Recognizing and addressing some of the pressing challenges we face as human society, including global health and climate change, requires trust in science. Philosophers of science have argued that people should trust science for its epistemic qualities–its capacity to produce accurate knowledge. Under this premise, the literature on public understanding of science has long sought to explain people’s trust in science by their knowledge of it–with sobering results: While people do tend to trust science, they do not tend to know much about it. If not grounded in knowledge, is public trust in science mostly irrational? In this thesis, I argue that no, not necessarily. From a cognitive perspective, this thesis aims to provide an explanation of the foundations of trust in science at the micro-level. I develop a ‘rational impression’ account of trust in science, according to which people do not need to understand or remember much about science to trust it. The account builds on two basic cognitive mechanisms of information evaluation: First, if someone finds out something that is hard-to-know, we tend to be impressed by it, if we believe it is true. This impression makes us infer that the person is competent, a crucial component of trustworthiness. Second, if something is highly consensual, we tend to infer that it is likely to be true, and that those who agree are competent. These inferences from consensus are particularly relevant in the context of science, where most people lack relevant background knowledge to evaluate claims for themselves. Scientists agree on hard-to-know findings such as the size of the milky way or the atomic structure of DNA. Although most people do not understand much of how the scientists came to make these findings, nor remember the details of the findings, the consensus provides good reasons to trust the scientists. This account underlines the critical role of education and science communication in fostering trust in science.
The rational impression account for trust in science is built on the hypothesis that people tend to be good at evaluating information, by relying on mechanisms of epistemic vigilance. In Chapter 7, I explore another consequence of this hypothesis, which is that people should be good at judging the veracity of news. In a meta-analysis, we found that this was largely the case: people around the world were generally able to distinguish true from false news. When they erred, people were slightly more skeptical towards true news than they were gullible towards false news. We do not conclude from these results that all misinformation is harmless, but that people don’t simply believe all misinformation they encounter–if anything, they tend to have the opposite tendency to not believe information, even if accurate. Based on this, we argue that if we are concerned about an informed public, we should not only focus on fighting against misinformation, but also on fighting for accurate information.
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