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The interplay of objective and subjective factors
in empirical aesthetics
Rebecca Chamberlain
Goldsmiths, University of London, 8 Lewisham Way, London SE14 6NW.
r.chamberlain@gold.ac.uk
Abstract The field of empirical aesthetics sets out to understand and predict our
aesthetic preferences (Palmer et al., 2013). Its history dates back to the birth of vis-
ual psychophysics and the work of Gustav Fechner (1876), while multiple models
of aesthetic experience have been proposed in the intervening years (Chatterjee &
Vartanian, 2014; Leder et al., 2004; Pelowski et al., 2017). This chapter briefly sets
out the history of empirical aesthetics, and the state of the research field at present.
I outline recent work on inter-observer agreement in aesthetic preference, before
presenting empirical work that argues the importance of first objective (character-
istics of stimuli) and then subjective (characteristics of context) factors in shaping
aesthetic preference. Considering the role of properties of the stimulus, I will review
literature on the relationship between aesthetic preference and symmetry, shape,
compositional structure, colour and complexity as well as considering the potential
role of statistical properties of images. I will then review putative subjective predic-
tors of aesthetic preference including the role of context, framing and the influence
of information about the artist and the artistic process. Both subjective and objective
approaches will be evaluated from an individual differences perspective, focusing
on the mediating role of familiarity, expertise, culture, cognitive ability and person-
ality. Finally, I will attempt to draw these approaches together with reference to
aesthetic sensitivity: an individual observer’s propensity to have an aesthetic re-
sponse to a particular objective image characteristic, and will explore some putative
factors that may modulate and explain individual differences in aesthetic sensitivity.
Introduction
The field of empirical aesthetics sets out to understand and predict human aes-
thetic preferences (Palmer et al., 2013). The origins of modern-day empirical aes-
thetics reside in the early psychophysical experiments of Gustav Fechner (1876) in
his seminal work ‘Vorschule der Aesthetik’. Fechner’s aesthetics ‘from below’ po-
sitioned objective stimulus properties at the heart of the empirical aesthetic project,
2
providing the foundation for later efforts to establish lawful relationships between
stimulus properties and aesthetic preferences (Birkhoff, 1933; Eysenck, 1940) with
reference to psychobiological mechanisms of arousal (Berlyne, 1974). Such efforts
focused on the predictive value of low-level stimulus properties, such as colour,
symmetry, proportion, contrast, contour, and later on collative properties such as
order, complexity and ambiguity (Berlyne, 1974). Such an approach remains com-
mon in empirical aesthetics. However, more recent research in the field has placed
focus on sensory and cognitive processing dynamics, modelling how observers re-
spond to salient properties of the stimulus (Flavell et al., 2020; Reber et al., 2004),
but also incorporating the sensory and cognitive history of the observer (Cutting,
2003; Zajonc, 1968). The latter approach highlights the critical role subjective as-
pects such as context and exposure play in shaping our aesthetic experiences. Ob-
jective and subjective perspectives have been brought together in comprehensive
aesthetic models in recent years, bringing both psychological and neuroscientific
understanding to the numerous objective and subjective mechanisms identified by
researchers in the field (Chatterjee & Vartanian, 2014; Leder et al., 2004; Leder &
Nadal, 2014; Pelowski et al., 2017; Tinio, 2013). Finally, contemporary accounts
focus on the additional role of curiosity and expectation violation in responses to
artworks (Muth et al., 2015; Van de Cruys & Wagemans, 2011).
This chapter will seek to address two key questions in the field of empirical aes-
thetics. The first is to what extent aesthetic preferences are shared or unique. If pref-
erences are found to be completely idiosyncratic this would strongly suggest that
attempts to establish lawful relations between stimulus properties and aesthetic pref-
erences are bound to fail. However, if preferences are found to be shared to some
degree, this does not necessarily entail that the shared variance among observers is
determined by objective stimulus properties, rather than common subjective expe-
riences (Vessel, 2010; Vessel et al., 2018). Therefore, the second question is to what
extent objective (characteristics of stimuli) and subjective (characteristics of con-
text) properties are responsible for shaping aesthetic preferences. Having addressed
these two critical questions, I will attempt to integrate an individual difference ap-
proach with stimulus-based approaches by exploring recent research on aesthetic
sensitivity. It is worth noting here that the focus of this chapter is on behavioural
empirical studies of preferences for visual stimuli. Much insight can be drawn from
neuroscientific perspectives on visual aesthetics (Chatterjee & Vartanian, 2014) and
from empirical work in other stimulus domains such as music (Brattico & Pearce,
2013), but such perspectives lie beyond the scope of this chapter.
