J Clin Aesthet Dermatol. 2025;18(4):24–27.
by Emmaline Ashley, BA, MCh (Hons), MBBChBAo (Hons), PgCert Derm, PgDipAes; Lee Walker, BDS, MFDS, RCPSG, MJDF, RCS (Eng); and Priyanka Chadha, MBBS (Lond), BSc (Hons), DPMSA (Lond), MRCS (Eng), MSc (Lond)
Drs. Ashley and Chadha are with Acquisition Aesthetics in London, United Kingdom. Dr. Walker is with B City Clinics in Liverpool, United Kingdom.
FUNDING: No funding was provided for this article.
DISCLOSURES: The authors declare no conflicts of interest relevant to the content of this article.
This paper examines the multifaceted nature of beauty, encompassing evolutionary, biological, neurological, cultural, and individual factors. It explores the limitations of objective assessments, such as artificial intelligence (AI) algorithms like the Facial Aesthetic Index and Facial Youthfulness Index, which often fail to capture the diversity of individual preferences and cultural standards. While AI tools can provide valuable insights into facial features, their use in aesthetic medicine should be approached with caution, recognizing the importance of subjective perceptions. We emphasize the need for a collaborative approach that integrates AI insights with clinical expertise and patient involvement to achieve personalized and satisfying outcomes in aesthetic medicine. Ultimately, beauty is a complex and subjective experience that cannot be fully defined or assessed objectively, and successful aesthetic interventions require a holistic approach that values both objective data and individual perspectives.
Keywords: Beauty, facial attractiveness, artificial intelligence, aesthetic medicine, ethics in medicine, facial symmetry, evolutionary biology, facial averageness
Introduction
Defining beauty is a difficult and elusive concept that has long challenged philosophers, artists, and scientists alike. Historically, medical and biological research has focused on quantifiable aspects, such as facial averageness,1–4 symmetry,2,3,5 and sex-specific physical traits.6,7 However, beauty is multifaceted, extending beyond the physical and into the realms of neuroscience, psychology, and philosophy.
While there is ongoing debate about what it means to be beautiful, there is a consensus that possessing beauty is regarded as a beneficial attribute. Facial appearance significantly impacts psychosocial wellbeing and, by extension, an individual’s perceived quality of life.8–10 Beyond this, facial attractiveness also has a significant impact on our social interactions.10,11 Therefore, within the realm of aesthetic medicine, there is a keen interest in obtaining an objective understanding of beauty in order to optimize patient care.12
In recent years, the reliance on digital tools and artificial intelligence (AI) for objective facial assessment has grown, culminating in innovations such as the Facial Aesthetic Index (FAI) and the Facial Youthfulness Index (FYI), two tools designed to assess facial features.12 The FAI analyzes various facial characteristics, such as skin texture, symmetry, and wrinkles, to generate a holistic rating of attractiveness on a seven-point scale.12 The FYI, derived from the FAI analysis, specifically measures the perceived youthfulness of a person’s face. These tools, developed through analyzing vast datasets across diverse demographics, aim to offer unbiased, standardized assessments.
However, the inception of such tools into aesthetic medicine raises certain ethical, philosophical, and practical questions about the nature of beauty and the role of objectivity in its assessment. Can an inherently subjective and multidimensional concept like beauty be adequately captured by algorithms and objective indices? The risk lies in reducing beauty to a set of quantifiable metrics, potentially neglecting the rich tapestry of cultural norms, individual preferences, and emotional responses that contribute to our perception of beauty.
The Mathematics of Beauty
The application of mathematical models in defining beauty aims to provide an objective framework for aesthetic assessment. Aesthetic clinicians are often initially trained to evaluate beauty and attractiveness using ratios and proportions, and in particular the golden ratio.13 Historically, concepts of beauty have often been modeled on Western-centric ideals.13 These ideals, while influential in shaping beauty standards, fail to account for the broader spectrum of human diversity. Take, for example, the division of the face into vertical fifths. It is taught in the neoclassical cannon that these should be quantitatively equal compared to the intercanthal distance.14 However, this principle fails to account for the diverse facial proportions observed in East Asian populations.14
Equally, the use of the golden ratio to define beauty has been a topic of debate and criticism.15 While some theories suggest that the golden ratio represents ideal beauty and proportion (for example, Marquardt’s Phi Mask15), this ratio is not universally applicable or relevant to all cultures and populations. It has been pointed out that this mask is ill-suited for Afro-Caribbean and East Asian faces, and represents more masculine European features.15 Mathematical models like the golden ratio, while offering a quantifiable approach to beauty, are inherently limited by rigid parameters. These models cannot adequately represent the diverse range of facial features and beauty standards found across different cultures and ethnicities. While mathematical models offer a starting point, a deeper understanding of beauty requires exploring its evolutionary and biological roots.
