates its models against gold standard datasets collected by multilateral partners in the field, and their methods are backed by rigorously peer reviewed scientific research.
"Atlas AI is an innovative model for translating the best research thinking into products and services that accelerate sustainable development. Part of The Rockefeller Foundation's vision is to unlock AI's tremendous potential to improve people's well-being while mitigating downside risks," said Zia Khan, Vice President of Innovation at The Rockefeller Foundation. "We're tremendously excited to welcome Victoria as Atlas AI's new CEO. We conducted an extensive search and she brings a unique combination of skills and experiences to complement a world-class team."
The reality is that it's difficult to reach people living at or near the poverty line with critical information and services, especially if they are not online. Fielding a census or survey is time consuming and remarkably expensive—particularly for low-income, fragile, and conflict-affected countries. Atlas AI was founded to solve these challenges, delivering information more quickly and cost-effectively, and with greater accuracy and detail.
Based on years of cutting-edge research, Atlas AI was launched by professors David Lobell, Stefano Ermon, and Marshall Burke of Stanford University to give decision-makers in developing countries access to low-cost, cutting-edge data. Experts in artificial intelligence, data science, and development economics, Lobell, Ermon and Burke had already shown that satellite imagery can be used to map poverty and crop yields in Africa with a combination of economic data, space technology, and machine learning algorithms. Over the last seven months they began building Atlas AI with support from The Rockefeller Foundation, working with partner organizations in Africa to test and operationalize new products, including high-resolution datasets on wealth, consumption, and agricultural yields.
Atlas AI has assembled a team of the best scientists and engineers in the world with the passion and creativity to make a positive difference. Today, Atlas AI announced Victoria Coleman as the organization's first CEO. As CTO at the Wikimedia Foundation – the non-profit organization behind Wikipedia, one of the world's largest and most popular web properties – Ms. Coleman set the vision and strategy for technology and operations for Wikimedia projects in collaboration with the Wiki community. Previously, as Vice President Engineering at Yahoo! Inc., she led the company's web services at scale. Before joining Yahoo!, Ms. Coleman served as Vice President, Emerging Technologies at Nokia. Throughout her career, she has demonstrated a commitment to open data, a crucial part of Atlas AI's mission. As a public benefit corporation, the company will support an open analytics platform allowing the public to browse economic datasets for the developing world, at sub-national resolution.
While private-sector businesses have been building and deploying artificial intelligence for years, most organizations in the non-profit, civic, and public sectors have yet to robustly apply these techniques towards the complex challenges they address. They have a strong appetite to use applied data to make their work go farther, faster, and ultimately help more people – but they may lack access to the skill sets and resources to do so in their context.
In an expanding effort to build the field of data science for social impact, in January 2019 The Rockefeller Foundation announced the creation of the Data Science for Social Impact collaborative in partnership with the Mastercard Center for Inclusive Growth. The first activity by the collaborative was $20-million in funding to DataKind, a global non-profit that connects data science talent with social organizations – harnessing the power of data science and AI in the service of humanity.
As a science-driven philanthropy focused on partnering for the greatest impact, The Rockefeller Foundation supports the growth and success of Atlas AI so that its cutting-edge data products and services get to those who need them most. The Foundation maintains a seat on Atlas AI's Board of Directors and will continue to be an active partner focused on long-term stewardship of results-oriented, global human development outcomes.
To learn more about Atlas AI, visit their website or read their Medium posts.
About The Rockefeller Foundation
The Rockefeller Foundation advances new frontiers of science, data, policy and innovation to solve global challenges related to health, food, power and economic mobility. As a science-driven philanthropy focused on building collaborative relationships with partners and grantees, the Foundation seeks to inspire and foster large-scale human impact that promotes the well-being of humanity throughout the world by identifying and accelerating breakthrough solutions, ideas and conversations. For more information, visit www.rockefellerfoundation.org.
SOURCE The Rockefeller Foundation
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