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\title{Dual processes and moral conflict: Evidence for deontological reasoners’ intuitive utilitarian sensitivity}

\author{
Michał Białek\thanks{Kozminski University, Department of Economic
Psychology, Centre for Economic Psychology and Decision Sciences,
Jagiellońska 59, 03--301, Warsaw, Poland. Email: mbialek@kozminski.edu.pl.}
\and
Wim De Neys\thanks{LaPsyDE (CNRS Unit 8240), Sorbonne --- Université
Paris Descartes, Sorbonne --- Labo A. Binet 46, rue Saint Jacques,
75005 Paris, France. Email: wim.de-neys@parisdescartes.fr.}
}

\date{} % leave empty
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\newcommand{\jhead}{Judgment and Decision Making, Vol.~12, No.~2}
\newcommand{\jdate}{March 2017}
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  \jdate \hfill Dual processes and moral conflict \qquad}
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\href{\jref}{\jhead}, \jdate, pp.\ 148-167
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{\small \href{\jref}{\jhead}, \jdate, pp.\ 148--167}
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\maketitle

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\vspace{-3mm}
\begin{onecolabstract}
%\end{latexonly}
The prominent dual process model of moral cognition suggests that
reasoners intuitively detect that harming others is wrong
(deontological System-1 morality) but have to engage in demanding
deliberation to realize that harm can be acceptable depending on the
consequences (utilitarian System-2 morality). But the nature of the
interaction between the processes is not clear. To address this key
issue we tested whether deontological reasoners also intuitively grasp
the utilitarian dimensions of classic moral dilemmas. In three studies
subjects solved moral dilemmas in which utilitarian and
deontological considerations cued conflicting or non-conflicting
decisions while performing a demanding concurrent load task. Results
show that reasoners’ sensitivity to conflicting moral perspectives, as
reflected in decreased decision confidence and increased experienced
processing difficulty, was unaffected by cognitive load. We discuss how
these findings argue for a hybrid dual process model interpretation in
which System-1 cues both a deontological and utilitarian intuition.

\smallskip
\noindent
Keywords: utilitrianism, deontology, dual-system theory, moral judgment, cognitive load.
%\begin{latexonly}
\end{onecolabstract}\bigskip
]
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{\renewcommand{\thefootnote}{}

\footnotetext{



Copyright: \copyright\ 2017.
The authors license this article under the terms of the
\href{http://creativecommons.org/licenses/by/3.0/}{Creative Commons
  Attribution 3.0 License.}
}}

\saythanks

\section{Introduction}

Moral dilemmas often force us to decide between so-called deontological
and utilitarian considerations. Imagine, for example, that by torturing
a captured terrorist we can obtain critical information that allows us
to prevent a planned attack that would kill dozens of innocent
citizens. Unfortunately, this example is not so hypothetical. We wrote
this paper in the aftermath of the Paris and Brussels terror attacks.
One of the members of the ISIS terrorist cell that planned both
attacks, Salah Abdeslam, was arrested a couple of days before his
partners put their plans into action and killed 32 people in suicide
bombings at Brussels airport and metro. There was quite some outrage –
voiced among others by Donald J. Trump - over the fact that authorities
had not used “all means possible” to get Abdeslam to confess the
upcoming attack (Diamond, 2016). But even if we assume that torturing
Abdeslam would have prevented the attack, would it therefore be morally
acceptable? Someone who takes a utilitarian point of view would say
“yes”. The moral principle of utilitarianism implies that the morality
of an action is determined by its expected consequences. Therefore, harming an
individual will be considered acceptable if it prevents comparable
harms to a greater number of other people. Although torture might
be intrinsically bad, it will nevertheless be judged morally acceptable
in this case because of the lives it saves (i.e., one chooses the
“greater good”). Alternatively, the moral perspective of deontology
implies that the morality of an action depends on the intrinsic
nature of the action. Here harming an individual is considered wrong
regardless of its consequences and potential benefits. Hence, from a
deontological point of view, the use of torture would always be judged
unacceptable. 

In the last two decades psychologists, philosophers, and economists have
started to focus on the cognitive mechanisms underlying utilitarian and
deontological reasoning (e.g., Białek \& Terbeck, 2016; Białek,
Terbeck \& Handley, 2014; Greene, 2015; Conway \& Gawronski, 2013,
Kahane, 2015; Moore, Stevens \& Conway, 2011; Nichols, 2002; Valdesole
\& Desteno, 2006). A lot of this work has been influenced by the
popular dual-process model of thinking (Evans, 2008; Kahneman, 2011),
which describes cognition as an interplay of fast, effortless,
intuitive (i.e., so called “System 1”) processing and slow,
working-memory dependent, deliberate (i.e., so-called “System 2”)
processing. Inspired by this dichotomy the dual process model of moral
reasoning (Greene, 2014; Greene \& Haidt, 2002) has associated
utilitarian judgments with deliberate System 2 processing and
deontological judgments with intuitive System 1 processing. The basic
idea is that giving a utilitarian response to moral dilemmas usually requires
System 2 thinking and allocation of cognitive resources
to override an intuitively cued deontological System 1 response that
primes us not to harm others. 

\pagebreak

In support of the dual process model of moral reasoning it has been
shown that people higher in working memory capacity tend to be more
likely to make utilitarian judgments (Moore, Clark \& Kane, 2008).
Also, experimental manipulations that limit response time (Suter \&
Hertwig, 2011) or cognitive resources (Conway \& Gawronski, 2013;
Trémolière, De Neys, \& Bonnefon, 2012) sometimes make utilitarian
judgments less likely. These findings give some backing to the basic
dual process claim that utilitarian responding typically results from
slow and demanding System 2 processing whereas deontological
responding typically results from fast and more effortless System 1
processing (but see, for failed attempts and doubts, Baron, 2017;
Baron, Scott, Fincher \& Metz, 2015; Kahane, 2015; Klein, 2011;
Tinghög et al., 2016; Trémolière \& Bonnefon, 2014).

However, the precise nature of the interaction between the two types
of processes is not clear (Białek \& De Neys, 2016; Gürçay \& Baron,
2017; Koop, 2013).  To illustrate this point, consider the question of
whether or not deontological responders also detect that there are
conflicting responses at play in moral dilemmas. That is, do
deontological responders blindly rely on the intuitively cued
deontological System 1 response without taking utilitarian
considerations into account? Or, do they also realize that there is an
alternative to the cued deontological response, consider the
utilitarian view but simply decide against it in the end? These two
possibilities can be linked to two different views on the nature of
the interaction between System 1 and System 2 in dual process models:
a serial or parallel one.

In a serial model (often also called a “default-interventionist”
model, Evans \& Stanovich, 2013) it is assumed that people initially
rely exclusively on the intuitive System 1 to make judgments. This
default System 1 processing might be followed by deliberate System 2
processing in a later stage but this is optional. Indeed, serial dual
process models often characterize human reasoners as cognitive misers
who try to minimize cognitive effort and refrain from demanding System
2 processing as much as possible (Kahneman, 2011; Evans \& Stanovich,
2013). Under this interpretation only utilitarian responders will
engage in the optional System 2 processing. Deontological responders
will stick to the intuitively cued System 1 response. Since taking
utilitarian considerations into account is assumed to require System 2
processing, this implies that deontological responders will not have
experienced any conflict from the utilitarian side of the
dilemma. However, in a parallel dual process model (e.g., Epstein,
1994; Sloman, 1996) both processes are assumed to be engaged
simultaneously from the start.  Under this interpretation,
deontological and utilitarian responders alike would always engage
System 1 and 2. Although deontological responders will not manage to
complete the demanding System 2 process and override the intuitive
System 1 response, the fact that they engaged System 2 would at least
allow them to detect that they are faced with conflicting
responses.\footnote{One can envisage further sub-types of serial and
  parallel models. Indeed, the fact that the two systems are activated
  in parallel does not necessarily imply that conflict will be
  detected or felt (e.g., one might envisage that the System 2
  computations need not only be engaged but also completed before
  conflict can be experienced). Here, we consider a parallel model in
  which engagement of System 2 does suffice for the experience of
  conflict (e.g., Sloman, 1996).}

% "detection" not the issue

A number of recent empirical studies have started to test these
different conflict predictions of the serial and parallel dual
process model of moral reasoning. In one study Białek and De Neys
(2016) contrasted subjects’ processing of conflict and no-conflict
dilemmas. Moral reasoning studies typically present subjects with
dilemmas in which they are asked whether they would be willing to
sacrifice a small number of persons in order to save several more
(e.g., kill one to save five). In these classic scenarios utilitarian
and deontological considerations cue conflicting responses (hence,
conflict dilemmas). Białek and De Neys also reversed the dilemmas by
asking subjects whether they would be willing to sacrifice more
people to save less (e.g., kill five to save one). In these no-conflict
or control dilemmas both deontological and utilitarian considerations
cue the exact same decision to refrain from making the sacrifice. By
contrasting processing measures such as response latencies and response
confidence when solving both types of dilemmas, one can measure
subjects’ conflict sensitivity (e.g., Botvinick, 2007; De Neys,
2012). If deontological responders are not considering utilitarian
principles, then the presence or absence of intrinsic conflict between
utilitarian and deontological considerations should not have an impact
on their decision making process. However, Białek and De Neys observed
that deontological responders were significantly slower and less
confident about their decision when solving the conflict dilemmas. In
contrast with the serial model predictions, this suggests that they
have to be considering both deontological and utilitarian aspects of
their decision. 

Related evidence against the serial model comes from the
mouse-tracking studies by Koop (2013; see also Gürçay \& Baron, 2017,
for a recent replication). After having read a moral dilemma, subjects
had to move the mouse pointer from the centre of the screen towards
the utilitarian or deontological response option presented in the
upper left and right corner to indicate their decision. In the
mouse-tracking paradigm researchers typically examine the curvature in
the mouse movement to test whether the non-chosen response exerts some
competitive “pull” or attraction over the chosen response (Spivey,
Grosjean \& Knoblich, 2005). One can use this attraction as a measure
of conflict detection. That is, if deontological reasoners are not
considering the utilitarian response option they can be expected to go
straight towards the deontological response option. If they are also
considering the utilitarian perspective, they will tend to slightly
move towards it resulting in a more curved mouse trajectory. Bluntly
put, people will reverse from one direction to the other reflecting
their “doubt”. Koop observed that mouse trajectories were indeed more
curved when solving conflict dilemmas vs control problems. But
critically, this effect was equally strong for utilitarian and
deontological responders. This suggests that, just like utilitarian
responders, deontological responders were considering and attracted by
both perspectives. As Koop argued, this pattern is more consistent
with a parallel than with a serial dual process model (also argued by
Gürçay \& Baron, 2017).

