By Raj Pandya
As you know, I’ve been thinking a lot about equity, power, and science. It isn’t a long walk from there to thinking about the appropriate role for a scientist in issues that deal with power and who has it. This seems to come to a head around issues that are especially contentious, like hydraulic fracturing, climate change, or genetically modified organisms.
The Thriving Earth Exchange recently held a workshop in Pittsburgh, PA on hydraulic fracturing as part of an AGU effort called “GeoPolicy Connect,” which is designed to break down barriers between groups on tough science policy issues. It was an artfully constructed workshop – props to my friend and colleague Lexi Shultz for her work creating an environment where scientists, policy-makers, local leaders and even industry representatives could sit down and have productive conversations. That level of civility alone was outcome enough for the workshop, but the workshop also helped me explore the roles scientists can play in contentious issues.
Going into the workshop, my starting point for scientist’s roles was based on two premises.
- As scientists, we can bring useful insight to the table. We don’t own the table, we can’t set the table, and we are just one voice at a big table, but, with appropriate humility and respect, science can offer a useful perspective.
- One of the best ways to be useful and honor the integrity of science is to be an honest broker. (I owe a lot of my thinking about this to the book “The Honest Broker” by Roger Pielke, Jr., and you should check that out for a much more thorough and readable explanation of the concept.) Essentially, honest broker means this: we don’t use science to advocate, we use it to describe options and consequences.
I walked into the GPC workshop thinking that AGU scientists could contribute to the hydraulic fracturing discussions by acting as honest brokers. I was buoyed when our facilitators told me about an exercise they used to cut through contentious issues: laying out the facts. Seemed perfect for an honest broker.
Not surprisingly, it wasn’t that easy. I ran into at least three challenges with the honest broker model.
First, facts aren’t static. They seem to be a function of where, and even when, you lived. In Pittsburgh today, hydraulic fracturing rescued the city from economic stagnation and provided the foundation for a tech resurgence. For the region, hydraulic fracturing means natural gas displaces coal, improves air quality, and slows climate change. For many small towns, hydraulic fracturing has meant traffic, noise, infrastructure, and unanswered questions about health, water quality, and air quality.
Second, the facts aren’t easy to get. The workshop focused on cumulative impacts. Cumulative impacts mean that you can’t think about a well in isolation, but you have to think about the combined impact of a whole series of wells. And you can’t just think about the fracturing process itself, but all the direct and indirect impacts that come with it, like pad sites, traffic, waste water, and injection wells. You can’t think about just geology, or just earth science, or just economics, or just public health – you need expertise across disciplines, and all those experts will want, and probably need, more data than you can afford.
Third, the facts are nearly impossible to compare. Think about all the tradeoffs that go into placing a well on a property. How do you weigh the short-term economic benefit to the owner against the long-term regional benefit from less coal, for example? At first, I thought we could turn to economics – some kind fancy accounting should be able to handle opportunity costs, deferred costs, sunk costs, and hidden costs. But there are ineffable costs, like the sound of crickets in the evening, instead of compressors.
All of this creates a practical problem for the honest broker model. You need a lot of honest brokers if you want to explore the whole set of potential impacts of any decision. How painful is that – imagine every decision as a faculty meeting! (I was a faculty member, and our meetings, in general, were not models of efficiency.)
Even with all those experts, you still haven’t made a decision. That is because science can’t tell you which impact is morally good or reprehensible, or how to weigh the potential benefits for some against the costs to others – that is about values and morals. Science can’t tell you whether reduced CO2 for the planet is a fair trade for the disruption in a small town or for the potential for damage to a watershed.
Wrestling with these challenges to the honest broker model, I thought maybe we could divide it up. Scientists can be honest brokers and provide input to decision-makers, who have the moral judgement and wide-ranging perspective necessary to weigh diverse pluses and minuses.
I quickly decided that wasn’t quite right. The scientists in the workshop weren’t just experts – they were also part of the decisions. They were studying hydraulic fracturing, but they were also members of communities that interacted with hydraulic fracturing.
In fact, I think it is probably a mistake to think we can or should separate expertise and human values. (Mr. Spock struggled with that, and he was only half-human.) Values and expertise are clearly intertwined – we choose what to study, at least in part, because of our values, and we all tend to value the things we study. Going even further, I’d argue that expertise and values should be intertwined. Science unmoored from values and morality is dangerous. Any powerful tool unmoored from values is dangerous.
So, what does that leave me, other than confused and uncomfortable? After several days, I had an idea. I think it is something like the honest broker who transparently participates in adaptive management. I am sorry it doesn’t have a catchier name.
Adaptive Management and the Honest Broker
Adaptive management, another concept explored in the workshop, essentially means you manage going forward, constantly adjusting based on the new data, toward a goal you have set together. An example might be town leaders, residents, and timber companies developing, implementing, monitoring, and adapting strategies designed to optimize the long-term productivity and sustainability of a forest while also achieving some near-term benefit and preserving local quality of life.
Because Adaptive Management uses both goal setting and monitoring, it might provide a way to reconcile the honest broker role with the human role of decision-making. In adaptive management, the human part is deciding – together and in an equitable way – what kind of future you want. The honest broker part is monitoring your progress toward that future. In both, a paramount responsibility is transparency and inclusion. To me, that means we scientists must ensure that information we collect isn’t hoarded, quarantined, or used in a way that undermines anyone’s ability to participate in decisions.
Sure, this isn’t perfect. No good name, for one. Setting goals is still a messy interplay of honest brokers and human beings, values and expertise. In true adaptive management, you revisit that goal setting over and over as you get new data, which makes the messy part larger. But, at least that messy part is demarcated from monitoring and fact collecting, and we can bring in new expertise in an ongoing way.
Maybe what adaptive management really does is distinguish between decision-support and decision-making. And maybe that distinction can help us manage the conflict between being an honest broker advising and being a community member.
Or maybe not. What do you think?
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