Are aesthetic preferences shared or unique?
Aesthetic preferences are idiosyncratic (Vessel, 2010; Vessel et al., 2018),
but the extent of this idiosyncrasy appears to be strongly dependent on the stimulus
category at the focus of research. Vessel and Rubin (2010; 2018) investigated the
3
proportions of ‘shared’ and ‘private’ taste adult observers displayed across different
stimulus categories. Participants were required to make pairwise preference judg-
ments on pictures of real-world scenes and abstract images, and across-observer
agreement was computed via pairwise correlations between preference judgments
of every pair of participants (Vessel, 2010). Participants showed a high degree of
cross-observer agreement for pictures of real-world scenes (46%), while cross-ob-
server agreement for abstract images was significantly lower (20%). In addition,
within-observer reliability (correlations in participants’ preference estimates be-
tween the first and second half of the testing session) was high for both sets of im-
ages suggesting that variability in cross-observer agreement could not be attributed
to measurement error. In a follow-up study Vessel and Rubin (2018) measured pref-
erences for a much larger stimulus set including: faces, natural landscapes, interior
and exterior architecture, and visual art. Cross-observer agreement was highest for
an ethnically diverse sample of faces (66%), and a sample of natural landscapes
(29%), lower for architecture (12%), and lower still for visual art (8%). The reasons
for variance in cross-observer agreement across these domains could be due to prop-
erties of the stimulus; for example averageness, facial symmetry and sexual dimor-
phism have been shown to be consistent predictors of facial attractiveness (Fink &
Penton-Voak, 2002). On the other hand, such variance could be due to shared or
unique environmental mechanisms such as mere exposure, which posits that ob-
servers develop a preference for stimuli that they have had greater amounts of ex-
posure to (Zajonc, 1968). The following section will explore putative objective pre-
dictors of aesthetic preference in more detail.
Objective predictors of aesthetic preference
Symmetry
Symmetry has been described as an ‘aesthetic primitive’ due to the special status
conferred to it by the visual system (Makin et al., 2018). Increased regularity in
patterns appears to elicit more fluent visual processing, evidenced by increased ac-
curacy and reduced reaction times in behavioural data (Makin et al., 2016) and by
a greater amplitude of the sustained posterior negativity (SPN) in occipital elec-
trodes in event-related potential (ERP) studies (Makin et al., 2016). Correspond-
ingly, increased regularity strongly predicts observers’ implicit (Makin et al., 2012)
and explicit preferences for random dot patterns (Höfel & Jacobsen, 2003; Jacobsen
& Höfel, 2002), an effect that has been replicated in cross-cultural samples (Makin
et al., 2018). Preference for symmetry can be conceptualised as a broader preference
for perceptual goodness, or Prägnanz in the Gestalt psychological tradition (Palmer
4
& Griscom, 2013). In the context of Makin et al. (2016; 2018) perceptual goodness
was mathematically quantified using the Holographic Weight of Evidence Model
(Van der Helm & Leeuwenberg, 1996), which is defined as the relationship between
the evidence for regularity and the total amount of information in a pattern. These
mathematical approaches to stimulus properties overlap with computational ap-
proaches to aesthetics which are further elaborated in the section on Global Image
Properties below. Beyond the simple dot patterns used in the aforementioned studies
(Höfel & Jacobsen, 2003; Jacobsen & Höfel, 2002; Makin et al., 2012, 2016, 2018),
symmetry is also a predictor of preference for more complex and ecologically-valid
stimuli such as faces, flowers and landscapes (Bertamini et al., 2019; Hůla & Flegr,
2016; Perrett et al., 1999). Two distinct mechanisms may underlie preference for
symmetry. The first is perceptual fluency (Reber et al., 2004); more symmetrical
stimuli are easier to process by the visual system as evidenced by neuroscientific
and behavioural data, and ease of processing gives rise to feelings of pleasure and
reward (Makin et al. 2018). On the other hand preference for symmetry may result
from sexual selective mechanisms via an association between symmetry and phys-
ical fitness, a view that is supported by the fact that symmetry preference is strong-
est for faces compared with other non-biologically relevant stimuli (Little, 2014).