The evidence for deontological reasoners’ utilitarian sensitivity argues
against the serial dual process model. However, the evidence does not
suffice to declare the parallel model the winner. Note that both the
serial and parallel model are built on the assumption that utilitarian
reasoning is demanding and requires System 2 thinking. The parallel
model entails that it will be this deliberate thinking that allows
people to consider the utilitarian aspects of the dilemma and detect
the conflict with the intuitively cued deontological response. But,
clearly, the fact that deontological responders feel conflict does
not in and by itself imply that this experience results from System 2
engagement. An alternative possibility is that deontological responders
experience conflict between two different System 1 intuitions. In other
words, under this interpretation taking utilitarian considerations into
account might also be an intuitive System 1 process that does not
require deliberation. Hence, rather than a System 1/System 2 conflict
between an intuitive and more deliberated response that the parallel
model envisages, the experienced conflict would reflect a System 1/System
1 clash between two different types of intuitions, one deontological in
nature and the other utilitarian in nature.

Interestingly, there have been a number of theoretical suggestions
that alluded to the possibility of such intuitive utilitarianism in
the moral reasoning field (e.g., Dubljević \& Racine, 2014; Kahane et
al., 2012; Trémolière \& Bonnefon, 2014). In addition, generic dual
process research in the reasoning and decision-making field has
recently pointed to a need for so-called hybrid dual process models as
alternative to purely serial or parallel models (De Neys, 2012;
Handley \& Trippas, 2015; Pennycook, Fugelsang \& Koehler, 2015). The
brunt of these models is that operations that are traditionally
assumed to be at the pinnacle of System 2 (e.g., taking logical or
probabilistic principles into account), can also be cued by System
1. At a very general level, these findings lend some minimal credence
to the possible generation of a utilitarian System 1 intuition in
classic moral dilemmas. If people do have such alleged utilitarian
intuitions, they could experience conflict between the competing moral
aspects of a dilemma without a need to engage in active
deliberation. The present paper tests this possibility and will
thereby present a critical test of the dual process model of moral
reasoning.

In our studies we adopted Białek and De Neys’ (2016) paradigm and
presented subjects with a set of classic moral conflict dilemmas
and no-conflict control versions to measure their conflict sensitivity.
Critically, while subjects were solving the problems their
cognitive resources were burdened with a demanding secondary task. The
basic rationale is simple. A key defining characteristic of System 2
thinking is that it draws on our limited executive working memory
resources. Imposing an additional load task that burdens these
resources will hamper or “knock-out” System 2. Hence, if subjects’
potential moral conflict sensitivity results from deliberate System 2
processing, it should become less likely under load. That is, under
load it should be less likely that subjects manage to consider the
alleged demanding utilitarian aspects of the dilemma and this should
decrease the likelihood that a conflict with the intuitive
deontological response will be experienced. Consequently, the previously
reported conflict detection effects such as an increased response doubt
for conflict vs no-conflict problems should no longer be observed under
load. Alternatively, intuitive System 1 processes are assumed to
operate effortless. Hence, if subjects’ conflict sensitivity
results from the competing output of two intuitive System 1 processes,
it should not be affected by load. 

We tested the predictions in Study 1 and assessed the robustness of the
findings in Study 2 and 3. Taken together, the studies will test
whether reasoners intuitively take the utilitarian aspects of a moral
dilemma into account. The answer will allow us to advance the specification
of the dual process model of moral cognition. 

\section{Study 1}

\subsection{Method}

\subsubsection{Subjects}

A total of 261 individuals (108 female, Mean age = 35.8, SD= 12.5, range
18--72) recruited on the Amazon Mechanical Turk platform participated in
the study. Only native English speakers from the USA or Canada were
allowed to participate. Subjects were paid a fee of \$0.75. 

\subsection{Material and procedure}

\begin{table*}[p]
\caption*{Table 1. Exact wording of the conflict and no-conflict versions
of the dilemmas that were used in Study 1. Dilemmas were presented in
two parts. The first part containing the background information is
shown in italics.} 

\paragraph{Trolley (Conflict)}
\textit{There is a runaway trolley barrelling down the railway tracks.
Ahead, on the tracks, there are five people tied up and unable to move.
The trolley is headed straight for them.}

You are standing some distance off in the train yard, next to a lever.
If you pull this lever, the trolley will switch to a different set of
tracks. Unfortunately, you notice that there is one person on the side
track. This person will die if you change the tracks, but the five
other will be saved. Would you pull the lever?

\paragraph{Plane (Conflict) }
\textit{You are a U.S. military base commander. A missile has just been
mistakenly fired from your base at a commercial airliner. If nothing is
done, fifty passengers of the airliner will die.}

You can alter the course of the commercial airliner. The airliner will
be safe, but the missile will destroy another commercial airliner (with
ten people onboard) flying right behind the first airliner. Would you
alter the course of the airliner?

\paragraph{Hospital (Conflict)}
\textit{You are the late-night watchman in a hospital. Due to an
accident in the building next door, there are deadly fumes rising up
through the hospital’s ventilation system. In a certain room of the
hospital are five patients. If you do nothing the fumes will rise up
into the room containing the five patients and cause their deaths.}

The only way to avoid the deaths of these patients is to hit a certain
switch, which will cause the fumes to bypass the room containing the
five patients. As a result of doing this the fumes will enter another
room containing a single patient, causing his death. Would you hit the
switch?

\paragraph{Cave (Conflict) }
\textit{A tour guide leading a group of five people out of a cave on a
coast is stuck in the mouth of that cave. In a short time high tide
will be upon them, and unless he is unstuck, they will all be drowned
except the tour guide, whose head is out of the cave.}

You have found the group and there seems no way to save the five others
and get the tour guide loose without using dynamite which will
inevitably kill the tour guide; but if you do not use it the five other
people will drown. Would you use the dynamite?

\paragraph{Trolley (No-conflict)}
\textit{There is a runaway trolley barrelling down the railway tracks.
Ahead, on the tracks, there is one man tied up and unable to move. The
trolley is headed straight for him.}

You are standing some distance off in the train yard, next to a lever.
If you pull this lever, the trolley will switch to a different set of
tracks. Unfortunately, you notice that there are five people on the
side track. These five people will die if you change the tracks, but
the one other will be saved.~Would you pull the lever?


\paragraph{Plane (No-conflict)}
{\itshape You are a U.S. military base commander. A missile has just
been mistakenly fired from your base at a commercial airliner. If
nothing is done, ten passengers of the airliner will die. }

You can alter the course of the commercial airliner. The airliner will
be safe, but the missile will destroy another commercial airliner (with
fifty people on board) flying right behind the first airliner. Would
you alter the course of the airliner?


\paragraph{Hospital (No-conflict)}
{\itshape You are the late-night watchman in a hospital. Due to an
accident in the building next door, there are deadly fumes rising up
through the hospital’s ventilation system. In a certain room of the
hospital is a patient. If you do nothing the fumes will rise up into
the room containing the patient and cause his death.}

The only way to avoid the death of this patient is to hit a certain
switch, which will cause the fumes to bypass the room containing the
patient. As a result of doing this the fumes will enter another room
containing five patients, causing their deaths. Would you hit the
switch?

\paragraph{Cave (No-conflict)}
{\itshape A tour guide leading a group of five people out of a cave on a
coast is stuck in the mouth of that cave. In a short time high tide
will be upon him, and unless he is unstuck, he will be drowned while
the rest of the group will survive inside the cave.}

You have found the group and there seems no way to get the tour guide
loose and save him without using dynamite which will inevitably kill
the rest of the group; but if you do not use it the tour guide will
drown. Would you use the dynamite?
\end{table*}

\begin{figure*}[t!]\centering
\renewcommand\arraystretch{1.35}
\begin{tabular}{l@{\hspace{1cm}}c@{\hspace{1cm}}c@{\hspace{1cm}}c@{\hspace{1cm}}c}
 & Target matrix & matrix 1 & matrix 2 & matrix 3\\
 Simple &
 \begin{tabular}{|c|c|c|c|}\hline
  \blob & \blob & \blob & \blob\\\hline
   &  &  & \\\hline
   &  &  & \\\hline
   &  &  & \\\hline
 \end{tabular} &
 \begin{tabular}{|c|c|c|c|}\hline
  \blob & &  & \\\hline
   & \blob &  & \\\hline
   &  & \blob & \\\hline
   &  &  &  \blob \\\hline
 \end{tabular} &
 \begin{tabular}{|c|c|c|c|}\hline
   &  &  &  \blob \\\hline
   &  & \blob & \\\hline
   & \blob &  & \\\hline
  \blob &  &  & \\\hline
 \end{tabular} &
 \begin{tabular}{|c|c|c|c|}\hline
  \phantom{\blob} & \phantom{\blob} & \phantom{\blob} & \blob \\\hline
   &  &  & \blob \\\hline
   &  &  & \blob \\\hline
   &  &  & \blob \\\hline
 \end{tabular}\\[7ex]
 & Target matrix & matrix 1 & matrix 2 & matrix 3\\
 Complex &
 \begin{tabular}{|c|c|c|c|}\hline
  \blob &  &  &  \\\hline
  \blob &  & \blob  &  \\\hline
   & \blob &  &  \\\hline
   &  &  & \blob \\\hline
 \end{tabular} &
 \begin{tabular}{|c|c|c|c|}\hline
 \blob  &  & \phantom{\blob} &  \\\hline
 \blob  &  &  &  \\\hline
   & \blob &  & \blob \\\hline
 \blob  &  &  &  \\\hline
 \end{tabular} &
 \begin{tabular}{|c|c|c|c|}\hline
   & \blob & \phantom{\blob} & \blob \\\hline
   &  &  &  \\\hline
  \blob &  &  &  \\\hline
   & \blob &  & \blob \\\hline
 \end{tabular} &
 \begin{tabular}{|c|c|c|c|}\hline
  \phantom{\blob} & \blob &  & \blob \\\hline
   &  &  &  \\\hline
   &  & \blob &  \\\hline
   &  & \blob & \blob \\\hline
 \end{tabular}\\
\end{tabular}
\caption*{Figure 1. Examples of the matrices and recall
options that were used in the low (Simple matrix) and high load
(Complex matrix) conditions.}
\end{figure*}

\paragraph{Moral reasoning task.} We used four classic moral dilemmas:
the trolley, plane, cave, and hospital problem. These were adopted
from the work of Royzman and Baron (2002), Foot (1978), and Cushman,
Young and Hauser (2006). All problems had the same core structure and
required subjects to decide whether or not to sacrifice the lives of
one of two groups of persons (all with a 1:5 ratio, see Table 1). Each
subject solved a total of four dilemmas. Two dilemmas were presented
in a conflict version and the other two in a no-conflict version. In
the conflict versions subjects were asked whether they were willing to
sacrifice a small number of persons in order to save several more. In
the no-conflict versions subjects were asked whether they were willing
to sacrifice more people to save less. For each subject it was
randomly determined which dilemmas were presented as conflict and
no-conflict problems. Presentation order of the four dilemmas was also
randomized for each subject. Each dilemma was presented in each
version an equal number of times.

