Decision Processes Colloquia

The 2016 US Presidential Election brought considerable attention to the phenomenon of “fake news”: entirely fabricated and often partisan content that is presented as is from a legitimate source. In this talk, I will explore two outstanding questions about fake news: Who falls for it, and what can be done to fight it? It is typically assumed that people believe fake news stories that are consistent with their political ideology because they engage deliberative reasoning to convince themselves that even the most fantastical of fabrications are plausible (i.e., motivated reasoning). This account predicts that particularly analytic individuals will be more likely to believe politically congruent than those who are particularly intuitive a pattern of results that has been observed previously in the context of climate change risk perceptions (Kahan et al., 2012). However, in a first set of experiments, we find the opposite pattern: Relatively analytic individuals were less likely to fall for even politically congruent fake news. In fact, at least among Democrats, people were better able to discern real from fake news if the headlines were congruent with their political ideology. These results suggest that, rather than backfiring, interventions intended to initiate analytic thinking about accuracy or plausibility may in fact decrease the partisan sharing of fake news. In a second set of experiments, we demonstrate the effectiveness of such interventions. We find that asking participants to judge the accuracy of each story prior to deciding whether they would share it on social media dramatically reduces the likelihood of fake news being shared. Furthermore, merely asking individuals to judge the accuracy of a single politically neutral news story (either fake or real) in a purported pretest was sufficient to decrease sharing of fake news stories (but not real news stories), doubling participants’ ability to discriminate between fake and real. This approach appears to be more promising than the main intervention introduced by Facebook – adding “disputed by 3rd party fact-checkers” warnings to stories known to be fake – which we show to be wanting in two additional experiments.