Getting policy unstuck #6: Chris Chibwana

Chris recently co-authored the Hewlett Foundation’s new Evidence-Informed Policymaking strategy. I wanted to speak to him to understand how the Hewlett Foundation thinks about research and its limits in policymaking, how AI is likely to affect this space, and what gets his attention when looking at a potential grantee. 

If you talk to data nerds, they tell you all we need is good quality data. If you talk to a political scientist, they tell you that data is just one input. In many cases, it's not even an input into policymaking because there are all these competing interests that the policymaker is trying to balance. If it's an election year, as this year is in a lot of countries, political interests will trump other interests. 

Even if the question was relevant for policy at the time, by the time the research is done that issue may no longer be relevant. You just have shiny results that nobody cares about. Researchers need to be much more responsive to policymaking needs. There are a number of organisations that are trying to ensure that evidence is provided in a timely manner, and that's all part of the reason that the Hewlett Foundation is moving towards supporting actors that deploy a broader methodological toolkit and are more proximate. If you're in the area, if you're in the country and there's a policy issue that needs to be addressed within a week… you have heard about that first hand, you know the context, you have the relationships, you can mobilise yourself and respond to that in a timely fashion.

There's often an inverse relationship between what's academically interesting and can therefore get published, and what is relevant for policy. A lot of the more important policy questions won't be interesting enough for journal editors to publish, because it’s the everyday, the simple things that we've already studied, and that maybe don't require new forms of evidence. Maybe the problem just requires that you synthesise what already exists and present it in a format every policymaker can understand. 

The way that researchers write is for other research audiences. It's not really for policymakers who only have a few seconds of attention for any given topic. Research papers are not fun to read if you are not a researcher. How can we make research more responsive to policy decision making? We partner with a number of organisations that are trying to do that. They exist not because they want to publish, but because they want to serve the public good.

If you incorporate evidence into policymaking that leads to greater public trust in the policymaking process, because it means you're not making decisions based on your personal interest, or to benefit people you know. And of course you get better development outcomes in general because you’re supporting interventions that are proven to be successful. 

One of the things that we're wanting to understand is what incentivises evidence use. Once we understand that, how can we elevate or increase the likelihood that evidence will play a part in policymaking? We want to maximise the chance that evidence becomes a key part of that policymaking process.

Over time these AI models will get smarter, and get a lot more precise. My hope is that eventually we’ll have ChatGPT on everybody's phones and it will decentralise research. It doesn't mean that we don't need PhDs in economics, we will, but for certain things people will have somewhat accurate information that they can use to make decisions. Maybe it will demystify evidence, so that it's not something for the elite and you don't have to have an Oxford or MIT doctorate to be able to participate.

When we fund, we’re looking for a hook to policymaking, not just something that is interesting to investigate. Why does this matter? It has to have a ‘so what?’ and it needs to be tied to policymaking. There needs to be a policymaker that you've identified who will benefit directly from the work that you're doing and you’ll be able to make their work a little bit easier. That's really why we exist. Policymaking is a hard job, and so how can we help policymakers do it a little bit better? And of course we have geographic restrictions to East and West Africa which is where we work.

The biggest mistake funders make is assuming they know everything: we don't. Funders have power, and it's the power of the purse, but our partners on the ground are the ones who know exactly what's needed. They are the ones that are talking to policymakers and discovering what challenges they’re facing. It's not my place to tell a grantee what they should be doing. It's important to give these organisations that are doing the hard work the agency that they need to determine what's needed. So we need to step back and see our role as facilitating the work of others, and being a thought partner where we can. 

The second mistake funders make is assuming there are quick fixes to the systemic challenges we’re trying to address. If policymaking was easy, we wouldn't be talking about it. Addressing these systemic issues that limit evidence-informed policymaking, whether it's capacity or whether it's building organisations that we need within the evidence ecosystem…  that takes time. These two or three year project cycles aren't going to do it. We need to be patient. We need to stay the course.

Parting thoughts…

I grew up in southern Malawi, and so I've seen the value of doing development right. Back in the day there weren’t social protection programs in Malawi, but I think if there were we would have been primary beneficiaries of those programs. And so when I got the chance to be able to acquire skills and use my expertise to help others, what better way to try and help address some of these challenges and hopefully contribute to making life better for a lot of people.

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