Shape and composition
Rudolf Arnheim (1965) argues compellingly for the significance of perceptual
goodness in his seminal work ‘Art and Visual Perception’, demonstrating its rele-
vance for higher-order shape and compositional properties of visual stimuli. There
has been much speculation concerning whether the golden ratio (or golden section,
denoted by the symbol ϕ) is a signifier of perceptual goodness in works of art and
design, and the presence of the golden ratio was one of the first objective stimulus
properties to be investigated in empirical aesthetics (Fechner, 1876). However,
there is little evidence to support the existence of a preference for the golden ratio.
Rather, in-depth studies on this topic have revealed preferences converging on pro-
totypical geometric shapes (McManus, 1980; McManus & Weatherby, 1997) and
on compact triangular shapes (Friedenberg, 2012). In terms of shape contour, a ro-
bust preference for curvature relative to angularity has been found for abstract geo-
metric shapes, real-life objects and environments (Bar & Neta, 2006; Palumbo et
al., 2015, 2020; Vartanian et al., 2013), a preference which has found to be reliable
in cross-cultural research (Gómez-Puerto et al., 2016). The origin of a preference
for curvature remains a debate in the literature. Some authors suggest it derives from
optimal stimulation of the visual system via Gestalt principles such as good contin-
uation (Bertamini et al., 2016), while other researchers argue that a preference for
curvature derives from an evolutionary adaptive avoidance of sharp stimuli (Bar &
Neta, 2006),
5
Extending out from preference for proportion and contour of singular forms,
Arnheim (1965) referred to the tension inherent in the configuration of forms, even
in a stimulus as simple as a circle within a frame (Figure 1). Arnheim posited that
observers prefer specific compositional arrangements that ensure balance and pre-
serve meaning. This was explored empirically in a series of studies in which partic-
ipants rated the goodness of dots placed in different locations in relation to a sur-
rounding frame (Wickens et al., 2008). The authors discovered a preference for dots
located in the centre and along the medial axes of a rectangular frame, lending sup-
port for Arnheim’s conjecture. This ‘centre-bias’ has since been replicated in studies
on photographic composition (Abeln et al., 2016) and drives eye movements during
free viewing of visual images (Judd et al., 2011; Tseng et al., 2009).
Fig. 1. Arnheim’s (1965) example of the tensions inherent in a form within a frame; the disk may
be perceived as being ‘drawn toward the contour to the right’ (p.12) and if the distance between
the disk and frame is altered, the effect may be weakened or there may be a contrary repulsion
effect.
However, the positioning of objects within a frame also interacts with an object’s
identity, such that objects facing or moving left-to-right are more preferred in the
left-hand side of the frame, and vice-versa, a phenomenon termed the inward bias
(Wickens et al., 2008). In a similar manner, vertical positioning of objects in a frame
interacts with the affordance spaces of those objects, such that a bowl is most pre-
ferred in a lower position in a frame, and a light fitting is preferred in a higher po-
sition in a frame (Sammartino & Palmer, 2012a). Such interactions make it increas-
ingly difficult to make straightforward predictions concerning which arrangement
of forms within a frame will be judged to be the most aesthetically pleasing.
