Think about how you met the most important people in your life? Did you open up the sports page of the newspaper and check their stats? Did you have a meeting with your friends and weigh the character of all the people you could go on a date with? And yet that is how nonprofit funders claim to approach their relationships in this world. They want to be “strategic” and “evidence based” when what would really transform our approach to solving a problem is to be more human, to be a better listener, and to be emotionally present in a long-term relationship. As a PhD neuroscientist turned data scientist, you’d expect me to argue for the primacy of evidence in decision-making. Instead, I’m a believer that being human first will lead us to the evidence that matters most.
Most Western leaders are technocratic. They like to think they’re well informed. They understand how evidence forms public policy. They see themselves as the experts, even experts in listening to people. But they do a poor job of understanding peoples’ feelings when the reasons for those feelings are emotional and illogical. The 2016-2017 backlash against technocratic leaders that brought about Brexit (UK), Trump (USA), and Le Pen (France) is a sign that hard evidence is not enough. A more “human” leader focuses on feelings, and accepts that in order to bring people together and help the majority understand the reasons for a policy, they’ll need to let them make decisions for themselves, even the wrong ones. Those who do this will build stronger coalitions, based on a shared-identity, which alters the basis for how people value their lives. When leaders speak at people instead of working to understand why the people resist the truth about the world, the people find other ways to assert their power and their identity (such as electing poor leaders who have a good understanding of their feelings). I explain the tactics for this coalition building in my book: Storytelling for Change https://www.amazon.com/dp/B01MZ7W1IA
I learned how to really listen to people – I mean systematically and without interjecting – from Nina, a kindergarten teacher. At the height of the US invasion of Iraq (2003), she showed up on the street corner with two folding chairs, set them up facing each other, and invited others to sit and tell their story. The sign read, “What are your hopes and dreams for the future? And how has violence affected you in your life?”
People of every ilk stopped and spoke to her. She listened. She nodded. She only asked questions.
The next day I joined her. I found two chairs of my own and wrote the same thing on my sign. The next day, a dozen others joined, and we became the listening project. Listening was hard. It required discipline. We had no political agenda; our purpose was to be a lightning rod, something that takes all the pain people are feeling and channels it safely into something productive: healing. Nina learned to do this from an earlier intervention to stop gang violence in Philadelphia. Perhaps those people learned it from someone else.
Years later when I got a chance to start a different kind of listening project at GlobalGiving, all these experiences were in the back of my mind for what I thought it could be. A household name among funders had given us the freedom to go to Kenya and Uganda and discover a way to collect stories from people about every kind of “community effort” (development project) that affects a person’s life. There were no limits, and no prescription for how it had to fit into evaluations yet – just explore and do what made sense.
Since 2010, GlobalGiving has collected over 65,000 stories from much of Kenya and Uganda and several other regions of the world. The core elements of the method (story-centered learning) are similar to the street dialogues that worked in earlier, less formal settings. Asking a probing question with no clear “right” answer. This inspires thousands of people to share their own answers, and then listen to tens of thousands of others sharing theirs. Each anecdote becomes a data point, and the emerging mosaic of these data points provides a picture of the complex problem in all its richness. This ability to synthesize meaning from narrative is only now possible, because of the rise of machine learning as a method and “data scientists” as a profession. But the combined power of structured community story sharing with data science is revealing everything that matters in community development from the only point of view that matters – the community’s. It is from their vantage point alone that we will someday launch the right interventions that end poverty and transfer budgeting power to the community (these two events are linked).
Going “human” as a leader is accepting the unpredictability of outcomes when you truly listen to people and let them decide what is going to happen. Understanding science leaves me comfortable with complexity. The only solution to global problems is to embrace and accelerate the process of evolution within a community context, and rapidly explore different ways to share wealth and decision-making power, as I’ve explained on my blog. Evolution is a mechanism that transforms bad ideas into better ones, weak approaches for behavior change into stronger ones, and it can even better align our actions with our personal moral code. If religious texts are in agreement on one thing, it is that we are not going to save the world without undergoing the disruptive process of changing ourselves.
So when you’ve got one of the largest collections of narratives about life in the Global South ever amassed and some algorithms, what can that tell you about moral evolution?
One of our explorations identified some of the reasons why Somalis living in Kenya were tempted to join Al Shabaab or another extremist group. After collecting over 1000 stories from people in a popular recruiting neighborhood about a time when they or someone they knew was approached and asked to sign up, we found that the majority of people who did join did it solely for the money. They were explicitly not doing it out of religious fervor, and religious identity was rarely a factor at all. Somalis in Kenya were more likely to identify as “socialist” and “nationalist” than as religious or as a Muslim. Most stories were about deciding not to join a group, and these reasons were much more complex and varied.
This 2012 East African pattern is eerily similar to identity patterns spreading in the West in 2017. A growing sub-population are decidedly more self-interested, more locally-focused, less open to global cooperation, and increasingly isolated. Along with this turning inward and self-ward is a turning away from contributing to the general welfare, self-sacrifice, and mutual interdependence that is a core part of liberal religion. In the Nairobi case, these patterns teased out what should have been done to provide a clear strategy for stopping terrorist recruitment in that neighborhood: (1) Invest more in after school programs for youth in Somali-majority neighborhoods; (2) allow older Somali immigrants to get work visas; (3) stop sending Somalis to jail for non-violent crimes, because bailing someone out of jail emerged as the most reliable way to recruit a terrorist; (4) punish policemen who beat up Somalis and extort them.
None of this happened, because there was no political will. The following year we had the Westgate Mall mass hijacking. I believe it could have been avoided. We knew the problems and the solutions, but the human side of the problem was not at the center of the debate.
The best and most disruptive way to do that, would be to relinquish control of the priorities and funding to the people, using this storytelling process to align decisions with the community in some form of participatory budgeting. We speak often of innovation, but are we truly ready for it?