Concepts of Beauty in Evolution and Biology
A classic study underpinning the biological basis of beauty demonstrated that nine-month-old infants prefer to look at the faces of attractive adults over less-attractive adults.2,16 This early inclination towards certain facial features indicates a possible evolutionary basis for beauty standards, and suggests that the assessment of attractiveness has an element of being innate and universal. A meta-analysis of 919 studies involving over 15,000 observers confirmed a consensus on attractiveness, both within and across cultures.17,18
From an evolutionary perspective, sexual selection favors traits that exploit pre-existing sensory biases.2 The “good genes” hypothesis posits that visually appealing sexual traits advertise genetic fitness, and are therefore selected for.2 In other words, physical appearance can serve as a proxy for youthfulness, health, sexual maturity, and social status.19
Facial symmetry has also been linked to attractiveness.2,5,10 This may also have an evolutionary basis, where symmetry can reflect genetic health and freedom from disease.2,5 However, research suggests that only highly asymmetrical faces are unattractive, and that perfectly symmetrical composite faces may be less appealing than asymmetrical “normal” faces.5
Additionally, there is research that suggests that the more “average” a face is, the more attractive it is.2,5,10 The phenomenon of averageness is demonstrated by merging several real faces into a single, composite face. Surprisingly, this composite face often appears more appealing than the majority of the individual faces it was created from.2 This could be because when faces are fused into a composite, specific flaws are blended out.2 It may also be because average faces indicate possession of a more diverse set of genes.10
However, there is also evidence to support that while an average face is attractive, the most attractive faces of all are not the average—demonstrating a U-shaped relationship.2,5,20 In other words, distinctive faces are both the least and most attractive faces.5
The U-shaped relationship of attractiveness suggests that extreme uniqueness can be as compelling as average features. From an evolutionary standpoint, this pattern indicates that while average features might signal genetic diversity and stability, distinctive features might highlight unique genetic advantages or health signals.10 This implies that beauty standards are not only fluid, but can also embrace a wide range of appearances.
Additionally, emphasis on secondary sexual characteristics is often associated with attractiveness.6 Enhancing the distinctly female characteristics of a female composite face—such as a smaller chin, a tinier nose, and a larger forehead—makes the face even more attractive.2 Likewise, features such as prominent cheekbones and thicker lips are also rated as more attractive.5 These features are seen as indicators of a high estrogen-to-testosterone ratio, which is often associated with greater fertility.2,21
Beyond this, research shows that there is also a distinction made between faces that signal the “good genes” of an ideal mate (of evolutionary value), and a face that is simply aesthetically pleasing.21 The perception of facial beauty, especially of the opposite sex, triggers brain areas associated with reward and motivation, leading to behaviors aimed at attracting the opposite sex.21 This mechanism underscores the evolutionary benefit of recognizing and being attracted to traits that indicate genetic fitness and reproductive potential.
However, our ability to recognize beauty extends beyond mate selection, suggesting that evolutionary adaptations have shaped distinct neural processes for assessing potential partners versus appreciating beauty in broader social contexts.21 This implies a complex interplay of neural mechanisms underlying our perception of beauty.
The Neuroscience of Beauty
Various studies have delved into the neural correlates of beauty perception. Initially, visual information is analyzed in the inferior occipital gyri, then progresses to the lateral fusiform gyrus and superior temporal sulcus for further examination.21 The fusiform gyrus plays a crucial role in recognizing faces and analyzing facial features like the eyes, nose, and mouth.17,21 Its processing speed is notably faster for faces considered attractive, facilitating swift recognition.17 Transcranial current stimulation can influence beauty perception, leading to changes in participants’ beauty rating scores of visual stimuli.22 This suggests that neural activity plays a role in shaping beauty perception and can be altered through external stimulation.