Colour
Palmer & Schloss (2010) demonstrated that there are robust relationships be-
tween colour attributes hue, lightness and saturation and preferences for those at-
tributes. Western observers show relative preferences for hues at the blue end of the
spectrum and for relatively more saturated colours. Ou et al. (2004, 2018) theorised
that colour preferences are based on semantic associations with particular hues,
whilst Hurlbert & Ling (2007) demonstrated that cone-opponent colour processing
predicted colour preference curves. However, colour preferences show intriguing
6
hue-lightness interactions, such that observers show a marked dislike for dark yel-
lows and oranges, which are not explained successfully in the aforementioned the-
ories. This pattern of colour preference is accounted for by Ecological Valence The-
ory (EVT; Palmer & Schloss, 2010) which posits that colour preferences are
determined by the emotional valence of objects associated with those colours. Thus,
dark yellows and oranges are arguably disliked due to their associations with bio-
logical waste, and blues are preferred due to their association with clear skies and
water. This theory was empirically supported by amalgamating data from partici-
pants on their: object-colour associations, object valence, and object-colour match
ratings, creating a weighted affective valence estimate (WAVE). WAVEs predicted
participants colour preference data remarkably well (Palmer & Schloss, 2010) and
colour preferences could be altered by experimental exposure to objects with nega-
tive or positive valence (Strauss et al., 2013). Subsequent studies revealed that col-
our preferences could also be linked to associations with abstract concepts, such as
an observer’s university and political affiliation (Schloss et al., 2011; Schloss &
Palmer, 2014).
Order, complexity and Global Image Properties
In his influential book ‘Studies in the new experimental aesthetics: Steps towards
an objective psychology of aesthetic appreciation’ Daniel Berlyne (1974) posited
that stimuli of intermediate complexity generate an optimal level of arousal, and
should therefore be most preferred by observers. However, this conjecture has found
limited support, with empirical findings obscured by different conceptualisations
and manipulations of complexity (Nadal et al., 2010). Recent research has high-
lighted the complementary role of order or unity in Berlyne’s Psychobiological The-
ory, demonstrating that an optimal balance or combination of order and complexity
predicts ratings of soothingness and fascination for images of organised objects
(Van Geert & Wagemans, 2019). The interplay of order and complexity was first
highlighted by Birkhoff (1933) who developed a mathematical formula for aesthetic
preference via a balance of order and complexity (Van Geert & Wagemans, 2020),
foreshadowing computational approaches to aesthetics (Brachmann & Redies,
2017).
Image statistical approaches in aesthetics aim to determine Global Image Prop-
erties (GIP) of a stimulus that can be automatically computed and related to image
preference (Letsch & Hayn-Leichsenring, 2020). Image statistical analysis can pro-
duce a number of different measures including: fractality, self-similarity, complex-
ity, and anisotropy (variation in gradient orientations in an image). Statistical anal-
ysis of artworks has revealed that they are similar to natural scenes (Graham et al.,
2009; Graham & Redies, 2010; Redies et al., 2012) and that different styles and
periods of art can be attributed to their underlying image statistics (Hayn-Leichsen-
ring et al., 2017; Mather, 2018). Furthermore, image statistics correlate with verbal
7
descriptions of artworks, suggesting that they capture meaningful aspects of visual
stimuli (Letsch & Hayn-Leichsenring, 2020; Lyssenko et al., 2016). Image statisti-
cal measures have also been used to study aesthetic responses to artworks, with
observers preferring less self-similar (statistical features of the whole image are
comparable with smaller parts of the image) paintings of representational still-lifes
and landscapes, and less complex portraits (Hayn-Leichsenring et al., 2017). How-
ever, research has revealed that image statistics are not robustly predictive of pref-
erence for abstract artworks (Letsch & Hayn-Leichsenring, 2020; Mallon et al.,
2014). Finally, a reliable preference for fractal images in a specific fractal domain
(1.3-1.5) has been found in both artworks and non-artistic images (Graham et al.,
2010; Graham & Redies, 2010; Spehar et al., 2003, 2015). Computational ap-
proaches constitute a highly objective approach to the study of stimulus-driven aes-
thetic preference, but as a result can present difficulties in interpretation of experi-
mental findings. This is especially true for images with higher ecological validity
which vary not only on these lower-level visual features, but also on mid-level fea-
tures associated with element grouping and higher-order properties such as semantic
associations with both abstract and representational content, and which are not cur-
rently captured by these computational methods.
Do aesthetic primitives exist?