The dilemmas were presented in two parts. First, the general background
information was presented (italicized text in Table 1) and subjects
clicked on a confirmation button when they finished reading it.
Subsequently, subjects were shown the second part of the problem
that contained the critical conflicting or non-conflicting dilemma
information and asked them about their personal willingness to act and
make the described sacrifice themselves (“Would you do X?”). Hence, on
the conflict version the utilitarian response is to answer “yes” and
the deontological response is to answer “no”. On the no-conflict
problems both utilitarian and deontological considerations cue a “no”
answer. Subjects entered their answer by clicking on a
corresponding bullet point (“Yes” or “No”). The first part of the
problem remained on the screen when the second part was presented. 

\paragraph{Confidence measure.} Immediately after subjects had entered
their dilemma response, a new screen with the confidence measure
popped-up. Subjects were asked to indicate their response confidence
(“How confident are you in your decision?”) on a 7-point rating scale
ranging from 1 (not confident at all) to 7 (extremely
confident).\footnote{Note that the interest is in the relative
  difference between confidence judgments on the no-conflict and
  conflict versions (Botvinick, 2007; Johnson, Tubau \& De Neys,
  2016). There are numerous reasons for individual variation in
  absolute ratings of confidence, and a variety of measurement biases
  may influence the particular value that subjects report (e.g. Berk
  \& Theall, 2006; Shynkaruk \& Thompson, 2006). Accordingly, absolute
  confidence levels must be interpreted with caution. At the same
  time, however, it can be assumed that any general bias in the
  response scale should affect confidence ratings in both conflict and
  no-conflict control versions.} Relatively lower confidence for the
conflict vs.\ no-conflict decision, in particular for those reasoners
who provide a deontological response (see further), can be taken as an
indicator that subjects considered both the utilitarian and
deontological aspects of the dilemma and were affected by the conflict
between them (Białek \& De Neys, 2016).

\paragraph{Dot memorization load task.} The secondary load task was
based on the work of Miyake, Friedman, Rettinger, Shah and Hegarty
(2001) and Trémolière et al.\ (2012). Subjects had to memorize a dot
pattern (like the one shown in Figure 1) during the moral reasoning
task. After subjects had read the first part of a dilemma, the dot
pattern was briefly presented. Next, subjects read the second part of
the dilemma, indicated their decision, and entered their response
confidence. After subjects had indicated their confidence they were
shown four matrices with different dot patterns and they had to select
the correct, to-be-memorized matrix (Figure 1). Finally, subjects were
given feedback as to whether they recalled the correct matrix and were
instructed to focus more closely on the memorization in case they
erred.

Half of the subjects were randomly allocated to the high load
condition, the other half were allocated to a low load control
condition. In the high load condition the matrix consisted of five
dots arranged in a complex interspersed pattern in a 4 x 4 grid, which
has been established to interfere specifically with effort-demanding
executive resources (Miyake et al., 2001). Previous studies
established that this demanding secondary task effectively burdens
System 2 during reasoning (De Neys, 2006; Johnson et al., 2016;
Trémolière et al., 2012). In the low load condition the matrix
consisted of a simple pattern of four aligned dots, which should place
only a minimal burden on executive resources (De Neys, 2006; De Neys
\& Verschueren, 2006).  Presentation time for the grid in the low load
condition was set to 1000 ms. To make sure that subjects could
perceive the extra complex pattern in the high load condition so that
storage would effectively burden executive resources, presentation
time was increased to 2000 ms in this condition (e.g., see Trémolière
et al., 2012, for a related approach).

As in Trémolière et al.\ (2012) we also used a multiple choice
recognition format for the dot memorization task. In the high load
condition all response options showed an interspersed pattern with 5
dots. There was always one incorrect matrix among the four options
that shared 3 out of the 5 dots with the correct matrix (e.g., see
Figure 1, matrix 1). The two other incorrect matrices shared one of
the dots with the correct matrix (e.g., see Figure 1, matrix 2 and
3). In the low load condition all response options showed four dots
aligned on a straight line.  Subjects were presented with two dot
memorization practice trials to familiarize them with the
procedure. In the first trial they only needed to memorize a (simple)
matrix. The second practice trial mimicked the full procedure, but
instead of a moral dilemma it used a simple arithmetic problem as
primary task.

The point at which the dot matrix was introduced in the experimental
trial sequence was specifically chosen to optimize the load procedure.
On one hand, one wants to minimize the amount of reading under load to
minimize the possibility that the load will interfere with basic
scenario reading and comprehension processes. This argues against
introduction of the load before the scenario is presented (i.e., if
subjects cannot read the scenario, responding will be random and
uninformative). On the other hand, if the load is introduced after the
full scenario has been presented, subjects can pre-empt and
sidestep the load by starting to reflect on their decision during the
scenario “reading” phase. Our two stage presentation minimizes these
problems. It allows reducing the amount of reading under load and
avoids the pre-empting confound since the critical alternative choice
and the resulting potential conflict between the utilitarian and
deontological considerations are introduced after the load has been
introduced.

To avoid any confusion it should be stressed that our load procedure
was not designed to interfere with subjects’ reading and comprehension
of the second part of the dilemma either. More generally, one should
keep in mind that all dual process models entail that System 1
processing can cue a response only after the problem material has been
properly encoded. Bluntly put, if you can’t read the different
alternative dilemma choices, there will not be any content that can
trigger an intuitive answer. Testing whether the load does indeed not
interfere with basic reading and comprehension is straightforward. If
it were, then people will not understand the problem, and they can
only guess when responding. Hence, we would get a similar rate of
random responding on conflict and no-conflict problems. If people
cannot encode the preambles, then by definition their cognitive
processing of both problem versions cannot differ. As we will show, in
all our studies the observed pattern of dilemma choices on the
conflict and no-conflict problems establishes that this is not the
case (i.e., “yes” responses are much rarer on the no-conflict problems
than on the conflict problems). Because the same task has been
extensively used in previous dual process work on
deductive/probabilistic reasoning (e.g., De Neys, 2006) and even moral
reasoning (Trémolière et al., 2012), we already knew that it was quite
unlikely that the task would interfere with basic comprehension
processes. At the same time, extensive prior evidence in the reasoning
field establishes that the task does disrupt System 2 deliberation
(e.g., De Neys, 2006, with syllogistic reasoning problems; Johnson et
al., 2016, with the bat-and-ball problem; De Neys \& Verschueren,
2006, with the Monty Hall Dilemma; Franssens \& De Neys, 2009, with
base-rate neglect problems; Trémolière et al., 2012, with moral
reasoning problems). In sum, there is good evidence for the soundness
of our load approach.

% need not be 50% - could be response bias

We recorded the time subjects needed to read the first part of the
dilemma (i.e., time between presentation of the first part of the
dilemma and subject’s confirmation) before the dot matrix was
presented. We refer to this measure as the initial dilemma reading
time. After the matrix was presented, we also measured the time that
elapsed between the presentation of the second part of the dilemma and
subjects’ answer selection. We refer to this measure as the dilemma
decision time, although, because of the two-stage dilemma
presentation, the decision time also includes some additional reading
time.\footnote{Previous studies that aimed at an accurate registration
  of decision time per se (e.g., Białek \& De Neys, 2016; Koop, 2013)
  have restricted it to the time needed after the full scenario had
  been read. We opted against this split up to optimize and not
  further complicate the load procedure. In addition, our use of a
  no-conflict control condition prevented most subjects from deciding on
  their response without reading the second part at all.}

\subsection{Results and discussion}

%\renewcommand{\baselinestretch}{1.03} \large\normalsize 

\subsubsection{Dot memorization load task}

Overall, subjects were able to select the correct matrix in more than
3 out of 4 cases. On average, accuracy reached 81\% (mean = 3.24, SD =
0.97) in the high load condition and 84 \% (mean = 3.36, SD = 0.88) in
the low load condition. This indicates that in general the load task
was performed properly, according to the instructions.  However,
although most subjects recalled the dot locations correctly, some
subjects made more recall errors. In cases where the dot matrix is not
recalled correctly, one might argue that we cannot be certain that the
load task was efficiently burdening executive resources (i.e., the
subject might be neglecting the load task, thereby minimizing the
experienced load). A possible lack of a load effect on conflict
detection could be then attributed to this possible confound. To
sidestep this potential problem we used a two-stage filtering
procedure. First, we discarded any subject who had made more than one
recall error (i.e., less than 75\% accuracy, n = 44; 16.9\% of the
sample). Next, from the remaining group we also removed subjects from
the high load condition who had selected an incorrect matrix that
shared only 1 dot with the correct pattern (n = 26; 9.96\% of the
sample). Hence, subjects who were included in the analyses had at
least 75\% accuracy and were able to recognize 3 out of 5 dots
correctly when they did err under high load. The final sample
consisted of 191 individuals (71 females, mean age = 35.9, SD = 12.3,
range 18--72). Resulting average memorization performance in the high
load condition was 94\% (mean = 3.75, SD =0.44) and 93 \% (mean = 3.73
SD = 0.45) in the low load condition.\footnote{Results with all
  subjects included are essentially the same and reported in the
  \href{http://journal.sjdm.org/17/17224/supplement.pdf}{supplement},
    Section C.}

\begin{figure}[t!]\centering
\includegraphics[width=2.75in]{fig2a.eps}\\[2em]
\includegraphics[width=2.75in]{fig2b.eps}\\[2em]
\includegraphics[width=2.75in]{fig2c.eps}\\
\caption*{Figure 2. Average willingness to make a sacrifice (\%
“yes” responses ) in Study 1 (top panel) and average moral
acceptability judgments (\% “yes” responses ) in Study 2 (middle panel)
and Study 3 (bottom panel) on conflict and no-conflict dilemmas as a
function of load. Error bars represent 95\% confidence intervals.}\vspace{1ex}
\end{figure}

