Navigating Uncertainty
Don't fall for easy answers, but also don't throw up your hands; embrace partial knowledge
I’ve started having trouble coming up with new entries for the blog. And then I realized I could write a post about why I’m having trouble writing posts1.
I haven’t actually run out of topics. In fact, my notes file lists about 50, many with a page or more of seed material. However, most of these potential topics would require a lot of research to flesh out, and I’m too lazy / busy / impatient2 to put in that work.
My goal for this blog, to the extent that I have a coherent goal, is to shed light on the most effective paths for mitigating climate change; basically, topics that can help us make choices and set priorities. Here are a few of the items on my list:
Which important emissions sources are least addressed?
Are there limiting factors to the greening of the economy that we need to be addressing? (E.g. skilled workers; key raw materials such as lithium, nickel, or copper; transmission lines; land. Which of these are on track to be a problem?)
What are the most important actions individuals can take? (As a consumer; as a voter / citizen; as an employee; as an investor; as a donor.)
How much of a role can improved land management (including agricultural practices and forestry) play in drawing down carbon?
How close are we to the point where demand for fossil fuels will start to drop significantly, and is the market reacting properly to that, or should we do more to discourage new supply?
These questions all have one thing in common: they require quantitative evaluations of how things are playing out in the real world. By contrast, most of my topics so far have been binary propositions whose truth can be reasoned from first principles. That’s not a coincidence. Guess which type of question requires more research?
To make further progress, I can’t keep dodging the messy empirical questions. Unfortunately, that way lies danger or, worse, hard work.
Quantitative Evaluations Of Climate Topics Are Hard
Propositions like “we need to address all of the emissions sources”, or “electricity is harder to store than fossil fuels, so we need better coordination of production and consumption” are sort of self-evident. A few motivating examples are sufficient to explain the idea and its importance, and then I can move on to discuss potential solutions.
Quantitative questions and relative comparisons, by contrast, are less amenable to quick conclusions. Take the topic of “regenerative agriculture” (a set of agricultural practices, such as no-till farming, that are thought to provide a number of benefits, including sequestering carbon in the soil). It’s easy to find support for the idea:
National Geographic: “The solution to climate change is just below our feet.”
oneearth.org: “A growing consensus is emerging among soil scientists that regenerative agriculture – agricultural practices that remove carbon from the atmosphere and put it back in the soil – could deliver a huge win for the climate.”
A recent Canary Media writeup notes that “The IPCC’s latest report lists soil carbon sequestration as one of the lower-cost, more readily available options for carbon dioxide removal.”
Sounds like this is a settled question, yes? And yet, there appears to be a lot of question as to how much carbon can be captured, which techniques are most helpful, and how to measure the impact. There is even some question as to whether some of these practices have any net climate benefit at all. For instance, in a recent podcast, Eric Slessarev (a staff research scientist at Lawrence Livermore National Laboratory) notes two significant problems with no-till agriculture:
The carbon captured in the soil is in the form of organic carbon, which is readily consumed by soil microbes. As a result, the carbon may only be stored temporarily.
We’ve recently been learning that there is a complex interplay between carbon at different depths in the soil. No-till agriculture can actually reduce the amount of carbon deeper in the soil. Unfortunately, many studies have only looked at the top 12 inches, and therefore have failed to account for this reduction in deep-soil carbon; the results may therefore be misleading.
So, how much carbon can we realistically expect to capture via regenerative agriculture, and how long will that carbon remain out of the atmosphere? I don’t know, and at this point, it seems that no one really knows for sure. There are a lot of questions for which we simply don’t have definitive answers yet. Many important questions in climate change are questions about how the future will play out, so they’re actually predictions3, which are always fraught.
Blindly Repeating Someone Else’s Take Is Rarely a Good Idea
Uncertainty is unpleasant. We like knowing the answers to things. I find it frustrating that I don’t understand how much of a role regenerative agriculture can play, which bottlenecks deserve attention, or exactly where we sit on the fossil fuel demand curve.