It is easy to mistake the presence of robust relationships between stimulus prop-
erties and aesthetic preference as evidence for universal, evolutionarily hard-wired
preferences. However, even the most reliable preferences for particular stimulus
properties can be the result of shared enculturation or exposure. For example, Huang
et al. (2018) found that both adults and 4 year-old children spontaneously attend to
symmetrical patterns, but that preference for symmetrical patterns was evident in
adults but not in children, calling into question the argument that processing fluency
underpins preference for symmetry. Rather, Huang et al. (2018) posit that mere ex-
posure (Zajonc, 1968) may account for a preference for symmetry in adulthood.
Furthermore, while the story of empirical aesthetics centres around group-level re-
sponses to manipulation of objective stimulus properties, authors consistently high-
light a high level of reliable variance in observers’ aesthetic responses to even very
simple stimuli.
Drawing on some of the stimulus properties discussed above, Jacobsen and Höfel
(2002) found evidence of substantial individual differences in preference for sym-
metry, while Bertamini et al. (2019) found that individual differences for symmetry
for one stimulus class did not predict preference for symmetry in another stimulus
class, suggesting that a unitary preference for symmetry across stimulus categories
does not exist. Preference for complexity in artworks is determined to some extent
by individual differences in visual working memory capacity (Sherman et al., 2015)
and the soothingness of order is predicted by sub-clinical traits associated with
8
organising tendencies in obsessive compulsive disorder (Van Geert & Wagemans,
2019). Cross-cultural research has revealed differences in preferences for spatial
composition, finding that preference for an object’s location in a frame is mediated
by the observer’s culture’s prevailing reading direction (Chokron & De Agostini,
2000; Ishii et al., 2011; Pérez González, 2012). Furthermore, Schloss and Palmer
(2017) found that Chinese participants’ WAVEs were predicted better by symbolic
associations (red=revolution) and US participants’ WAVEs by object associations
(red=apple), while Taylor et al. (2013) found that WAVEs did not predict colour
preference in the Himba tribe of Namibia. Finally, McManus et al. (2010) discov-
ered large and stable individual differences in preferences for proportioned rectan-
gles, with very simple patterns being ascribed individualised meanings (McManus
& Wu, 2013). This finding lends support to the notion of the ‘Gestalt nightmare’, in
which even the weakest stimuli elicit complex semantic associations in the viewer,
which presents huge challenges for identifying group-level preferences (Makin,
2016). Indeed, semantic associations of stimuli often far outweigh the influence of
any lower-level stimulus features on aesthetic preference, as demonstrated in Mar-
tindale’s (1990) critical explorations of Daniel Berlyne’s (1974) Psychobiological
Theory. The prominent role of individualised semantic associations casts doubt on
the possibility of establishing lawful relations between stimulus properties and aes-
thetic preferences.
Subjective determinants of aesthetic preference
Having considered stimulus-based properties that influence aesthetic preference,
we can now turn to subjective properties. Subjective factors tend be broadly at-
tributed to observer-level (personality, expertise, exposure) and context-level (fram-
ing, knowledge about the artist and process) variables. The following section will
focus on the latter, and take an individual differences approach to these variables at
the conclusion of the section to ascertain the extent to which such contextual factors
have predictable effects on aesthetic preference across observers.
Effect of context
Context has a large impact on aesthetic preference, particularly for visual works
of art. Sammartino and Palmer (2012b) showed that the seemingly robust centre and
inward biases for spatial composition could be manipulated by the addition of titles
that changed the metaphorical meaning of an image. Complementarily, labelling an
artwork with a metaphorically congruent title leads to increased meaning (Cupchik
et al., 1994; Leder et al., 2006) and aesthetic appreciation (Leder et al., 2006; Millis,
2001; Russell & Milne, 1997) and providing titles that accentuate particular aspects
9
of the image (e.g. presence of depicted movement) leads to increased sensory
awareness of those attributes (Mastandrea & Umiltà, 2016). The presence of an ar-
tistic frame around a stimulus can also have an impact on the quality and intensity
of aesthetic judgements. Displaying objects in unexpected contexts (e.g. a post-box
on a tennis court) induces an aesthetic stance; observers are more likely to respond
at the poles of an aesthetic Likert scale for objects in abnormal contexts, and more
neutral aesthetic responses toward objects in semantically congruent contexts (Kirk,
2008). Informing observers that a set of photographs of mouldy food come from an
art exhibition in contrast to a health and safety booklet has no impact on reports of
disgust but does modulate positive valence toward the photographs (Wagner et al.
