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<reference>
Fake news, fast and slow:
Deliberation reduces belief in false (but not true) news headlines
In press at Journal of Experimental Psychology: General
DOI: http://dx.doi.org/10.1037/xge0000729
Bence Bago1*, David G. Rand2,3, & Gordon Pennycook4

1

Institute for Advanced Study in Toulouse, University of Toulouse Capitole
2
Sloan School, Massachusetts Institute of Technology
3
Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology
4
Hill/Levene Schools of Business, University of Regina

*Corresponding author: Bence Bago, Institute for Advanced Study in Toulouse, University of
Toulouse Capitole, 21 Allée de Brienne, 31015 Toulouse, France, e-mail:
bencebagok@gmail.com

Abstract
What role does deliberation play in susceptibility to political misinformation and “fake
news”? The “Motivated System 2 Reasoning” account posits that deliberation causes people
to fall for fake news because reasoning facilitates identity-protective cognition and is
therefore used to rationalize content that is consistent with one’s political ideology. The
classical account of reasoning instead posits that people ineffectively discern between true
and false news headlines when they fail to deliberate (and instead rely on intuition). To
distinguish between these competing accounts, we investigated the causal effect of reasoning
on media truth discernment using a two-response paradigm. Participants (N= 1635 MTurkers)
were presented with a series of headlines. For each, they were first asked to give an initial,
intuitive response under time pressure and concurrent working memory load. They were then
given an opportunity to re-think their response with no constraints, thereby permitting more
deliberation. We also compared these responses to a (deliberative) one-response baseline
condition where participants made a single choice with no constraints. Consistent with the
classical account, we found that deliberation corrected intuitive mistakes: subjects believed
false headlines (but not true headlines) more in initial responses than in either final responses
or the unconstrained 1-response baseline. In contrast – and inconsistent with the Motivated
System 2 Reasoning account – we found that political polarization was equivalent across
responses. Our data suggest that, in the context of fake news, deliberation facilitates accurate
belief formation and not partisan bias.

Keywords: fake news, misinformation, dual-process theory, two-response paradigm

2

Although inaccuracy in news is nothing new, so-called “fake news” – “fabricated
information that mimics news media content in form but not in organisational process or
intent” (Lazer et al., 2018, p. 1094 ) – has become a focus of attention in recent years. Fake
news represents an important test-case for psychologists: What is it about human reasoning
that allows people to fall for blatantly false content?
Here we consider this question from a dual-process perspective, which distinguishes
between intuitive versus deliberative cognitive processing (Evans & Stanovich, 2013;
Kahneman, 2011). The theory posits that intuition allows for quick automatic responses that
are often based on heuristic cues, while effortful deliberation can override and correct
intuitive responses.
With respect to misinformation and the formation of (in)accurate beliefs, there is
substantial debate about the roles of intuitive versus deliberative processes. In particular,
there are two major views: the “Motivated System 2 Reasoning” (MS2R) account and the
classical reasoning account. According to the MS2R account, people engage in deliberation
to protect their (often political) identities and to defend their pre-existing beliefs. As a result,
deliberation increases partisan bias (Charness & Dave, 2017; Kahan, 2013, 2017; Kahan et
al., 2012; Sloman & Rabb, 2019).1 In the context of evaluating news, this means that
increased deliberation will lead to increased political polarization and decreased ability to
discern true from false. Support for this account comes from studies that correlate
deliberativeness with polarization. For example, highly numerate people are more likely to be
polarized on a number of political issues, including climate change (Kahan et al., 2012) and
gun control (Kahan, Peters, Dawson, & Slovic, 2017). Furthermore, Kahan, Peters, Dawson,

