The 'Problem' With Science

Photo by Guillaume Henrotte on Unsplash

We tend to have this view that science is a ‘fixed’ subject, in the sense that we think of it as defined and permanent in nature. That once scientists have done their thing, that once the facts surrounding a specific topic have been gathered and a perspective has been reached, then that’s it. We’re done.

Of course, that’s not actually the case. Science evolves, it changes and is subject to refinement. That’s actually the value of the scientific process - that as more data is captured, as we see the interplay of different variables over time, we learn more. And in doing so, we further prove or disprove our original hypotheses. And then we adjust our recommendations accordingly. 

We’ve seen this at play most recently with COVID-19, where in the early days, scientists had some ideas about the virus, but not enough to make any absolute conclusions. So the advice was broad and loose. As they learned more, they refined their thinking and were able to suggest more focused recommendations. (Clearly, we’re still not there in terms of knowing everything we need to know, so the ‘learning’ is still in process.)

This idea is frustrating to many and understandably so. We love certainty, we hate ambiguity. We want to know for sure if we should do this or that. We want to be told what we should do and once we do that, we don’t like to be told that we need to change. 

But the reality is that there is no such thing as ‘permanent’. (Cue the cliched joke about death and taxes.) There is no such thing as fixed. There is our best knowledge to date - what we know at this time with the data available to us, from the best possible sources that are accessible by us.

That last part - at this time with the data available to us from the best possible sources accessible by us - is important and has to inform our thinking. It tells us to keep an open mind in terms of data, in terms of sources, in terms of what we expose ourselves to. It tells us to be critical, to be thoughtful, but it also tells us that we need to be open to change, especially as the dataset gets better and our understanding is refined. (When you put it that way, the idea of science not being a fixed or static subject makes a lot of sense, right?) 

Funnily enough, this same underlying principle applies equally as much, if not more so, to our own thinking. That as we learn more, we should evolve our own mental models. The ones we make our own decisions with. The ones we use to do the work we do. The ones we use to judge ourselves, and others. 

Those models were taught to us by someone, at some point in time, on the basis of data (and ideas and analyses) available to them at the time. The structure and quality of those models was shaped by a range of factors, from their education, their environment, their families, their experiences and their state of mind, to name a few. We took all of that input and shaped our own thinking on the basis of all of these factors, which were further compounded by all of our own influencing factors, which resulted in our resulting mental models.

Some of those interpretations were valid and helped us get to where we are. But it’s also quite possible that some of them aren’t fit-for-purpose anymore. 

That perhaps our ‘science’ needs a bit of a rethink. That perhaps it’s time to open ourselves to more and different sources, different environments, different experiences. 

Ones that might make us uncomfortable, possibly even scared. 

Ones that might change our defining assumptions, and hence our world view. 

Ones that require us to engage in some difficult work, but ultimately take us to a better place, with better conclusions, forcing us to “do better”, now that we “know better”.