2014). Furthermore, perceived beauty and positive affective responses are more
tightly linked in artistic contexts (Wagner et al., 2014).
Effect of artist and process
Knowledge about the creative process and the artist herself can also modulate
aesthetic responses to artworks. Informing participants that an artwork was made
by a professional artist rather than the experimenter leads to increased aesthetic rat-
ings for the same stimuli (Kirk et al., 2009), while labelling an artwork as created
by a famous artists boosts its aesthetic appraisal further (Mastandrea & Crano,
2019). Contrariwise, attribution of part of the creative process to a computer algo-
rithm leads observers to downgrade their liking of an artwork (Chamberlain et al.,
2018) and artworks with an association with criminal activity such as graffiti tags
also elicit diminished aesthetic appraisal relative to visually similar artforms such
as calligraphy (Chamberlain et al., in press). These effects likely operate through
observers’ assumptions about the creative process. The effort heuristic (Kruger et
al., 2004) posits that perceived effort is used as proxy for quality in the absence of
disambiguating information. In a series of studies, Kruger et al. (2004) showed that
participants valued artworks and designed objects more if they were informed that
they took longer to create. This effect was most pronounced in situations in which
the quality of the object was difficult to determine purely on the basis of sensory
information (Kruger et al. 2004). However, the effort heuristic itself is malleable. If
observers are required to read a piece of text highlighting the role of talent (in con-
trast to effort) prior to evaluating objects, experimental effects are reversed and par-
ticipants rate more quickly created artworks as more valuable (Cho & Schwarz,
2008). Finally, the authenticity of an artwork plays a large role in its aesthetic re-
ception. An artwork’s history is important because, being a non-functional item in
the practical sense, it is prone to biases around contagion, the notion that it is the
end point of a performance, and intuitions about its originality and scarcity (New-
man & Bloom, 2012). In support, Newman and Bloom (2012) found that informing
observers that an object was a duplication of an existing object led to devaluation
of the duplicate, but only in the context of artworks (paintings) not artifacts (cars).
10
Supporting the notion that contagion is also an important factor in the valuation of
art, the contact level between creator and object had a much larger impact on per-
ceived value of artworks than artifacts (Newman & Bloom, 2012).
Stability of contextual influences
Whilst categorised as subjective determinants of aesthetic preference, some of
the contextual effects described above, such as the effort heuristic or essentialist
beliefs associated with duplication, could conceivably account for some of the
shared variance in aesthetic attitudes if sufficiently stable within a given cultural
setting (Vessel, 2010; Vessel et al., 2018), whilst others are by their nature transient.
Effects of authorship on aesthetic preference do not seem to diminish if the re-
sponses of expert artists are compared with non-experts (Chamberlain et al. 2018),
suggesting that these biases concerning artistic process are not superseded by artis-
tic knowledge. However, individual differences in expertise do determine the mag-
nitude of framing effects where the framing relies on adequate recognition of pres-
tige (Verpooten, 2018; Verpooten & Dewitte, 2017).
Finally, many studies have shown that the personal context of the observer in
terms of their demographics and personality affects the kind of artistic stimuli they
seek in the first instance. Both expertise and the Big Five personality factor of
‘openness to experience’ (McCrae, 2007) have been shown to be predictive of pref-
erence for abstract and modern art (Batt et al., 2010; Chamorro-Premuzic et al.,
2009; Kruger et al., 2004; McManus & Furnham, 2006; van Paasschen et al., 2015).