1

Various accounts of motivated reasoning other than MS2R have been offered (e.g., Dawson,
Gilovich, & Regan, 2002; Haidt, 2001; Mercier & Sperber, 2011), and these accounts may
make differing predictions regarding the role of deliberation. Here we focus on the MS2R
account (Kahan, 2017), as this account makes clear and specific predictions about the
connection between greater deliberation and increased partisan bias.
3

and Slovic (2017) experimentally manipulated the political congruence of information they
presented to participants and found that the ratings of highly numerate participants responded
more to the congruence manipulation.
The classical account of reasoning, in contrast, argues that when people engage in
deliberation, it typically helps uncover the truth (Evans, 2010; Evans & Stanovich, 2013;
Pennycook & Rand, 2019a; Shtulman & McCallum, 2014; Stanovich, 2011; Swami,
Voracek, Stieger, Tran, & Furnham, 2014). In the context of misinformation, the classical
account therefore posits that it is the lack of deliberation that promotes belief in fake news,
while deliberation results in greater truth discernment (Pennycook & Rand, 2019a). Support
for the classical account comes from correlational evidence that people who are
dispositionally more deliberative are better able to discern between true and false news
headlines, regardless of the ideological alignment of the content (Pennycook and Rand
2019a; see also Bronstein, Pennycook, Bear, Rand, & Cannon, 2019; Pennycook & Rand,
2019b). Relatedly, it has been shown that people update their prior beliefs when presented
with evidence about the scientific consensus regarding anthropogenic climate change,
regardless of their prior motivation or political orientation (Van der Linden, Leiserowitz, and
Maibach (2018); see also Lewandowsky, Gignac, & Vaughan, 2013); and that training to
detect fake news decreases belief regardless of partisanship (Roozenbeek & van der Linden,
2019a, 2019b). Although not directly manipulating deliberation, these results suggest that
engaging in reasoning leads to more accurate, rather than more polarized, beliefs.
To differentiate between these motivated and classical accounts, the key question,
then, is this: When assessing news, does deliberation cause an increase in polarization or in
accuracy?
Here we shed new light on this question by experimentally investigating the causal
link between deliberation and polarization (MS2R) versus correction (classical reasoning).

4

Specifically, we used the two-response paradigm, in which participants are presented with the
same news headline twice. First, they are asked to give a very quick, intuitive response under
time pressure and working memory load (Bago & De Neys, 2019). After this, they are
presented with the task again and asked to give a final response without time pressure or
working memory load (thus allowing unrestricted deliberation). This paradigm has been
shown to reliably manipulate the relative roles of intuition and deliberation across a range of
tasks (e.g., Bago & De Neys, 2017, 2019; Thompson, Turner, & Pennycook, 2011).
The classical account predicts that false headlines – but not true headlines – should be
judged to be less accurate in deliberative (final) responses compared to intuitive (initial)
responses; and that this should be the case regardless of whether the headlines are politically
concordant (e.g., a headline with a Pro-Democratic lean for a Democrat) or discordant (e.g., a
headline with a Pro-Democratic lean for a Republican). In contrast, the MS2R account
predicts that politically discordant headlines should be judged to be less accurate – and
politically concordant headlines judged to be more accurate – for deliberative responses
compared to intuitive responses, regardless of whether the headlines are true or false.
Method
Data, preregistrations of sample sizes and primary analyses, and supplementary
materials are available on the Open Science Framework: https://osf.io/egy8p.
The preregistered sample for this study was 1000 online participants recruited from
Mechanical Turk (Horton, Rand, & Zeckhauser, 2011); 600 for the two-response experiment,
and 400 for a one-response baseline condition (participants in previous experiments of ours
on this topic were not allowed to participate). In total, 1012 participants were recruited (503
females, Mage = 36.9 years). The research project was approved by the University of Regina
and MIT Research Ethics Boards.

