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What We Do

We leverage our capacity to overcome challenges in three core areas:

Theme 1: Vibrancy and Diversity
Overarching Challenges:
We Aim To:

Empower the disempowered in data-driven decision making processes.

Increase the diversity of those that can participate in data-driven decision making.

Give the young generation a voice in data-driven decisions that will impact the future of their world.

Provide Free Access to critical "building block" datasets and technologies that are relevant for advocacy across multiple domains.

Train the next generation of leaders in the use of data for decisionmaking activities, with a focus on individuals without STEM backgrounds.

Remove barriers faced by groups to use data, even if they lack instiutional capacity.

Theme 2: Sustainability
Overarching Challenges:
We Aim To:

Mitigate negative human implications of a changing climate.

Identify solutions that have worked to promote mitigation of emissions or adaptation to new environments using causal inferential techniques.

Communicate the challenges and the opportunities posed by climate change, with a focus on practical solutions. 


Develop new machine learning techniques that take advantage of freely available satellite imagery to understand what mitigation and adaptation strategies are working - and, which aren't.

Identify succesful interventions hand-in-hand with practitioners in order to avoid divisive rhetoric and speed the adoption of new technologies in the climate change space.

Provide practical guidance on what project types are most likely to suceed in different geopolitical contexts, based on what's worked in the past.

Theme 3: Security
Overarching Challenges:
We Aim To:

Reduce the likelihood that international citizens - especially those providing development aid - are put in harms way.

Identify locations that are becoming more secure in order to facilitate a return of aid activities in a more timely manner than is currently possible.

Promote the free exchange of security-related information.

Collect and publish event-based data on where large actors are conducting activities that may mediate security environments around the world.

Derive novel machine learning approaches to detect shifts in infrastructure that are of relevance to the global security environment.