Openness to experience represents a tendency towards intellectual curiosity, aes-
thetic sensitivity, liberal values, and emotional differentiation (McCrae, 2007) and
also predicts preference for the visual arts more generally (Feist & Brady, 2004)
and the prevalence of aesthetic ‘chills’ (Silvia & Nusbaum, 2011). Need for cogni-
tive closure, an aversion toward semantic and sensory ambiguity which can be mod-
ulated in a state or trait-like manner, also predicts dislike for abstract art (Ostrofsky
& Shobe, 2015) and for ambiguous movie endings (Wiersema et al., 2012). Exper-
tise has a marked influence over how observers inspect and categorise artworks
(Augustin & Leder, 2006; Vogt & Magnussen, 2007; Zangemeister et al., 1995) and
an observer’s willingness to engage with abstract and ambiguous art (Silvia, 2013;
van Paasschen et al., 2015). Thus, it can be seen that stable and fluctuating observer-
centred and context-centred variables modulate aesthetic preferences in a complex
and interacting manner. The next section will attempt to summarise the effects of
both objective and subjective predictors of aesthetic preference and introduce an
approach that takes into account the action of objective features at the group-level
and individual differences at the subject level.
11
Considering the interplay between objective and subjective
approaches
The previous sections have summarised evidence for both objective and subjec-
tive between-groups effects on aesthetic preference. Objective features such as sym-
metry, proportion, contour, colour and composition show reliable associations with
aesthetic preference, particularly for simple stimuli that accentuate the target stim-
ulus property. Similarly, contextual information and inferences about effort and au-
thenticity demonstrate reliable effects on perceived value of visual stimuli. How-
ever, a consistent caveat to these group-level effects is the existence of substantial
and reliable differences which do not merely represent variance due to error but can
instead be attributed to person-level variables. The aetiology of these individual dif-
ferences can be attributed to multiple sources. Behavioural genetic research implies
that variation in genes account for a limited proportion (approximately 30%) of the
variance in perceived facial attractiveness (Germine et al., 2015), and a similar pro-
portion of the variance in the intensity of aesthetic appraisal of abstract objects and
scenes (Bignardi et al., 2020). The remaining variation likely lies within unique
environmental factors, due to individual differences in exposure and enculturation.
Individual differences in expertise and personality likely play a strong role in mod-
ulating the role of objective predictors, an issue that has been addressed with the
revival of the concept of aesthetic sensitivity.
Aesthetic sensitivity
A useful way of conceptualising individual differences in empirical aesthetics is
through the notion of aesthetic sensitivity. This concept originates in the work of
Hans Eysenck, who posited the existence of an individual difference in the ability
to detect objective beauty in a stimulus, similar to the notion of a general intelli-
gence factor, g (Eysenck, 1940). It will have become clear that establishing an ob-
jective notion of beauty as a property of the stimulus was bound to fail. However,
recently researchers have revived the label if not the underlying meaning of Ey-
senck’s aesthetic sensitivity (Corradi et al., 2019, 2020). Under its revised concep-
tion, aesthetic sensitivity is the extent to which a particular objective feature (sym-
metry, contour, complexity) influences an observer’s aesthetic valuation. Empirical
support for the existence of aesthetic sensitivity was derived from a study which re-
examined stimuli from a seminal study on curvature preference (Bar & Neta, 2006)
and found both group-level preference for curvature as well as large individual dif-
ferences, across two different stimulus categories (real objects and abstract designs;
Corradi et al. 2019). A follow-up study using a larger range of stimuli again found
evidence for high variability in preference for curvature, symmetry, complexity and
balance in visual stimuli (Corradi et al. 2020). Furthermore, sensitivity across
12
different stimulus properties was not correlated, although sensitivity was stable over
time, echoing existing individual difference research (Bertamini et al., 2019;
McManus et al., 2010).
Research exploring the underlying determinants of aesthetic sensitivity is still in
its infancy. Individual differences in aesthetic sensitivity for contour and symmetry
was found to be weakly predicted by expertise, but not by personality factors such
as openness to experience (Corradi et al. 2020). In a similar study, Cotter et al.