5

Participants rated the accuracy of 16 actual headlines taken from social media; four
each of Republican-consistent false, Republican-consistent true, Democrat-consistent false,
and Democrat-consistent true. Headlines were presented in a random order and randomly
sampled from a pool of 24 total headlines (from Pennycook and Rand, 2019a). For each
headline, participants were asked “Do you think this headline describes an event that actually
happened in an accurate way?” with the response options “Yes/No” (the order of Yes/No v.
No/Yes was counterbalanced across participants).
In the one-response baseline condition, participants merely rated the 16 headlines,
taking as long as they desired for each. In the two-response experiment, participants made an
initial response in which the extent of deliberation was minimized by having participants
complete a load task (memorizing a pattern of five dots in a 4X4 matrix, see Bago & De
Neys, 2019) and respond within 7 seconds (the average reading time in an N = 104 pre-test).
They were then presented with the same headline again – with no time deadline or load – and
asked to give a final response.
After rating the 16 headlines, participants completed a variety of demographics,
including the Cognitive Reflection Test (Frederick, 2005; Thomson & Oppenheimer, 2016;
CRT) and a measure of support for the Republican versus Democratic Party (which we used
to classify headlines as politically concordant versus discordant). See Supplementary
Materials for further methodological details.
We analyze the results using mixed-effect logistic regression models, with headlines
and subjects as random intercepts. Any analysis that is not preregistered is labeled as post
hoc. We necessarily excluded the 4.1% of trials where individuals missed the initial response
deadline. We also preregistered that we would exclude trials where individuals gave an
incorrect response to the load task, but we found a significant correlation between score on
the CRT and performance on the cognitive load task, r = 0.11, p < 0.0001. Thus, we kept the

6

incorrectly solved load trials to avoid a possible selection bias. Note that, for completeness,
we also ran the analysis with the preregistered exclusions and there are no notable deviations
from the results presented here (see Supplementary Materials). Furthermore, 14 participants
did not give a response to our political ideology question and were also excluded from
subsequent analyses. As preregistered, we excluded no trials when comparing the oneresponse baseline to the final response of the two-response paradigm to avoid selection bias
(apart from the 14 participants who did not answer the ideology question).

Results
Politically neutral pre-test. We begin by reporting the results of a pre-test that used
politically neutral headlines (N = 623; see Supplementary Materials for details). As there is
no motivation to (dis)believe these headlines, the straightforward prediction is that
deliberation would reduce the perceived accuracy of false (but not true) headlines. Indeed, in
the two-response experiment there was a significant interaction between headline veracity
and response number (initial vs final), b = 0.47, 95% CI = [0.29, 0.65], p < 0.0001. Similarly,
when comparing across conditions, there was a significant interaction between headline
veracity and condition (one-response baseline vs two-response experiment), using either the
initial response, b = 0.61, 95% CI = [0.42, 0.79], p < 0.0001, or final response, b = 0.23, 95%

7

CI = [0.04, 0.41], p = 0.018, from the two-response experiment (see Figure 1). Deliberation
increased ability to discern true versus false politically neutral headlines.

100

Neutral headlines
Initial response
Final response
One response baseline

Percent Rated as Accurate

90
80
70
60
50
40
30
20
10
0
False

True
Headline Veracity

Figure 1. Percentage of true versus false politically neutral headlines that subjects rated as accurate
across conditions. Error bars are 95% CIs.

Within-subject analysis. We now turn to our main experiment, where subjects judged
political headlines, to adjudicate between the MS2R and classical accounts (see Figure 2).
First, we compare initial (intuitive) versus final (deliberative) responses within the tworesponse experiment to investigate the causal effect of deliberation within-subject. Consistent
with the classical account, we found a significant interaction between headline veracity and
response number, b = 0.36, 95% CI = [0.2, 0.52], p < 0.0001, such that final responses rated
false (but not true) news as less accurate relative to initial answers. Moreover, inconsistent
with the MS2R account, there was no interaction between political concordance and response
number, b = 0.004, 95% CI = [-0.16, 0.17], p = 0.96, and no three-way interaction between
response type, political concordance, and headline veracity, b = 0.03, 95% CI = [-0.14, 0.21]
p = 0.72. Thus, people were more likely to correct their response after deliberation, regardless

