I'm adding my voice to the clamor
- Because our new administration has, at best, contradictory views on climate change and science
- Because 80% of scientists say that the general public’s lack of understanding about the nature of science contributes to the controversy surrounding climate change
- Because moderate views are endangered in politics and lots of other places including climate science and reporting
I hope you'll stick with this even though it's long. Sound bytes can sometimes do us an incredible disservice, and there are no shortcuts out of here. I’d go so far as to say one reason we’re in this pickle is because we’re overly enamored of shortcuts.
This is a prismatic overview of how and why science works, how facts transform into "alternatives," and the science of climate change. I’ll split each into its composite parts so we can study the paths and chase down origins and, of course, fact.
Origins matter. When you can’t divide something any further, its nature is revealed and we stand at the feet of truth.
*|| CHOOSING SIDES ||*
Regardless of what side you’re on in any given argument, you should be alarmed by partisan facts.
Through some freaky cultural alchemy, we (and our candidates and news sources) are now able to point at a square and say, “nope, that’s a strawberry,” and no amount of hard evidence presented to counter is sufficient to draw out a retraction.
I feel comfortable defining that as a literal act of insanity.
We need to make facts bipartisan again, and I’m going to start here with science and eventually move into climate change, because its important and validity has recently come up.
*|| DEFINING FACT AND SCIENCE ||*
A fact is something that has existence, is objective and immutable; in short, it’s the truth. The “objective” part is particularly important.
SCIENTIFIC PROCESSES ARE HOW WE DISCOVER FACTS. Your 8th grade textbook defines science as the process of observation, explanation, reasoning, testing, and predicting, to discover fact. It sounds like such a clean process, moving linearly from question to conclusion, full stop.
Real-world science is rarely linear, and it’s riddled with uncertainty because the world is an incredibly complicated place. Every new piece of understanding we unearth shines more light on all the things we don’t know—which is not something to fear! Uncertainty is a huge reason why good scientists will always account for the fact that there’s more to learn. Admitting uncertainty doesn’t undermine the validity of discovery; it’s proof of responsibility, because hubris is the enemy of impartiality and inquiry.
Facts must be impartial.
That’s why you’ll almost never get a scientist to say that they’re “100% certain” about anything, and I believe that stance can mystify people who aren’t scientists. From the outside looking in, seeing experts who “aren’t sure” about something big and important like our world changing is really frightening. They’re the experts! If they don’t know, then who does…?
The truth is, scientists usually know more than anyone else, but it may not look like that to non-scientists. Also, a lot of scientists are genuinely awful at talking about what they do.
So yes, we must acknowledge that the discovery of facts comes from an imperfect system, but it’s the best system and scientific processes (Observation! Testing! Retesting! Data series!) are designed to account for and minimize our fallibility.
*|| MODELS ||*
In order to be very certain of something and get over that fallibility hump, science needs a lot of time for tons of information to be collected, which can suck because we usually need to make a decision about what to do right now. Our problems aren’t going to wait fifty years while we collect a really robust data set. It’s go time.
That’s where models come in. A scientific model is in some ways similar to a model plane: it’s a fraction of the size and it tries to capture as many of the real-life details as possible. Scientific models are a representation of a real-life process that's difficult to study because it’s so large (like ocean currents) or it happens over a long time scale. There are many kinds of models, but in this case, I'm talking about predictive models, which rely on data from past events to create predictions for the future. Scientists take the data from years of measurements and build an equation that explain those data, while ALSO including math that helps capture more recent changes.
Then, they use the equation to predict how events will turn out in the future. Models usually give you a range of possibilities, like a weather report.
Models are like the Cliff Notes version of science; they give you a general idea of what’s happening, but if you’re writing a final paper worth 50% of your grade, you can’t rely on Cliff Notes. It’s the same thing with predictive models. They’re useful when time is short, but to generate quick answers, models can end up sacrificing accuracy.
When a layperson or newscaster or politician sees a model, it’s easy to assume that’s what’s going to happen or choose one extreme end of the model, because extremes are interesting and newsworthy. But, if a certain scenario doesn’t happen, well, people become more distrustful of science. Scientists hate creating fifty year predictions because it’s pretty darn likely that the model will be wrong in some significant way. Unfortunately, decision makers and money allocators and policy implementers need to know whether to worry about it right this very minute, or can we put it off for a while?
I’m making this whole “science” thing sound really terrible, aren’t I? Like it’s this wishy-washy process where the only results are men in white coats cashing grant checks and going ¯\_(ツ)_/¯
It’s not, though. It’s one of the most powerful processes in the universe, and it’s helped us tremendously as a species. I can say with full confidence that science is also going to be responsible for a huge portion of any future successes we have.
I’m breaking this down so non-scientists understand the strengths and weaknesses of the scientific process so we all have a basic understand of the results of science. I don’t think the solution to facts becoming partisan is to put blind faith in experts; I think the answer is for all us to become scientists: to embrace skepticism, give up cynicism, and to always ask questions.
*|| COMING SOON: FACT DRIFT ||*
Part II will focus on how facts get bent out of shape, and what kind of effect that has on science and policy.