\subsubsection{Dilemma decision choices}

Subjects were asked to decide whether they were willing to make a
sacrifice and perform the action that was described in each dilemma.
For each subject we calculated the average willingness to make a
sacrifice (i.e., percentage “yes” responses) in the conflict and
no-conflict dilemmas.\footnote{ Complementary item analyses can be
  found in the Supplementary Material. For completeness, the
  Supplementary Material also presents unfiltered subject-wise
  analyses in which all subjects – irrespective of their load recall
  accuracy – were included.} These averages were entered in a 2
(Conflict, within-subjects) x 2 (Load, between-subjects) mixed model
ANOVA. Recall that on the conflict versions the utilitarian response
is to answer “yes” and the deontological response is to answer
“no”. On the no-conflict problems both utilitarian and deontological
considerations lead to a “no” answer. Figure 2 (top panel) gives an
overview of the results. Not surprisingly there was a main effect of
the Conflict factor, F(1, 189) = 499.61, p {\textless} .001,
$\eta_p^2$ = .726. As Figure 2 shows, overall, subjects were willing
to make a sacrifice in 80\% of the cases on the conflict
versions. Hence, in line with previous studies (e.g., Lotto,
Manfrinati \& Sarlo, 2014; Gold, Colman \& Pulford, 2014; Royzman \&
Baron, 2002) subjects gave utilitarian responses to the conflict
dilemmas in the majority of cases. Obviously, the average willingness
to make a sacrifice was much lower (i.e., 11.6\%) on the conflict
problems. The main effect of load was not significant, F(1, 189) =
3.61, p = .059, but the two factors interacted, F(1, 189) = 4.74, p
{\textless} .035, $\eta_p^2$ = .024. Planned contrasts showed that
load had no impact on no-conflict decisions, F(1, 189) {\textless}
1. However, willingness to make a sacrifice decreased under load on
the conflict problems, F(1, 189) = 6.49, p {\textless} .015,
$\eta_p^2$ = .033. Hence, in line with previous observations, under
high load subjects were less likely to make utilitarian decisions on
conflict dilemmas (Conway \& Gawronski, 2013; Trémolière et al.,
2012).\footnote{Section A of the
  \href{http://journal.sjdm.org/17/17224/supplement.pdf}{supplement}
    shows the results for the four dilemmas. Only Plane and Cave
    showed this effect.}

\subsubsection{Decision confidence}

Obviously, our primary interest lies in subjects’ decision confidence
as this allows us to measure their moral conflict detection
sensitivity. The key contrast concerns the confidence ratings for
conflict vs.\ no-conflict problems. If subjects take utilitarian
considerations into account and detect that they conflict with the
cued deontological response, response confidence should be lower on
the conflict vs no-conflict problems. We first focus on the contrast
analyses for deontological (“no”) conflict responders. Next, we
present the analyses for utilitarian (“yes”) conflict
responders.\footnote{See the
  \href{http://journal.sjdm.org/17/17224/supplement.pdf}{supplement},
  Section B, for additional analyses for the subgroup of subjects who
  consistently gave deontological responses on both conflict problems
  that they solved.} Note that we use only those no-conflict responses
in which subjects refuse to make a sacrifice (i.e., “no”
responses). No-conflict decisions to sacrifice many to save few are
cued by neither deontological nor utilitarian considerations.  These
“other” responses were rare but were excluded from the contrast
analyses to give us the purest possible test of subjects’ conflict
sensitivity.

\paragraph{Deontological responders.} We entered subjects’ average
confidence ratings in a 2 (Conflict, within-subjects) x 2 (Load,
between-subjects) mixed model ANOVA. Results are illustrated in Figure
3 (top panel). There was a main effect of the conflict factor, F(1,
46) = 6.8, p {\textless} .015, $\eta_p^2$ = .129. Overall,
deontological responders’ confidence decreased with about 12\% (mean
decrease = 0.66 scale points) when solving conflict problems. In line
with previous findings this increased decision doubt indicates that
deontological responders take both utilitarian and deontological
considerations into account and are sensitive to conflict between
them.  However, the critical finding is that this sensitivity was not
affected by load. Neither the main effect of load, F(1, 46)
{\textless} 1, nor the interaction with the conflict factor reached
significance, F(1, 46) {\textless} 1 (see the results of Study 3 for
an overall Bayes factor analysis further supporting this conclusion).

\begin{figure}[t]\centering
\includegraphics[width=2.75in]{fig3a.eps}\\[2em]
\includegraphics[width=2.75in]{fig3b.eps}\\
\caption*{Figure 3. Average confidence ratings (7-point scale)
for utilitarian and deontological decisions on the conflict problems
and no-conflict control decisions (“no” responses) under high and low
cognitive load in Study 1 (top panel) and Study 2 (bottom panel). Error
bars represent 95\% confidence intervals.}
\end{figure}

\paragraph{Utilitarian responders.} Our main theoretical interest concerned
the conflict detection findings for deontological conflict responders.
For completeness, we also analysed the conflict contrast for
utilitarian conflict responders. It should be noted that these findings
face a potential fundamental methodological problem (e.g., Conway \&
Gawronski, 2013). Deontological considerations cue “no” responses on
the conflict and no-conflict problems. Utilitarian considerations cue a
“no” response on no-conflict problems, but a “yes” response (i.e.,
willingness to make a sacrifice) on conflict problems. Hence, in the
case of utilitarian responders, conflict and no-conflict responses not
only differ in the presence or absence of conflict but also in terms of
the decision made (i.e., willingness to take action or not).
Consequently, when contrasting the conflict and no-conflict detection
indexes, results might be confounded by the decision factor. Any
potential processing difference might be attributed to the differential
decision rather than to conflict sensitivity. Therefore, we present the
utilitarian conflict contrast for completeness. If one wants to
eliminate the potential decision factor confound completely, one can
focus exclusively on the analysis for deontological responders. 

%\pagebreak

%\renewcommand{\baselinestretch}{1.08} \large\normalsize 

We entered utilitarian responders average confidence ratings in a 2
(Conflict, within-subjects) x 2 (Load, between-subjects) mixed model
ANOVA. Results are also illustrated in Figure 3 (top panel, orange
bars). As the figure indicates, findings were similar to the trends we
observed for deontological responders. There was a main effect of the
conflict factor, F(1, 158) = 11.98, p {\textless} .005, $\eta_p^2$ =
.07. Overall, utilitarian responders’ confidence decreased with about
6.5\% (mean decrease = 0.33 scale points) when solving conflict
problems. The conflict effect was not affected by load. Neither the
main effect of load, F(1, 158) {\textless} 1, nor the interaction with
the conflict factor reached significance, F(1, 158 ) {\textless} 1.

\begin{table*}[t]\centering
\caption*{Table 2. Mean ratings, decision time, and reading time for conflict and no-conflict dilemmas as a function of the dilemma response decision in \textbf{Study 1}. Standard deviations are shown in parentheses.}
\begin{tabular}{ll*{4}{C{1in}}}\toprule
 & & \mc{2}{c}{Conflict} & \mc{2}{c}{No Conflict} \\\cmidrule(lr){3-4}\cmidrule(lr){5-6}
 & & \raisebox{-1ex}{Deontological} &\raisebox{-1ex}{Utilitarian} &Utilitarian/ Deontological& \raisebox{-1ex}{Other} \\\midrule
\textbf{Low load} &Sample size (n) &20 &101 &106 &20 \\
 Confidence &1--7 scale & {\ } 4.65 {\ } (1.68) & {\ } 4.92 {\ } (1.42) & {\ } 5.39 (1.29) & {\ } 4.60 (1.73) \\
 Reading time (s) &Raw latencies &13.73 {\ } (9.28) &13.90 {\ } (5.90) &16.04 (11.60) &13.12 {\ } (8.03) \\
  &Antilogged &10.81 {\ } (2.13) &12.70 {\ } (1.55) &13.43 {\ } (1.80) &11.41 {\ } (1.67) \\
 Decision time (s) &Raw latencies &20.51 (16.42) &17.55 {\ } (7.36) &18.61 {\ } (9.95) &16.30 (10.81) \\
  &Antilogged &14.56 {\ } (2.54) &16.21 {\ } (1.49) &16.63 {\ } (1.61) &13.42 {\ } (1.92) \\\midrule
\textbf{High load} &Sample size (n) &29 &67 &77 &16 \\
 Confidence &1--7 scale & {\ } 4.90 {\ } (1.66) & {\ } 5.07 {\ } (1.49) & {\ } 5.45 {\ } (1.50) & {\ } 4.69 {\ } (1.91) \\
 Reading time (s) &Raw latencies &17.20 (14.21) &15.78 {\ } (9.02) &15.44 {\ } (9.17) &17.21 (16.58) \\
  &Antilogged &13.33 {\ } (2.03) &13.66 {\ } (1.73) &13.17 {\ } (1.81) &13.17 {\ } (2.04) \\
 Decision time (s) &Raw latencies &18.27 (12.56) &16.91 {\ } (7.72) &18.19 (11.23) &10.01 {\ } (8.40) \\
  &Antilogged &14.93 {\ } (1.90) &15.54 {\ } (1.50) &16.12 {\ } (1.60) & {\ } 7.98 {\ } (1.89) \\\bottomrule
\end{tabular}
\end{table*}

\subsubsection{Reading and decision latencies}

We recorded subjects’ dilemma reading (i.e., time between
presentation of the first part of the dilemma and subject’s
confirmation) and decision times (i.e., time that elapsed between the
presentation of the second part of the dilemma and subjects’ answer
selection). Because of skewness all latencies were log transformed
prior to analysis. An overview can be found in Table 2. Average reading
times were entered in a 2 (Conflict, within-subjects) x 2 (Load,
between-subjects) mixed model ANOVA. Neither for deontological
responders [all F(1, 46) {\textless} 1, all p {\textgreater} .431], nor
utilitarian responders [all main effects F(1, 158) {\textless} 1, all p
{\textgreater} .337; interaction F(1, 158) = 1.07, p = .303] did any of the
factors reach significance. As one might expect this establishes that
subjects did not process the problems differently before the
introduction of load.

We also ran a similar 2 (Conflict, within-subjects) x 2 (Load,
between-subjects) ANOVA on the decision times. As with the reading
times, neither for deontological responders [all F(1, 46) {\textless}
1, p {\textgreater} . 419] nor utilitarian responders [conflict, F(1,
158) = 2.28, p = .133; all other F(1, 158) {\textless} 1, p
{\textgreater} .541] did any of the factors reach significance. The
absence of a load effect and load by conflict interaction suggests that
subjects in the high load condition did not try to compensate for
the load by taking more time to solve the (conflict) problems under
load. Note that we also did not observe a main effect of the conflict
factor. Białek and De Neys (2016) previously used decision time as a
conflict detection index an observed that the doubt associated with
conflict detection also resulted in longer conflict (vs no conflict)
decision times. However, unlike the present study this study measured
decision time after the full scenario had been read. It is possible
that the combination of reading and decision time in the present
two-stage presentation format obscured this effect. 