8

of whether the item was concordant or discordant with their political beliefs. Naturally,
concordance had some effect – people rated politically concordant headlines as more accurate
than discordant ones, b = -0.21, 95% CI = [-0.34, -0.07], p = 0.003 – but this was equally true
for initial and final responses.
There was also a significant interaction between political concordance and headline
veracity, b = -0.3, 95% CI = [-0.47, -0.14], p = 0.0003, such that the difference between
politically concordant and discordant news was larger for real items than for fake items – that
is, people were more politically polarized for real news than for fake news – but, again, this
was equally true for initial versus final responses. Finally, we also found significant main
effects of veracity (perceived accuracy was lower for false than true news), b = 1.56, 95% CI
= [1.14, 1.98] p < 0.0001, and response type (perceived accuracy was lower for final than initial
responses), b = -0.38, 95% CI = [-0.52, -0.25], p < 0.0001.
We also examined the role of dispositional differences in deliberativeness (as measured
by performance on the CRT). As described in detail in the Supplementary Materials, we
replicated prior findings that people who scored higher on the CRT were better at discerning
true versus false headlines, and we found significant interactions with response number such
that this relationship between CRT and discernment was stronger for final responses than initial
responses (although still present for initial responses).

9

Political headlines
Initial response
Final response
One response baseline

Percent Rated as Accurate

100
80
60
40
20
0
False

True

Politically Concordant

False

True

Politically Discordant

Figure 2. Percentage of true versus false political headlines that subjects rated as accurate across
conditions and political concordance. Error bars are 95% CIs.

Between-subject analysis. Finally, we compare perceived accuracy ratings in the tworesponse experiment with ratings from the one-response baseline (see Figure 2). We first report
a post hoc analysis comparing the initial (intuitive) response from the two-response experiment
with the one-response baseline. This recapitulates a standard load/time pressure experiment, in
which some subjects respond under load/pressure while others do not. We found a significant
interaction between headline veracity and condition; b = 0.34, 95% CI = [0.17, 0.51], p <
0.0001; concordance and veracity; b = -0.31, 95% CI = [-0.48, -0.15], p = 0.0002; and veracity,
condition, and concordance, b = 0.21, 95% CI = [0.03, 0.39], p = 0.035. Load/time pressure
increased perceived accuracy of fake headlines regardless of political concordance. Load/time
pressure had no effect for politically concordant real headlines, but did decrease perceived
accuracy of politically discordant real headlines. Therefore, deliberation causes an increase in
truth discernment for both discordant and concordant headlines.
We conclude by comparing the final (deliberative) response from the two-response
experiment with the one-response baseline. This allows us to test whether forcing subjects to
10

report an initial response in the two-response experiment had some carryover (e.g. anchoring)
effect on their final response. Although there was no significant interaction between veracity
and condition, b = 0.03, 95% CI = [-0.14, 0.2] p = 0.74, there was a significant interaction
between veracity and concordance b = -0.28, 95% CI = [-0.44, -0.11], p = 0.0009, and a
significant three-way interaction between veracity, condition, and concordance, b = 0.19, 95%
CI = [0.01, 0.37], p = 0.037. Politically discordant items showed an anchoring effect whereby
perceived accuracy of fake headlines was lower – and perceived accuracy of real headlines was
higher – for the one-response baseline relative to the final response of the two-response
condition. For politically concordant items, however, there was no such anchoring effect.
Together with the significant anchoring effect among politically neutral headlines observed in
our pre-test, this suggests that there is something unique about politically concordant items
when it comes to anchoring.
Discussion
What is the role of deliberation in assessing the truth of news? We found experimental
evidence supporting the classical account over the MS2R account. Broadly, we found that
people made fewer mistakes in judging the veracity of headlines – and in particular were less
likely to believe false claims – when they deliberated, regardless of whether or not the
headlines aligned with their ideology. Conversely, we found no evidence that deliberation
influenced the level of partisan bias/polarization.
Theoretical implications
These observations have important implications for both theory and practice. From a
theoretical perspective, our results provide the first causal evidence regarding the “corrective”
role of deliberation in media truth discernment. There has been a spirited debate regarding the
role of deliberation and reasoning among those studying misinformation and political
thought, but this debate has proceeded without causal evidence regarding the impact of