For every messy real-world question, the Internet provides an unlimited supply of easy answers. Earlier, I listed a few sources which were extremely positive regarding the potential for regenerative agriculture. It’s very tempting to take these at face value. “Regenerative agriculture” just sounds wholesome (someone did a nice job of branding there), and the idea has a win/win appeal: simply by updating the way we manage our croplands, we can mitigate climate change and improve soil health, without significant cost.
However, on any topic that’s even mildly controversial, I’ve learned that it’s dangerous to repeat a conclusion if I’m not prepared to explain the facts and arguments that support it. I start to feel ownership of the idea. When I read contradictory evidence, I discount it. When challenged, my natural reaction is to double down; but since I don’t have a deep understanding to fall back on, this pushes me toward unproductive forms of argument.
Even for topics where there seems to be a clear correct answer, there will be people who disagree, and I’d like to be able to hold up my end of a detailed, thoughtful, fact-based discussion. Of course, we can hardly all take the time to become informed experts on every topic. So it’s important to pay attention to the distinction between “opinions I hold because I understand the objective facts and the arguments based on those facts” and “opinions I hold because someone I like espoused them”. If you’re parroting someone else’s conclusion without understanding how they got there, then you can’t explain it, defend it, recognize the level of uncertainty it reflects4, or update it to reflect new data. You can angrily repeat it on Twitter though! But maybe you shouldn’t.
Navigating Uncertainty
For topics where there is no expert consensus, how to proceed?
I touched on this in Why Everyone Disagrees About Climate. Sometimes, with some digging, it may become clear that one side of the dispute is simply out of date, or their arguments have been addressed, and a clear answer emerges.
Often there won’t be a clear answer. My intuition is that there is still value in wading into the messy, unanswerable questions. At a minimum, we can highlight the uncertainty, and try to delimit its boundaries. It may be possible to sharpen the conversation by highlighting the key points of debate. Or it may be possible to identify some conclusions we can draw despite uncertainty.
What is certainly true is that none of this will be possible without a lot of legwork. In Never Trust a Number, I argued that there are no shortcuts to understanding. This is especially true for unresolved, messy real-world questions like “how does the likely future supply of lithium match up with likely future demand”. By reading predigested opinions from experts, we can fast-forward the learning process a bit, but only a bit. It’s necessary to read a range of opinions, understanding the arguments and their merits.
This brings me back to the start: I’ve started having trouble coming up with new topics to blog about, because I’m running out of “easy” topics. I’m going to try diving deeper into the messy, quantitative, future-prediction questions. I expect that I won’t be posting as often, though I’ll probably come up with some research-lite pieces to mix in along the way. In the meantime, keep in mind:
Navigating climate change requires tackling a lot of messy, empirical, future-looking questions.
Don’t get too attached to any specific idea, especially ideas that you’re repeating without understanding.
But don’t just throw up your hands. Even when a question can’t be answered precisely, it can often be answered loosely, and we can get a lot done with that.
P.S. I just listened to David Roberts of Volts being interviewed by Jason Jacobs of My Climate Journey. It’s an outstanding exploration of how to think about the climate situation, and very accessible. Highly recommended for anyone who reads this blog. You can find it here (Volts) or here (MCJ).
I’d apologize for going meta on you, but look, that’s the risk you take when reading a blog written by a software engineer.
Or possibly “efficient”? No, honestly, “lazy”.
Obligatory Yogi Berra quote: “It's tough to make predictions, especially about the future.” Except it seems that this quote is actually Danish in origin. Yogi Berra, like Mark Twain, has become a sort of default attribution for all sorts of sayings. As he actually does seem to have said: “I really didn’t say everything I said”.
As ideas are passed along from one person to another, whether in print or otherwise, they tend to be expressed in more definitive ways. Caveats, qualifications, and error bars get overlooked. Some of this is just the general tendency for details to be dropped. But also, articles that sound more confident may be more likely to find their way into your inbox. All of the conscious and unconscious forces in the system push in the direction of simpler, more confident presentation of ideas.