Fake news & bad science journalism: the case against insincerity

Philosophers and social scientists largely agree that fake news is not just necessarily untruthful, but necessarily insincere: it’s produced either with the intention to deceive or an indifference toward its truth. Against this, I argue insincerity is neither a necessary nor obviously typical feature of fake news. The main argument proceeds in two stages. The first, methodological step develops classification criteria for identifying instances of fake news. By attending to expressed theoretical and practical interests, I observe how our classification practices turn on worries about fake news’s unique political-epistemic risks. From this, I argue (i) theories of fake news should capture independent mechanisms that realise these risks and (ii) the manifestation of them suffices for classifying a news story as fake news. The second step applies the classification criteria to bad science journalism. I argue the systematic epistemic faults in bad science journalism manifest the same political-epistemic risks we see in fake news, which suffices to justify classifying it as fake news. But since such faults aren’t plausibly attributed to its propagators being insincere, insincerity doesn’t function independently as a mechanism for realising fake news’s political-epistemic risks. Thus, I conclude, we should exclude insincerity from our accounts of the phenomenon.