11

manipulating deliberation on polarization versus correction. To our knowledge, our
experiment is the first that enables us to do so – and provides clear support for the classical
account of reasoning.
Limitations and future directions
Using similar methods to test the role of deliberation in the continued influence effect
(CIE, Johnson & Seifert, 1994), wherein people continue to believe in misinformation even
after it was retracted or corrected (Lewandowsky, Ecker, Seifert, Schwarz, & Cook, 2012), is
a promising direction for future work. So too is examining the impact of deliberation on the
many (psychological) factors which have been shown to influence the acceptance of
corrections, such as trust in the source of original information (Swire, Berinsky,
Lewandowsky, & Ecker, 2017), underlying worldview or political orientation (Ecker & Ang,
2019), and strength of encoding of the information (Ecker, Lewandowsky, Swire, & Chang,
2011). For example, deliberation might make it easier to accept corrections and update
beliefs. Relatedly, the computations taking place during deliberation are underspecified, and
therefore future work could benefit from developing formalized, computational models that
better characterize underlying computations, such as the Decision by Sampling model
(Stewart, Chater, & Brown, 2006).
One limitation of the current work is that it was conducted on non-nationally
representative samples from MTurk. However, it is not imperative for us to have an
ideologically balanced/representative sample, as we are not making comparisons between
holders of one ideology versus another. Instead, we investigate motivated reasoning – which
should apply to both Democrats and Republicans – by comparing discordant versus
concordant headlines (collapsing across Democrats and Republicans). It would be interesting
for future work to replicate our results using a more representative sample to investigate the
potential for partisan asymmetries in the impact of deliberation.

12

Another potential concern is that our sample may not contain the people who are the
most susceptible to misinformation, given that the baseline levels of belief in fake news we
observe are low (Kahan, 2018). This problem is endemic in survey-based research on
misinformation. Future work could potentially address such issues by using advertising on
social media to recruit participants who have actually shared misinformation in the past.
Practical implications
From a practical perspective, the proliferation of false headlines has been argued to
pose potential threats to democratic institutions and people, by increasing apathy and
polarization or even inducing violent behavior (Lazer et al., 2018). Thus, there is a great deal
of interest around developing policies to combat the influence of misinformation. Such
policies should be grounded in an understanding of the underlying psychological processes
that lead people to fall for inaccurate content. Our results suggest that fast, intuitive (likely
emotional; Martel, Pennycook, & Rand, 2019) processing plays an important role in
promoting belief in false content – and therefore that interventions that promote deliberation
may be effective. Relatedly, this suggests that the success of fake news on social media may
be related to users’ tendency to scroll quickly through their newsfeeds, and the use of highly
emotionally engaging content by authors of fake news. Most broadly, our results support the
conclusion that encouraging people to engage in more thinking will be beneficial rather than
harmful.

Acknowledgments
We gratefully acknowledge funding from the Ethics and Governance of Artificial Intelligence
Initiative of the Miami Foundation (DGR and GP), the William and Flora Hewlett
Foundation (DGR and GP), the Social Sciences and Humanities Research Council of Canada
(GP), ANR grant ANR-17-EURE-0010 (Investissementts d’Avenir program, BB), ANR
Labex IAST (BB) and the Scientific Research Fund Flanders (FWO-Vlaanderen, BB).
Author note
Data, headlines and the supplementary materials are openly available at the project’s OSF
page: osf.io/egy8p.
13

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18
</reference>

<statements>
1. For fake news, deliberation reduces belief in false headlines regardless of political concordance, and the mechanism is framed as lack of reasoning rather than closure
2. The fake-news load study did not measure NFC
3. The fake-news deliberation study used non-nationally representative MTurk samples and may have missed people most susceptible to misinformation
4. Interventions that promote deliberation or inoculation may reduce misinformation, but neither directly tests NFC
</statements>

Begin the assessment now. Output only the JSON list, without any conversational text or explanations.