(2017) found individual differences in preference for curvature could be explained
by personality and expertise. It is possible that visual sensitivity, that is the extent
to which individuals can visually detect differences in symmetry, contour, balance,
may be predictive of aesthetic sensitivity. Research on fractal patterns suggests that
observers’ preferences for levels of fractality and their visual sensitivity to those
particular patterns are tightly linked (Spehar et al., 2015). It would be valuable to
investigate whether an observer’s ability to detect the curvature of contours, the
presence of symmetry and the objective complexity of an image, predicted their
aesthetic sensitivity for the same stimulus feature. Whilst the focus of research on
aesthetic sensitivity is predominantly focused upon stimulus-based features which
influence aesthetic preference, it is reasonable to believe that aesthetic sensitivity
could be extended to the realm of subjective factors as well. Some observers may
be more or less sensitive to the effect of context, or of factors associated with the
artist or artistic process. This is indicated by a study finding that prestige effects
(stating that an artwork was located at the Museum of Modern Art in New York
rather than a local art gallery) only impact the aesthetic preferences of expert artist
observers (Verpooten, 2018; Verpooten & Dewitte, 2017). It is also possible that
aesthetic sensitivity functions in a domain-specific manner. Objective and subjec-
tive features of natural and man-made objects may influence aesthetic preferences
of observers in different ways. It is possible that biologically- relevant stimuli in-
duce sensitivity at the level of stimulus properties, while artworks elicit sensitivity
at the level of subjective factors (Vessel & Rubin, 2010; 2018). This domain-spec-
ificity may further interact with other individual differences measures (such as ex-
pertise) whereby sensitivity to objective and subjective features is determined by
the level of artistic knowledge an individual has. The notion of aesthetic sensitivity
is a useful tool with which to move beyond group-level principles in empirical aes-
thetics, and to categorise and predict the individual differences that permeate the
data collected in this domain.
Conclusion
This chapter has provided an overview of empirical psychological perspectives
to aesthetic preferences. It can be seen that contemporary approaches to the inves-
tigation of aesthetic preferences are still heavily influenced by early work in the
field (Fechner 1876; Berlyne, 1971) which strove to identify lawful relationships
13
between objective stimulus properties and aesthetic responses. This approach has to
a large extent failed, partly due to the combinatorial influence of objective factors
(Makin, 2016) and the myriad subjective influences that often supersede the effects
of stimulus properties on aesthetic preference. However, we have seen that there are
robust and replicable group-level effects of stimulus features like symmetry and
curvature which appear to be culturally invariant (Gomez-Puerto et al. 2018; Makin
et al. 2018), suggesting that it is not necessary to abandon all efforts to identify
objective determinants of aesthetic preferences. Contextual factors have recently
received more attention as researchers pursue more complete models of the aesthetic
process. It is clear that information about the artist and the artistic process has a
large impact on the strength of aesthetic judgments to artistic stimuli (Chamberlain
et al. 2018; Mastandrea & Cruno, 2019; Kirk et al. 2009; Kruger et al. 2004; New-
man & Bloom, 2012). Merely framing a sensory experience as being one of viewing
an artwork, impacts on the kind of emotional and evaluative response the observer
has to the artwork (Wagner et al. 2014; Kirk et al. 2008).
Group-level objective and subjective effects aside, permeating much of this re-
search is the observation that people significantly and reliably differ in their aes-
thetic responses to stimulus features. The question of why people differ in their aes-
thetic judgments has been present since the inception of empirical aesthetics, but
has gained much more prominence in recent years (Vessel & Rubin, 2010; Vessel
& Rubin, 2018; Cotter et al. 2017; McManus et al. 2010). Putative mechanisms for
individual differences in aesthetic span both genetic and environmental influences.
These sources of variance encapsulate differences in exposure via expertise (both
practical and intellectual knowledge of the artistic domain) and culture, and trait-
level differences due to cognitive ability and personality. While there is a promising
line of research exploring the aetiology of individual differences for stimulus fea-
tures, there is very little research exploring the effect of individual differences in
response to contextual manipulations, which is likely to be a fruitful line of research
in the future. Furthermore, findings concerning individual differences can be better
understood in relation to the notion of aesthetic sensitivity, which posits that indi-
viduals’ aesthetic responses are driven to a greater or lesser extent by different fea-
tures of the stimulus and context. By combining what we know about the relatively
stable subjective and objective features of an aesthetic experience alongside the
sources of variance surrounding them, it seems possible to develop a more complete
understanding of the seemingly unpredictable nature of individual aesthetic prefer-
ences.
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