%\renewcommand{\baselinestretch}{1.00} \large\normalsize 

\section{Study 2}

Subjects’ decreased decision confidence when solving conflict dilemmas
indicates that they are taking utilitarian considerations into account
and are sensitive to conflict between the competing utilitarian and
deontological aspects of moral dilemmas. The fact that this conflict
sensitivity effect was not affected by load indicates that it operates
effortlessly and results from intuitive System 1 processing.  However,
Study 1 is but the first study to test this hypothesis. In Study 2 we
therefore tried to replicate the findings and test the robustness of
the effects. The study also allowed us to eliminate a potential
remaining confound. Study 1 asked subjects to indicate their personal
willingness to act (e.g., “would you pull the switch?”)  in the moral
dilemmas. Although this question format is not uncommon, most studies
in the moral reasoning field ask subjects to judge whether they find
the described action morally acceptable (e.g., “do you think it is
morally acceptable to pull the switch?”). Our choice reflected a
personal preference to question people about their actual behaviour
rather than about their moral beliefs. However, recent studies
indicate that this design choice might not be trivial (Francis et al.,
2016; Patil, Cogoni, Zangrando, Chittaro \& Silani, 2014; Tassy et
al., 2012; Tassy, Oullier, Mancini \& Wicker, 2013). When people are
tested with both questions there tends to be a discrepancy in their
answers. That is, people often indicate they believe they have to make
a sacrifice, although they still judge the action to be
unacceptable. Consequently, subjects tend to be slightly more
“utilitarian” when questioned about their personal willingness to act
(but see also Baron, 1992, for a small opposite effect).  What is
important in the present context is that the
personal-willingness-to-act question might elicit stronger conflict
than the acceptability question (possibly because people take a more
egocentric perspective and are more emotionally engaged in the task,
e.g., Patil et al., 2014, and Tassy et al., 2012, 2013). This points
to a potential confound. By asking subjects about their personal
willingness to act we might have made the utilitarian/deontological
conflict more salient than it is with the traditional moral
acceptability question. Hence, with the more traditional acceptability
format, conflict might be less clear, and deontological responders
might not manage to (effortlessly) detect conflict between the
utilitarian and deontological aspects. Therefore, in Study 2 we simply
changed our question format and tested whether there was still
evidence for deontological responders’ utilitarian sensitivity under
load.

\subsection{Method}

\subsubsection{Subjects}

A total of 189 individuals (94 female, Mean age = 40.2, SD= 12.7, range
19--75) recruited on the online Crowdflower platform participated in the
study. Only native English speakers from the USA or Canada were allowed
to participate. Subjects were paid a fee of \$.75. 

\subsubsection{Material and Procedure}

The exact same material and procedure as in Study 1 was adopted. The
only difference was the way that the dilemma decision question was
phrased (i.e., the last sentence of the dilemma). Whereas subjects
in Study 1 were asked to indicate their personal willingness to act
(“Would you do X”?) subjects in Study 2 were asked to judge whether
or not they found the action morally acceptable (“Do you think it is
morally acceptable to do X”). 

\subsection{Results and discussion}

\renewcommand{\baselinestretch}{1.03} \large\normalsize 

\subsubsection{Dot memorization load task}

Overall, subjects selected the correct matrix in more than 3 out of
4 cases. On average, accuracy reached 88\% (mean = 3.52, SD = 0.63) in
the high load condition and 82\% (mean = 3.28, SD = 0.84) in the low
load condition. We used the same two-stage filtering procedure as in
Study 1 to screen for individuals who might have neglected the load
task. First, all subjects who had made more than one error were
discarded (i.e., less than 75\% accuracy, n = 24; 12.7\% of the
sample). Next, subjects in the high load condition who selected an
incorrect matrix that shared only one dot with the correct matrix were
also discarded (n = 24, 12.7\% of the initial sample). The final sample
consisted of 141 individuals (64 females, mean age = 40.3, SD = 13.1,
range 19--75). The resulting average memorization performance in the
high load condition was 95\% (mean = 3.81, SD = 0.40) and 92\% (mean =
3.68, SD = 0.47) in the low load condition.

\subsubsection{Dilemma acceptability judgments}

Subjects were asked to judge whether it was morally acceptable to make
the sacrifice that was described in each dilemma. For each subject we
calculated the average acceptability (i.e., percentage “yes”
responses) in the conflict and no-conflict dilemmas. For clarity, note
that, just as in Study 1, on the conflict versions the utilitarian
response is to answer “yes” and the deontological response is to
answer “no”. On the no-conflict problems both utilitarian and
deontological considerations lead to a “no” answer. The average
acceptability judgments were entered in a 2 (Conflict,
within-subjects) x 2 (Load, between-subjects) mixed model
ANOVA. Figure 2 (middle panel) shows the results. Not surprisingly,
there was again a main effect of the conflict factor, F(1, 139) =
195.23, p {\textless} .001, $\eta_p^2$ = .57. Subjects found it far
more acceptable to make a sacrifice on the conflict problems (i.e.,
66.3\%) than on the no-conflict problems (i.e., 12.6\%). The main
effect of load was not significant, F(1, 139) {\textless} 1, but the
two factors interacted, F(1, 139) = 4.91, p {\textless} .035,
$\eta_p^2$ = .034. As Figure 2 shows, there seemed to be a trend
towards more frequent utilitarian “yes” judgments under load,
especially on the conflict problems. Follow-up test showed that the
load impact on the conflict problems (just as on no-conflict problems,
F(1, 139) = 1.37, p = .24, $\eta_p^2$ = .01) did not reach
significance, F(1, 139) = 2.58, p = .11, $\eta_p^2$ = .018. However,
the interesting point here is that there is clearly no evidence for
the decreased utilitarian responding under load for conflict problems
that was observed in Study 1. Hence, this suggests that giving a
utilitarian acceptability judgment (in contrast to indicating that one
is personally willing to act) does not necessarily require demanding
System 2 computations.\footnote{Although speculative this also
  suggests that the impact of load on utilitarian responding per se
  might be fairly subtle and depend (among other things) on the
  precise framing of the dilemma question (Körner \& Volk, 2014) or
  as well as the dilemma (Baron, 2017; Gürçay \& Baron, 2017).}

Finally, note that we also contrasted the rate of utilitarian
responses on the conflict dilemmas in Study 2 and Study 1. Average
rate of utilitarian responses was 66\% in Study 2 whereas it reached
80\% in Study 1, univariate ANOVA, F(1, 329) = 18.61, p {\textless}
.001, $\eta_p^2$ = .05. Hence, in line with previous studies we also
observed that utilitarian responding is less likely when people are
asked about the moral acceptability of an action than when they are
asked about their personal willingness to do the action (e.g., Tassy
et al., 2012).

\subsubsection{Acceptability decision confidence}

Our primary interest again lies in subjects’ decision confidence as
this allows us to measure their moral conflict detection
sensitivity. As in Study 1, we ran separate analyses for deontological
(“no”) and utilitarian (“yes”) conflict responders and only used
no-conflict responses in which subjects indicate that they find it
unacceptable to make a sacrifice (i.e., “no” responses).

\paragraph{Deontological responders.} We entered subjects’ average
confidence ratings in a 2 (Conflict, within-subjects) x 2 (Load,
between-subjects) mixed model ANOVA. Results are illustrated in Figure
3. There was a main effect of the conflict factor, F(1, 62) = 18.72, p
{\textless} .001, $\eta_p^2$ = .232. Overall, deontological
responders’ confidence decreased with 12\% (mean decrease = 0.64 scale
points) when solving conflict problems. The critical finding is that,
in line with Study 1, this sensitivity was not affected by
load. Neither the main effect of load, F(1, 62) {\textless} 1, nor the
interaction with the conflict factor reached significance, F(1, 62)
{\textless} 1. Hence, results replicate the key finding of Study 1:
Cognitive load does not hamper deontological responders’ detection of
conflict between utilitarian and deontological considerations in
classic moral dilemmas.

\paragraph{Utilitarian responders.} We entered subjects’ average
confidence ratings in a 2 (Conflict, within-subjects) x 2 (Load,
between-subjects) mixed model ANOVA. Results are also illustrated in
Figure 3. There was a main effect of the conflict factor, F(1, 97) =
22.08, p {\textless} .001, $\eta_p^2$ = .185. Utilitarian responders’
confidence decreased with 11\% (mean decrease = 0.60 scale points)
when solving conflict problems. Neither the main effect of load, F(1,
97) {\textless} 1, nor the interaction with the conflict factor
reached significance, F(1, 97) {\textless} 1. These findings are also
consistent with the Study 1 results.

\begin{table*}[t]
\caption*{Table 3. Mean ratings, decision time, and reading time for conflict and no-conflict dilemmas as a function of the dilemma response decision in \textbf{Study 2}. Standard deviations are shown in parentheses.}
\begin{tabular}{ll*{4}{C{1in}}}\toprule
 & & \mc{2}{c}{Conflict} & \mc{2}{c}{No Conflict} \\\cmidrule(lr){3-4}\cmidrule(lr){5-6}
 & & \raisebox{-1ex}{Deontological} &\raisebox{-1ex}{Utilitarian} &Utilitarian/ Deontological& \raisebox{-1ex}{Other} \\\midrule
\textbf{Low load} &Sample size (n) &44 &62 &77 &19 \\
 Confidence &1--7 scale & {\ } 4.57 {\ } (1.63) & {\ } 4.80 {\ } (1.63) & {\ } 5.31 {\ } (1.39) & {\ } 4.26 {\ } (1.80) \\
 Reading time (s) &Raw latencies &16.32 (11.14) &16.25 {\ } (9.34) &16.14 (10.67) &17.13 (12.23) \\
  &Antilogged &13.15 {\ } (1.86) &14.07 {\ } (1.94) &13.47 {\ } (1.79) &12.88 {\ } (4.97) \\
 Decision time (s) &Raw latencies &18.51 (11.98) &18.38 (10.41) &21.42 (13.37) &24.09 (30.13) \\
  &Antilogged &15.70 {\ } (1.78) &15.91 {\ } (1.73) &18.48 {\ } (1.72) &14.53 {\ } (1.00) \\\midrule
\textbf{High load} &Sample size (n) &22 &47 &54 &8 \\
 Confidence &1--7 scale & {\ } 4.64 {\ } (1.91) & {\ } 4.63 {\ } (1.33) & {\ } 5.31 {\ } (1.31) & {\ } 4.5 {\ } (0.93) \\
 Reading time (s) &Raw latencies &14.29 {\ } (9.92) &13.91 {\ } (5.58) &15.13 {\ } (8.20) &11.89 {\ } (5.60) \\
  &Antilogged &11.22 {\ } (1.71) &12.47 {\ } (1.91) &12.71 {\ } (1.75) & {\ } 9.55 {\ } (2.07) \\
 Decision time (s) &Raw latencies &23.95 (21.89) &18.45 {\ } (7.46) &20.42 (18.65) &18.48 (16.66) \\
  &Antilogged &17.57 {\ } (2.21) &16.83 {\ } (1.59) &16.42 {\ } (1.85) &13.33 {\ } (2.37) \\\bottomrule
\end{tabular}
\end{table*}

\renewcommand{\baselinestretch}{1.0} \large\normalsize 

\subsubsection{Reading and decision latencies}

We also ran analyses on subjects’ dilemma reading and decision times
(log transformed, as in Study 1). Table 3 presents an
overview. Average reading times were entered in a 2 (Conflict,
within-subjects) x 2 (Load, between-subjects) mixed model
ANOVA. Neither for deontological responders [main effects all F(1, 62)
{\textless} 1; interaction, F(1, 62) = 1.12, p = .294] nor utilitarian
responders [all F(1, 97) {\textless} 1] any of the factors reached
significance. As in Study 1, this establishes that subjects did not
process the problems differently before the introduction of load.

