Today's post is by Vanessa Schipani (University of Pennsylvania) who discusses a recent open access paper on journalism and public trust in science published in Synthese. A version of this post has appeared on the LSE blog on 2 September 2024.
Vanessa Schipani |
During the 2016 U.S. presidential election, I was hired as a journalist to report on politicians’ claims about science for FactCheck.org. Coming off of finishing a master’s in the history and philosophy of science, my eye for stories was a bit more philosophical than most.
Starting with my first article on whether climate science was pseudoscience (spoiler: it’s not), I noticed a trend in how politicians misunderstood the scientific process, especially when arguing for policy inaction: They set the bar for action at certain results, and condemned researchers when they offered their opinions about policies.
Now on the cusp of finishing a dissertation on trust in science, I see more clearly the trick these politicians (and the tobacco industry executives who came before them) were playing: If you set the bar for action at an unachievable level (certainty), then you never need to act. Unfortunately, many members of the public fell for this trick because a certain image of science permeates popular culture.
In our films, classrooms, and, yes, in our journalistic reporting, we portray scientists as depositories of indisputable, value-free facts, trustworthy only when in consensus. So, when scientists disagree, aren’t certain or share their values publicly, we think we shouldn’t trust them. As many philosophers of science, including myself, agree, this view of science is mistaken.
In a recent paper published in Synthese, I outline how this image of science makes it difficult for journalists to abide by their trade’s norms when reporting on scientific disagreement. By integrating social science research on science communication and philosophical work on trust in science, I also offer a solution to this problem – what I call the responsiveness model of trust in science. Journalists need the responsiveness model to ethically carry out their work. They’re also crucial to the model’s success.
These are two central journalistic norms: Good journalists care about maximizing their reporting’s accuracy. They also care about minimizing its harm. But when they accurately report scientific disagreement, there’s a reasonable chance their coverage might lead to distrust of science, as recent research on communicating scientific uncertainty suggests. In many policy-relevant cases, this distrust could lead tangible harm, such as not wearing a mask when doing so may prevent a deadly virus’ spread.
How can we overcome this problem? We need to shift the public’s image of science, which is what I designed the responsiveness model to do. The model instructs journalists to communicate reasons that warrant the public’s trust in scientists that go beyond certainty, value-freedom and consensus. Instead, when journalists report disagreement, they can explain that we should trust scientists when they exhibit a critical responsiveness to evidence as well as to the public’s values.
Importantly, journalists also need to verify and communicate whether scientists are, in fact, being responsive. In doing so, they perform one of their central democratic duties – acting as the public’s watchdogs. In other words, the model tells journalists to report on the process of science, instead of just its product (knowledge). Alas, this is something journalists have historically not done. This needs to change.