Many important insights throughout history seem obvious to us now. How could people not have realized that apples fall to the ground due to gravity? Well it wasn’t obvious until Isaac Newton created a framework for that understanding. The very fact that it made so much sense in retrospect is exactly what made it such a powerful insight.

A problem well-defined is a problem half solved”

— John Dewey

#WeTheData used an experimental approach to engage a community in defining and simplifying a complex problem. This approach combined collective expert input and network analysis to identify a few core Grand Challenges for “democratizing data” (making our personal data work for us and not against us). A number of people asked, “Why did you have to go through that complicated crowd-mapping process and network analysis to define these challenges? Aren’t they kind of obvious?”

Well, maybe in retrospect, but it wasn’t so obvious at the start. When we first interviewed a diverse group of experts, we compiled over 150 challenges that at least one expert deemed extremely important for democratizing data. With input from others, we boiled that down to 90 ‘critical challenges’.

So how do we filter 90 down to a more manageable subset?  We could have just asked people to vote on which ones were most important, but popularity doesn’t always equal importance.  So instead we developed an approach for people to indirectly vote on which challenges are most impactful by voting on consequences.

We asked how do these problems influence one another? If one challenge is solved, which others are solved too? Which get worse? That created a Problem Ecosystem. Each node (or ‘species’) in that network is a critical challenge to be solved (defined by experts) and each link is a human brain saying “These 2 challenges are inter-dependent.” So it’s literally a map of collective understanding of the bigger problem.

We then used the structure of that network to identify a small group of under-nourished catalysts with broad reach (the yellow points in the image above).  Those yellow ‘asymmetric hubs’ then were clustered into four groups of challenges that are tightly interdependent to create a nexus of four Core Challenge Areas that, if solved together could catalyze positive change:

1. Digital Access – This is the basic technical challenge of providing access to the under-served.

2. Digital Trust – While technical access is a core foundation, people won’t participate if they can’t trust in the system, especially if their personal security is at risk.

3. Data Literacy – Even if people have access (both to technology and data) and the trust to participate, they need to be able to intuitively ask questions with data and think critically about the answers presented to them. This  concept of ‘literacy’ is not restricted to traditional education. It could come from better designed interfaces that make interacting with data a basic part of everyday life.

4. Platform Openness – Finally, the vibrancy of our personal data ecosystem will only come from openness to copy, modify, improve, and innovate.  Clearly being open can make a platform susceptible to abuse, but it also creates opportunities for shareable innovations that prevent it.

Make sense in retrospect? We hope so! Now we know why; We understand that they need to be solved together (each is necessary, none are sufficient); and We know this is not just one person’s random opinion.

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