Next, we ran a 2 (Conflict, within-subjects) x 2 (Load,
between-subjects) mixed model ANOVA on the decision times. In line
with the Study 1 findings, for deontological responders none of the
factors reached significance [conflict, F(1, 62) = 2.36, p = .129;
load, F(1, 62) {\textless} 1; interaction, F(1, 62) = 1.81, p =
.18]. For utilitarian responders, we found a significant interaction
between conflict and load, F(1, 97) = 10.06, p {\textless} .005,
$\eta_p^2$ = .094, whereas the main effects of load, F(1, 97)
{\textless} 1, and conflict, F(1, 97) = 3.83, p = .053, did not reach
significance. Follow-up test showed that utilitarian responders showed
increased conflict decision latencies (20.82 s vs 17.09 s in antilogged
units) in the low load condition, F(1, 54) = 218.73, p {\textless}
.001, $\eta_p^2$ = .258, but not in the high load condition, F(1, 43)
{\textless}1.

\section{Study 3}

%\renewcommand{\baselinestretch}{1.04} \large\normalsize 

The critical confidence findings in Study 2 are consistent with the
Study 1 results. This supports the robustness of our findings.
Nevertheless, a critic might object to the use of a confidence rating
to measure conflict detection during moral reasoning per se. That is,
although the confidence measure has been frequently used to assess
conflict detection in the cognitive control, memory, and reasoning
field (e.g., Botvinick, 2007; De Neys, 2012; Thompson \& Johnson,
2014), paradigms in these fields typically concern cases in which a
response can be understood by everyone as normatively right or
wrong. In the moral cognition case, people are asked a question about
what they may see as a matter of personal conviction. Indeed, subjects
in moral reasoning studies are typically explicitly informed that
there are no “wrong” or “right” answers. In and by itself, this
ambiguity might bias the confidence measure.\footnote{We are indebted
  to Greg Murphy and Gord Pennycook for pointing out this issue.} In
Study 3 we address this issue. Note that one assumption underlying the
use of a confidence rating as a conflict detection index is that the
measure allows us to track the experienced processing difficulty
associated with the conflict. It is this processing difficultly that
is believed to lead to a lowered decision confidence. Hence, instead
of measuring subjects’ confidence one might try to question them more
directly about the experienced difficulty and/or conflict. For
example, studies on conflict detection in economic cooperation games
have started to simply ask people to rate their feeling of conflict
(“How conflicted do you feel about your decision?”, e.g., Evans,
Dillon \& Rand, 2015; Nishi, Christakis, Evans, O’Malley \& Rand,
2016). In Study 3 we adopted a similar approach and asked subjects to
indicate how difficult they found the problem and how conflicted they
felt while making their judgment.  Thereby, Study 3 will allow us to
further validate the findings.

\subsection{Method}

\subsubsection{Subjects}

We recruited 200 individuals (110 female, mean age = 36.9, SD = 11.7,
range 19--67) on the Crowdflower platform. Only native English speakers
from the USA or Canada were allowed to participate. Subjects were
paid a fee of \$.75.

\subsubsection{Material and procedure}

The same material and procedure as in Study 2 was adopted (i.e.,
subjects were asked to judge the moral acceptability of the
action). The only difference was that subjects were not asked for a
confidence rating but were instead presented with two questions that
were aimed to more specifically track any experienced conflict related
processing difficulty. The \textit{difficulty} rating question stated
“\textit{How hard did you find it to make a decision?} (1-Very easy
$\rightarrow$ 7-Very hard)”. The \textit{conflictedness} rating
question stated “\textit{Did you feel conflicted when making your
decision (e.g., did you consider to make a different decision)?} (1-Not
at all $\rightarrow$ 7-Very much so)”. The difficulty and
conflictedness rating questions were presented below each other. For
both questions subjects selected a rating on a 7-point scale. 

As can be expected, results showed that ratings on both questions were
highly correlated, r = .83, p {\textless} .001. We calculated a
conflict composite by averaging subject’s ratings on both
questions. For completeness, we will also report the analyses for each
individual question separately. 

\subsection{Results and discussion}

\subsubsection{Dot memorization load task}

Average accuracy reached 83\% (mean = 3.33, SD = 0.81) in the high load
condition and 86\% (mean = 3.44, SD = 0.77) in the low load condition.
We used the same two-stage filtering procedure as in Study 1 and 2 to
screen for individuals who might have neglected the load task. First,
all subjects who had made more than one error were discarded (i.e.,
less than 75\% accuracy, n = 28; 14\% of the sample). Next,
subjects in the high load condition who selected an incorrect
matrix that shared only one dot with the correct matrix were also
discarded (n = 21, 10.5\% of the sample). The final sample consisted of
151 individuals (82 females, mean age = 36.3, SD = 11.3, range 19--67).
The resulting average memorization performance in the high load
condition was 94\% (mean = 3.75, SD = 0.44) and 93\% (mean = 3.71, SD =
0.46) in the low load condition.

%\renewcommand{\baselinestretch}{1.00} \large\normalsize

\subsubsection{Dilemma acceptability judgments}

As in Study 2, subjects were asked to judge whether it was morally
acceptable to make the sacrifice that was described in each dilemma.
For each subject we calculated the average acceptability (i.e.,
percentage “yes” responses) and entered these in a 2 (Conflict,
within-subjects) x 2 (Load, between-subjects) mixed model
ANOVA. Figure 2 (bottom panel) shows the results. As in the first two
studies, there was again a main effect of the conflict factor, F(1,
149) = 231.76, p {\textless} .001, $\eta_p^2$ = .61. Subjects found it
far more acceptable to make a sacrifice on the conflict problems
(i.e., 70.9\%) than on the no-conflict problems (i.e., 15.3\%). The
main effect of load, F(1, 149) {\textless} 1, and the interaction,
F(1, 149) {\textless} 1, were not significant. Hence, as in Study 2
there was no evidence for the decreased utilitarian responding under
load that was observed in Study 1 when subjects were asked about their
willingness to act. As in Study 2, we also observed that the overall
rate of utilitarian responses on the conflict dilemmas in Study 3
(71\%) was lower than in Study 1 (80\%), univariate ANOVA, F(1, 340) =
6.92, p = .009, $\eta_p^2$ = .02. In sum, the pattern of acceptability
judgments is consistent with Study 2 and differs from the pattern
observed in Study 1 where subjects were questioned about their
willingness to act rather than the action’s moral acceptability. As we
noted in Study 2, this result is consistent with recent claims that
have pointed to the impact of the framing of the dilemma question in
moral reasoning studies (e.g., Francis et al., 2016; Körner \& Volk,
2014).

\subsubsection{Moral conflict detection indexes}

\begin{figure}[t]\centering
\includegraphics[width=2.75in]{fig4a.eps}\\[2em]
\includegraphics[width=2.75in]{fig4b.eps}\\
\caption*{Figure 4. Average difficulty rating (top panel) and
conflictedness rating (bottom panel) for utilitarian and deontological
decisions on the conflict problems and no-conflict control decisions
(“no” responses) under high and low cognitive load in Study 3. All
ratings were made on a 7-point scale. Error bars represent 95\%
confidence intervals.}
\end{figure}

Our primary interest in Study 3 concerns the alternative conflict
detection indexes. Each subject was asked to rate the experienced
problem difficulty and conflict. Both measures were combined into a
conflict composite. For completeness, we analysed both the results on
the individual scales and the composite measure. Note that as with the
confidence analyses in Study 1 and 2, we ran separate analyses for
deontological (“no”) and utilitarian (“yes”) conflict responders and
only used no-conflict responses in which subjects indicate that
they find it unacceptable to make a sacrifice (i.e., “no” responses). 

\paragraph{Deontological responders.} We entered subjects’ average
ratings on the difficulty, conflictedness, and composite scales
separately in a 2 (Conflict, within-subjects) x 2 (Load,
between-subjects) mixed model ANOVA. Results are illustrated in Figure
4. As Figure 4 suggests, results for the difficulty and conflictedness
scales were very coherent and fully in line with the confidence
findings in Study 1 and 2. For the difficulty analysis we found a main
effect of the conflict factor, F(1, 61) = 7.66, p = .007, $\eta_p^2$ =
.112. Overall, deontological responders judged conflict problems as
about 10\% harder (mean increase = 0.57 scale points) than no-conflict
problems. But neither the main effect of load, F(1, 61) {\textless} 1,
nor the interaction with the conflict factor reached significance,
F(1, 61) {\textless} 1. For conflictedness, there was also a main
effect of the conflict factor, F(1, 61) = 8.33, p = .005, $\eta_p^2$ =
.120. Overall, deontological responders’ felt about 10\% more
conflicted (mean increase = 0.62 scale points) when solving conflict
problems. Again, neither the main effect of load, F(1, 61) {\textless}
1, nor the interaction with the conflict factor reached significance,
F(1, 61) {\textless} 1. Finally, when both scales were combined, the
composite analysis also pointed to a main effect of the conflict
factor, F(1, 61) = 8.96, p = .004, $\eta_p^2$ = .128. Overall,
deontological responders’ composite conflict rating increased with
10\% (mean increase = 0.60 scale points) when solving conflict
problems. Neither the main effect of load, F(1, 61) {\textless} 1, nor
the interaction with the conflict factor reached significance, F(1,
61) {\textless} 1.

