In modern times we experience regular public exchanges of opinion, whether about COVID-19 policies, humanity’s influence on climate, or whether or not the local jail needs replacing.  When arguing in the public sphere, opposing sides each frame their take on a subject and present supporting arguments and facts.  Unfortunately, this is often where the discussion ends. 

There are cynical reasons for the perpetual arguments—someone benefits.  But cynicism aside, is there something we can do to improve public discussion and make positive progress?

The more frankly we interrogate our data, assigning appropriate error limits, the more we can learn from them. 

In my engineering classes, I spend quite a bit of time encouraging students to observe and note down the process of learning.  There are things to learn in class, of course, but it would be a shame not to use the opportunity of learning something new to teach ourselves about how one learns something new.  What is that process?  Well, we confront a new situation, we ask questions, we try out solutions or pathways to solution, and we pick something to try.  Then, we see if it works.  If it works, we win!  If it does not work, we review how we got to the non-working solution, and we try something else.  We are only finished when we find an answer that works.

How does this anecdote help us to address the problem of stalled public discourse? 

Let’s compare public discourse to the STEM classroom.  We start with a topic, which is usually something wrong in society that someone asserts needs to be addressed or changed.  Let’s use climate change as an example.  According to my description of the classroom process, once the topic has been raised, the next step is to ask questions and identify solutions and pathways to solution.  That works for public discussion of climate change.  The next step is to pick something to try.  This seems to be the moment when public discourse breaks down—we can’t agree on what to try. 

Why does public discussion break-down at this step while the scientific-engineering process moves forward?  Well, it would be revisionist history to say that scientific discovery progresses smoothly.  Science is performed by people, after all, and the same conflicts that beset public discussions rankle in science too.  Germ theory, espoused by Louis Pasteur, was roundly mocked when presented to the great minds of the 19^th century.

What makes the difference, then?  Well, in the case of germ theory, it made a difference that Pasteur was right.  Germs do cause disease, and the hygiene protections that the theory suggests do work to reduce disease spread.  So, the difference is that there can be hard measurements made and correctly interpreted to lead us to positive progress.

Thus, I arrive at my suggestion for the public discourse problem—hard measurements correctly interpreted.  And perhaps a bit of patience.  It took years for the germ theory to be accepted.  These years were spent taking data, interpreting them or improving them, and seeing what it all added up to. 

It may be a bit tough to be patient, given what’s at stake with some of the questions we are debating in the public sphere.  One aspect that may help to accelerate the process of getting it right is to encourage widespread familiarity with the nature of measurements and with the uncertainty that is unavoidable in hard measurements.  The more frankly we interrogate our data, assigning appropriate error limits, the more we can learn from them.  We should not imagine that they are more definitive than they are—we may miss or misstate the truths that they contain.  Widespread literacy on the topic of uncertainty in measurements would go a long way in improving public discourse on the topics that divide us.