The Impact Genome Project plans to use "big data and genomic analysis to measure, predict, and improve the outcomes of social programs." It's a worthy goal: All of us involved in social change would love the power to predict outcomes, particularly when we're on the hook to funders for those results.
What may get lost, however, are the programs that matter most in the long run.
Sure, we can use data from prior bed-net distribution campaigns to predict whether a new bed-net campaign will successfully increase the number of bed net users (and thus decrease instances of malaria). We may even be able to use data from bed-net distribution campaigns to predict, albeit with less certainty, the outcome of a condom distribution campaign. Given how much government and philanthropic funding goes toward aid programs, that's important information.
But such programs represent only a small subset of the changes our world needs. Sometimes, yes, we need more people to use bed nets. Other times, we need laws and courts that protect journalists, appropriate police investigation and prosecution of gender-based crimes, an adequate system of contract enforcement so entrepreneurs can flourish, or an end to the internment of refugees in camps—a massive waste of human capital and a blatant violation of refugees' rights to work.
Can the Impact Genome Project predict the success of initiatives designed to achieve these ends? Would the Impact Genome Project have predicted Dr. Martin Luther King Jr.'s success or Harvey Milk's influence on marriage equality?
Even with bed nets, we probably don't see distribution by aid agencies as a sustainable model, long-term. Instead, we want policies that make bed nets a local imperative: government incentives for local production of bed nets, public health advertising encouraging bed net use, and a strong science curriculum in schools so that students—the next generation of parents, citizens, and leaders—understand why bed nets matter.
Even for bed nets, we ultimately want a new policy framework. Without it, social change is unsustainable.
If the Impact Genome Project can accurately predict programs that yield policy change, anywhere in the world, I'll be thrilled. I'll also be surprised. The factors that influence success are highly varied and often have little or nothing to do with the policy in question.
My organization’s Thai affiliate, Asylum Access Thailand, for example, began work in 2010 aimed at getting a historic temporary asylum law on the books in Thailand. If passed, the law—technically an amendment to Thailand’s existing Immigration Act—would mark the first time Thailand granted any legal status to refugees. Could the Impact Genome Project have predicted that, just as the draft law was ready for introduction to Parliament in 2014, one party would boycott elections and leave the country without a functioning government? Or could it have predicted that Asylum Access Tanzania's 2012 letter to the UN Special Rapporteur on Migrants, which initially soured our relationship with the Tanzanian government, would ultimately catalyze improvements in the government's approach to refugees when a new Minister of Home Affairs was appointed?
More likely (in my admittedly non-data-driven view), the Impact Genome Project will reinforce many funders' preferences for programs that yield immediate and easily measurable returns.
The Impact Genome Project's creators, Jason Saul and Nolan Gasser, liken their efforts to those used in the financial world. They're right—and that's the problem. Lenders prefer those whose credit-worthiness is easily measurable—even those with a history of nonpayment—over foreigners, young people, and others whose credit-worthiness may be excellent but whose credit history is unknown. Financial markets prefer companies with recurring quarterly profits over those that incur losses as they build a foundation for greater gains long-term. The Impact Genome Project similarly incentivizes a focus on short-term results.
At the Skoll World Forum last month, Saul said he hopes that the Impact Genome Project will lead to a "social capital market," where outcomes are bought and sold. The problem is, the most sustainable and effective social change won't sell well.
If we're serious about effective social change, we need more incentives for funders to support efforts to shift policy frameworks. By developing and promoting the Impact Genome Project, Saul and Gasser create a countervailing incentive, pushing funders toward direct aid models. And by pushing for a social capital market, they replicate, rather than correct, the inefficiencies of existing capital markets.