\begin{table*}[t]
\caption*{Table 4. Mean ratings, decision time, and reading time for conflict and no-conflict dilemmas as a function of the dilemma response decision in \textbf{Study 3}. Standard deviations are shown in parentheses.}
\begin{tabular}{ll*{4}{C{1in}}}\toprule
 & & \mc{2}{c}{Conflict} & \mc{2}{c}{No Conflict} \\\cmidrule(lr){3-4}\cmidrule(lr){5-6}
 & & \raisebox{-1ex}{Deontological} &\raisebox{-1ex}{Utilitarian} &Utilitarian/ Deontological& \raisebox{-1ex}{Other} \\\midrule
\textbf{Low load} &Sample size (n) &36 &70 &79 &21 \\
 Difficulty &1--7 scale & {\ } 4.71 {\ } (1.92) & {\ } 4.29 {\ } (1.93) & {\ } 3.73 {\ } (1.72) & {\ } 4.02 {\ } (1.87) \\
 Conflicted &1--7 scale & {\ } 4.97 {\ } (1.76) & {\ } 4.71 {\ } (1.82) & {\ } 4.09 {\ } (1.71) & {\ } 4.24 {\ } (1.81) \\
 Reading time (s) &Raw latencies &19.74 (15.83) &17.61 (12.47) &16.63 {\ } (8.08) &20.95 (28.14) \\
  &Antilogged &14.69 {\ } (2.00) &14.31 {\ } (1.85) &14.03 {\ } (1.71) &12.8 {\ } (2.68) \\
 Decision time (s) (s)&Raw latencies &22.76 (12.18) &21.19 (10.98) &20.87 (10.71) &18.88 (15.88) \\
  &Antilogged &19.09 {\ } (1.86) &18.09 {\ } (1.77) &18.14 {\ } (1.66) &13.62 {\ } (2.24) \\\midrule
\textbf{High load} &Sample size (n) &28 &57 &65 &18 \\
 Difficulty &1--7 scale & {\ } 4.46 {\ } (1.84) & {\ } 4.11 {\ } (2.02) & {\ } 3.50 {\ } (1.78) & {\ } 3.06 {\ } (1.66) \\
 Conflicted &1--7 scale & {\ } 4.59 {\ } (1.87) & {\ } 4.25 {\ } (1.98) & {\ } 3.70 {\ } (1.79) & {\ } 3.58 {\ } (1.96) \\
 Reading time (s) &Raw latencies &17.45 (15.30) &17.91 (12.91) &17.03 (12.03) &10.75 {\ } (5.32) \\
  &Antilogged &12.98 {\ } (2.12) &13.90 {\ } (1.70) &13.34 {\ } (1.79) & {\ } 9.39 {\ } (1.67) \\
 Decision time (s)&Raw latencies &14.74 {\ } (5.69) &17.89 (11.81) &17.40 {\ } (8.34) &12.70 {\ } (5.29) \\
  &Antilogged &13.60 {\ } (1.51) &15.16 {\ } (1.66) &15.44 {\ } (1.58) &11.27 {\ } (1.56) \\\bottomrule
\end{tabular}
\end{table*}

In sum, for all scales there is a clear effect of the conflict factor
but this effect is not affected by cognitive load. This pattern
replicates the confidence measure findings in Study 1 and 2.
Interestingly, the size of the observed conflict effect is also quite
consistent across measures and studies (i.e., it typically hovers at
around 10\%-12\%). Taken together these findings validate the moral
conflict sensitivity findings we observed in Study 1 and 2. 

\paragraph{Utilitarian responders.} We entered subjects’ average
rating on each of the measures in a 2 (Conflict, within-subjects) x 2
(Load, between-subjects) mixed model ANOVA. Results are also
illustrated in Figure 4. As in Study 1 and 2, results were in line
with the pattern we observed for deontological responders. In the
analysis on difficulty ratings, there was a main effect of the
conflict factor, F(1, 118) = 23.86, p {\textless} .001, $\eta_p^2$ =
.168. Utilitarian responders’ difficulty rating increased with 11\%
(mean increase = 0.67 scale points) when solving conflict
problems. But neither the main effect of load, F(1, 118) {\textless}
1, nor the interaction with the conflict factor reached significance,
F(1, 118) {\textless} 1. For conflictedness, there was again a main
effect of the conflict factor, F(1, 118) = 14.72, p {\textless} .001,
$\eta_p^2$ = .111. Utilitarian responders’ felt about 10\% more
conflicted (mean increase = 0.59 scale points) when solving conflict
problems. The effect of load, F(1, 118) = 3.11, p = .08, $\eta_p^2$ =
.026 , and the interaction with the conflict factor, F(1, 118)
{\textless} 1, did not reach significance. Finally, in the composite
analysis --- in which both scales were combined – there was also a
main effect of the conflict factor, F(1, 118) = 20.60, p {\textless}
.001, $\eta_p^2$ = .149. Utilitarian responders’ composite conflict
ratings increased with 11\% (mean increase = 0.64 points) when solving
conflict problems. Neither the main effect of load, F(1, 118)
{\textless} 1, nor the interaction with the conflict factor reached
significance, F(1, 118) {\textless} 1.

\subsubsection{Reading and decision latencies}

We also analyzed dilemma reading and (log transformed) decision
times. Table 4 presents an overview. Average reading times were
entered in a 2 (Conflict, within-subjects) x 2 (Load,
between-subjects) mixed model ANOVA. Neither for deontological
responders [all main effects and interaction, F(1, 61) {\textless} 1],
nor utilitarian responders [main load, F(1, 118) = 1.14, p = .288;
main conflict and interaction, F(1, 118) {\textless} 1] any of the
factors reached significance. As in Study 1 and 2, this suggests that
subjects did not process the problems differently before the
introduction of load.

We also ran a 2 (Conflict, within-subjects) x 2 (Load,
between-subjects) mixed model ANOVA on the decision
times. Deontological responders answered faster under higher load
(18.48 vs 14.10 sec in antilogged units respectively), F(1, 61) =
4.48, p = .038, $\eta_p^2$ = .068, but were equally fast for conflict
and no-conflict problems, F(1, 61) {\textless} 1 (interaction, F(1,
61) = 3.04, p = .086, $\eta_p^2$ = .047). A similar pattern of results
was found in utilitarian responders, where load significantly reduced
decision times, (19.03 vs 15.74 s in antilogged units,
respectively), F(1, 118) = 5.65, p = .019, $\eta_p^2$ = .046, but all
others effects were nonsignificant (all F(1, 118) {\textless} 1)

\subsubsection{Pooled conflict sensitivity and Bayes factor analysis}

The critical conflict sensitivity findings with our alternative
difficulty and conflictedness ratings in Study 3 are consistent with
the Study 1 and 2 results we obtained with confidence ratings.
Subjects show sensitivity to moral conflict and this effect is not
affected by cognitive load. To obtain an even more powerful test of the
hypothesis we also pooled the individual rating data from the three
studies in a final set of analyses and again tested whether there was
evidence for an impact of load on the conflict sensitivity findings.
These pooled analyses used the reversed composite conflict score (i.e.,
the average of the difficulty and conflictedness ratings) from Study 3
as confidence proxy (i.e., the higher the experienced processing
difficulty, the lower the score, as with confidence ratings). 

Results of the pooled analysis were consistent with the individual
studies. Deontological responders showed a main effect of conflict,
F(1, 173) = 32.622, p {\textless} .001, $\eta_p^2$ = .159. Overall,
the index decreased with 12\% (mean decrease = 0.63 scale points) when
solving conflict dilemmas in the pooled test. However, the effect of
load, F(1, 173) {\textless} 1, and the interaction, F(1, 173)
{\textless} 1, were still not significant.

For completeness we also ran a pooled analysis for utilitarian
responders. Here too results were consistent with the individual
studies. There was a main effect of conflict (mean 9\% decrease = 0.51
scale points), F(1,377) = 53.16, p {\textless} .001, $\eta_p^2$ =
.124, but no significant effect of load, F(1,377) {\textless} 1, or
interaction effect, F(1,377) {\textless} 1.

As we clarified, we mainly focused on deontological responders’
conflict sensitivity to obtain the purest possible test of our
hypothesis.  However, in all our Study 1, Study 2, and Study 3 tests,
the conflict sensitivity rating findings were similar for
deontological and utilitarian responders. Therefore, in a final
analysis we also pooled the utilitarian and deontological responders
in the three studies to get the strongest possible test of the load
hypothesis. In this final analysis we obtain a sample size of n =
458. Results were still consistent with the previous analysis. There
was a main effect of conflict (mean 7\% decrease = 0.40 scale points),
F(1, 456) = 70.47, p {\textless} .001, $\eta_p^2$ = .134, but no load
effect, F(1,456) {\textless} 1, or interaction, (1,456) {\textless} 1.

Finally, although our conflict sensitivity findings seem to be robust,
our key conclusion always relies on acceptance of the null hypothesis
(i.e., the absence of a conflict x load interaction).  The
null-hypothesis significance testing approach that we followed so far
does not make it possible to quantify the degree of support for the
null hypothesis. An alternative in this case is Bayesian hypothesis
testing using Bayes factors (e.g., Masson, 2011; Morey, Rouder,
Verhagen \& Wagenmakers, 2014; Wagenmakers, 2007). We used the JASP
package (JASP Team, 2016) to run 2 (Conflict, within-subjects) x 2
(Load, between-subjects) Bayesian ANOVAs with default priors on our
pooled data. Analyses were run for deontological responders,
utilitarian responders, and deontological and utilitarian responders
combined. The full JASP output tables are presented in the
Supplementary Material. In all cases the model that received the most
support against the null model was the one with a main effect of
conflict only (deontological responders BF10 = 1.60e+65; utilitarian
responders BF10 = 3457.41; combined BF10 = 2031.95). In all cases
adding the interaction to the model decreased the degree of support
against the null model (deontological responders BF10 = 3.74e+63;
utilitarian responders BF10 = 33.48; combined BF10 = 61.8).  Hence,
the model with a main effect of Conflict only was preferred to the
interaction model by a Bayes factor of at least 32 (deontological
responders BF10 = 42.81; utilitarian responders BF10 = 103.26;
combined BF10 = 32.88). Following the classification of Wetzels et
al.\ (2011) these data provide strong evidence against the hypothesis
that cognitive load is affecting deontological responders’ utilitarian
sensitivity.

\section{General discussion}

The present studies established that moral reasoners show an intuitive
sensitivity to conflict between deontological and utilitarian aspects
of classic moral dilemmas. In line with previous findings subjects
showed increased doubt (or experienced processing difficulty) about
their decisions when solving dilemmas in which utilitarian and
deontological considerations cued conflicting responses. Critically,
this crucial moral conflict sensitivity was observed irrespective of
the amount of cognitive load that burdened reasoners’ cognitive
resources. This implies that reasoners are considering the utilitarian
aspects of the dilemma intuitively without engaging in demanding
deliberation. 

In terms of the dual process model of moral cognition the findings
support a hybrid model in which System 1 is simultaneously generating a
deontological and utilitarian intuition when faced with a classic moral
scenario. For the serial model it is hard to explain that deontological
reasoners show utilitarian sensitivity. For the parallel model it is
hard to explain that this sensitivity (both for utilitarian and
deontological responders) is observed without deliberate, System 2
thinking. The present data imply that the operation of considering the
utilitarian aspects of one’s moral decision and detecting the conflict
with deontological considerations is effortless and happens
intuitively. This supports the hypothesis that the process is achieved
by System 1.

Our load conflict findings lend credence to the concept of an intuitive
utilitarianism. As we noted, in and by itself the idea that utilitarian
reasoning \textit{can} be intuitive is not new. For example, at least
since J. S. Mill various philosophers have portrayed utilitarianism as
a heuristic intuition or rule of thumb (Sunstein, 2004). At the
empirical level, Kahane (2012, 2015; Kahane, Wiech, Shackel, Farias,
Savulescu \& Tracey, 2012) demonstrated this by simply changing the
severity of the deontological transgression. He showed that in cases
where the deontological duty is trivial and the consequence is large
(e.g., when one needs to decide whether it is acceptable to tell a lie
in order to save someone’s life) the utilitarian response is made
intuitively. Likewise, Trémolière and Bonnefon (2014) showed that when
the kill-save ratios (e.g., kill 1 to save 5 vs kill 1 to save 5000)
were made extreme, people also effortlessly made the utilitarian
decision. Hence, one could argue that these earlier empirical studies
established that at least in some exceptional or extreme scenarios
utilitarian responding can be intuitive. What the present findings
indicate is that there is really nothing exceptional about intuitive
utilitarianism. People’s sensitivity to utilitarian-deontological
conflict in the present studies indicates that intuitive utilitarian
processing occurs in the standard dilemmas with conventional kill-save
ratios (e.g., 1 to 5) and severe deontological transgressions (e.g.,
killing) that were used to validate the standard dual process model of
moral cognition. This implies that utilitarian intuitions are not a
curiosity that result from extreme or trivial scenario content but lie
at the very core of the moral reasoning process. In this sense, one
might want to argue that our observations fit with earlier theoretical
suggestions that stress the primacy of intuitive processes in moral
judgments (e.g., Białek \& Terbeck, 2016; Dubljević \& Racine, 2014;
Greene \& Haidt, 2002; Haidt, 2001).

To avoid confusion it is important to underline that our hybrid dual
process model proposal does not argue against the idea that there also
exists a type of demanding, deliberate utilitarian System 2 thinking
as suggested by the traditional dual process model of moral cognition.
Note that at least in Study 1 we observed – in line with the load
studies of Conway and Gawronski (2013) and Trémolière et al.\ (2012)
--- that people gave fewer utilitarian responses under load. This
implies that although people might be intuitively detecting conflict
between utilitarian and deontological dimensions of a moral dilemma,
resolving the conflict in favour of a utilitarian decision can require
executive resources. Hence, we do not contest that there might be a
type of utilitarian thinking that is driven by System 2.\footnote{The
  failure to observe this effect in Study 2 and 3 also indicates that
  the load effects on moral decisions might be more subtle than the
  Conway and Gawronski (2013) and Trémolière et al.\ (2012) studies
  suggest (e.g., see also Baron et al., 2015; Körner \& Volk, 2014).}
However, the key point here is that simply taking utilitarian
considerations into account does not necessarily require deliberation
or System 2 thinking. Mere System 1 thinking suffices to have people
grasp the utilitarian dimensions of a dilemma and appreciate the
conflict with competing deontological considerations. It is this
observation that forces us to postulate that System 1 is also
generating a utilitarian intuition. In other words, in the hybrid
model intuitive and deliberate utilitarianism are complementary rather
than mutually exclusive.

To illustrative the core differences between the hybrid model of moral
cognition that we propose and the alternative serial or parallel
models, we present a schematic illustration in Figure 5. In the serial
model people initially start with System 1 processing which will
generate an intuitive deontological response. This System 1 processing
might be followed by optional generation of a utilitarian response
based on deliberate System 2 processing in a later stage (represented
by time t1 in the figure). In the parallel model these System 1 and
System 2 processes are assumed to be activated simultaneously from the
start. In the hybrid model, there is also parallel initial activation
but this activation concerns cueing of a deontological and utilitarian
System 1 intuition rather than the parallel activation of the two
reasoning systems. But note that, as in the serial model, the initial
System 1 processing can be followed by additional System 2 processing
in a later stage. Indeed, making a final utilitarian decision and
resolving the conflict between competing intuitions in favour of the
utilitarian response is expected to be favoured by the explicit
reflection and justification that is provided by System 2. However,
the key point is that this System 2 deliberation is not needed to
simply take the utilitarian view into account and experience the
conflict with the cued deontological response.

\begin{figure}[t!]\centering
\includegraphics[width=2.75in]{fig5a.eps}\\[2em]
\includegraphics[width=2.75in]{fig5b.eps}\\[2em]
\includegraphics[width=2.75in]{fig5c.eps}\\
\caption*{Figure 5. Schematic illustration of three possible
views on the interplay between System 1 and System 2 processing in dual
process models of moral cognition. Deliberate system 2 processing is
represented by gray bars and intuitive System 1 processing by white
bars. The horizontal axis represents the time flow. In the serial model
(A) reasoners initially only rely on System 1 processing that will cue
an intuitive deontological response. In the parallel model (B) the two
systems are both activated from the start. In the hybrid model (C)
initial System 1 activation will cue both a deontological and
utilitarian intuition. The dashed lines represent the optional nature
of System 2 deliberation in the serial and hybrid model that can follow
the initial System 1 processing in a later stage (represented as t1).}
\end{figure}

It should be noted that the hybrid model that we present does not make
any specific claims about the nature of the System 2 deliberation that
follows the initial System 1 processing. What we refer to as
“utilitarian deliberation” might involve a justification process that
allows people to provide explicit justifications for the initially
cued intuitive utilitarian response. Alternatively, it might involve
demanding inhibitory processing to override one of the conflicting
responses, some deliberate weighting of the utilitarian and
deontological responses, or a combination of all these different
processes. Likewise, the hybrid model does not entail that System 2
deliberation is necessarily restricted to the utilitarian view. It is
not excluded that in some cases people will allocate System 2
resources to deliberate about the deontological response.\footnote{In
  that sense, one could also add a “Deontological Deliberation” grey
  bar to the hybrid model in Figure 5.} Moreover, given that the
impact of load on moral decisions was not robust across our three
studies, one might even question whether there is still a need to
postulate that making a utilitarian decision necessarily requires
System 2 deliberation to start with. Hence, pinpointing the precise
role and nature of the postulated System 2 deliberation phase is
clearly one aspect of the model (or any other dual-process model) that
will need further testing. Clearly, the key contribution of our model
and work lies in the specification of the initial processing stage and
the postulation of a parallel cueing of a deontological and
utilitarian System 1 intuition.

It is also worthwhile to highlight that there might be some confusion
in the field as to which specific interaction architecture the
original dual process model of Greene and colleagues (e.g., Greene
2014; Greene \& Haidt, 2002) entails. Often the model has been
interpreted as postulating a serial processing architecture, although
it is acknowledged that the model is also open to a parallel reading
(e.g., Baron et al., 2015; Koop, 2013; Tinghög et al., 2016). However,
note that it might also be the case that the Greene dual process model
was conceived with a hybrid processing architecture in mind. Under
this interpretation of the Greene model, mere reading of the
utilitarian dilemma option – without any further deliberation ---
suffices to intuitively grasp the utilitarian implications of a
dilemma and detect the conflict with the deontological view. The idea
here is that people cannot be said to have understood a moral
“dilemma” without some understanding of the fact that there are
competing considerations at play. Such understanding would --- by
definition --- imply that people automatically give some minimal
weight to each perspective in their judgment process. Under this
reading, the Greene model always entailed that moral dilemmas cue both
deontological and utilitarian intuitions and it should indeed be
conceived as a hybrid model. Consequently, rather than a revision of
the Greene dual process model our present work should be read as a
correction of the received interpretation of the model. We prefer to
keep a neutral position in this debate.  Whatever the precise model
Greene and colleagues might have had in mind, the key point is that
the different possible incorporations have never been empirically
tested against each other. As even the most fervent proponents of the
dual process model in cognitive science have acknowledged, without a
specification of the interaction, any dual process model is vacuous
(e.g., Evans, 2007; Evans \& Stanovich, 2003).  It is here that the
main contribution of our paper lies: We test the predictions of three
possible architectures directly against each other and present robust
evidence for the hybrid model.

We believe it is interesting to point to the possible wider
implications of the present findings for dual process models of human
cognition, outside of the specific moral reasoning field. As we noted,
hybrid dual process models have already been put forward in studies on
logical and probabilistic reasoning (and the related Heuristics and
Biases literature, e.g., De Neys, 2012; Handley \& Trippas, 2015;
Pennycook, Fugelsang \& Koehler, 2015). In a nutshell, the traditional
serial or parallel dual process models in these fields posits that,
when people are faced with a logical or probabilistic reasoning task,
System 1 will cue an intuitive, so-called “heuristic” response based
on stored associations. Sound reasoning along traditional logical and
probabilistic principles is typically assumed to require deliberate,
System 2 processing (e.g., Kahneman, 2011; Evans \& Stanovich, 2013).
However, empirical studies have demonstrated that even reasoners who
give the intuitively cued heuristic System 1 answer show sensitivity
to the conflict between cued heuristics and logical or probabilistic
principles in classic reasoning tasks – as expressed, for example, by
an increased response doubt (De Neys, Rossi \& Houdé, 2013; Thompson
\& Johnson, 2014; Pennycook, Trippas, Handley \& Thompson, 2014;
Stupple, Ball \& Ellis, 2013; Trippas, Handley, Verde \& Morsanyi,
2016). Critically, this sensitivity is also observed when System 2 is
“knocked out” under load or time pressure (e.g., Bago \& De Neys,
2017; Franssens \& De Neys, 2009; Johnson, Tubau \& De Neys, 2016;
Pennycook et al., 2014; Thompson \& Johnson, 2014). This result
suggests that people consider the logical and probabilistic principles
intuitively and presented one of the reasons to posit a hybrid view in
which System 1 cues simultaneously a heuristic and logical intuition
(e.g., De Neys, 2012; Pennycook et al., 2015). The simple fact that we
want to highlight here is that these findings from the
logical/probabilistic reasoning field show an interesting similarity
with the current findings in the moral reasoning field. Both in the
case of moral and logical/probabilistic reasoning there is evidence
that reasoning processes that are often attributed to System 2 can
also be achieved by System 1. To put it bluntly, in both cases it
seems that System 1 is less oblivious and more informed than it has
been assumed. Whereas this point remains somewhat speculative we hope
that the present study will at least stimulate a closer interaction
between dual process research on moral cognition and
logical/probabilistic reasoning (e.g., Trémolière, De Neys \&
Bonnefon, 2017). We believe that such interaction holds great
potential for each of the fields and the possible development of a
general, all-purpose dual process model of human thinking.

To conclude, the results of the present studies indicate that reasoners
show an intuitive sensitivity to the utilitarian aspects of classic
moral dilemmas without engaging in demanding deliberation. These
findings lend credence to a hybrid dual process model of moral
reasoning in which System 1 is simultaneously generating a
deontological and utilitarian intuition. Taken together, the available
evidence strongly suggests that the core idea of an intuitive
utilitarianism needs to be incorporated in any viable dual process
model of moral cognition. 

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