The superior temporal sulcus evaluates facial expressions and is linked to other brain areas involved in emotional processing.21 This area also conveys information to the nucleus accumbens and the anterior cingulate cortex within the orbitofrontal cortex, where beauty judgements occur and dopamine is released in response to perceived beauty.17 Functional MRI (fMRI) studies have highlighted these pathways, showing increased blood flow in areas of the brain associated with the recognition of beauty.23 Here, the amygdala plays a key role in the perception of beautiful faces.21 Overall, this suggests that observing and processing a beautiful image or person not only engages specific brain pathways, but also rewards the observer, reinforcing the inherent human attraction to beauty. Therefore, there is a complex interplay between attractiveness, social cues, and brain activity, revealing that beauty perception is not only visual, but also deeply connected to social and reward mechanisms in the brain.24
fMRI studies have also indicated that beauty perception involves both objective parameters (“embodied natural beauty”) and subjective social constructs (“socially endowed beauty”).25 Neural activities in the insula and amygdala correlate with the experience of objective and subjective beauty respectively, supporting the existence of these dual processes.26,27 This distinction underscores the complexity of beauty perception, as it involves both innate responses and culturally-influenced judgments.25 This duality means that while certain aspects of beauty are universally recognized, others are highly subjective and shaped by context and individual experiences.
Beauty and Culture
It is important to explore how cultural contexts shape perceptions of beauty and attractiveness, highlighting the role of familiarity, social learning, and cultural standards. The development of sophisticated human cultural groups has led to culturally specific notions of facial beauty.21
Humans engage in social learning, taking cues from those around them as to what is perceived to be attractive.10 The definitions of beauty vary across different regions, from countries to cities, and even neighborhoods—yet within a specific culture, these notions tend to be consistently understood and assessed, transcending differences in age and gender.28 A person is more likely to perceive higher attractiveness when evaluating another person from the same ethnicity.29,30 Research spanning various cultures reinforces this concept, revealing that individuals within the same cultural or subcultural group often share similar standards of attractiveness.28 Familiarity, fostered through shared cultural experiences, is a powerful driver of attraction and social reward.10
When a layperson is asked to judge attractiveness, a holistic method is typically employed, accounting for a myriad of factors including confidence, posture, genuineness, and adornments.28 Dayan31 proposed a novel model, the “Special Theory of Relativity for Attractiveness,” suggesting that the pursuit of physical beauty alone is not enough; people also desire to appear genuine and feel confident.32 In other words, attractiveness as a multidimensional concept comprising beauty, genuineness, and self-esteem, with “naturalness” being an interpretation of the optimal balance of these factors.32 It is a reminder that beauty, like time, is a relative concept, shaped by individual perspectives and cultural contexts.31
Beauty in Aesthetic Medicine
Clinicians’ perceptions of beauty and attractiveness are shaped by a multitude of factors, including cultural background, geographic location, peer influences, and social media.28 This diversity can lead to a range of aesthetic ideals among providers, resulting in subjective views on beauty, varying treatment priorities, and potentially disparate outcomes. It is crucial to also recognize that patients themselves exhibit a similar range of perspectives, and their individual preferences should be central to treatment planning. Importantly, patient perceptions of beauty do not always align with those of the practitioner. Given these challenges, one of the potential strengths of AI is its perceived objectivity.
To bridge the gap between subjective perceptions and objective assessments, AI tools offer several potential benefits. In order to be objective, clinicians are initially trained to focus on anatomy and mathematical proportions, as discussed previously.14,28 In this context, AI can be an effective teaching aid and learning tool, helping clinicians to objectively understand and quantify facial features. AI can standardize assessment processes, facilitating the training of new practitioners in aesthetic evaluation. By providing a data-driven approach to facial analysis, AI can support clinicians in making informed treatment decisions.
However, given all that has been previously discussed about the complexity of beauty, the use of AI in beauty assessment presents challenges. One concern is the risk of overgeneralization due to limited dataset diversity.33 AI algorithms often rely on datasets that may not adequately represent the full spectrum of human diversity, including various genders and ethnicities. This can lead to recommendations that do not align with the unique aesthetic ideals of diverse patient groups.33 Additionally, while interracial mixing contributes to the richness and diversity of human appearance, it also makes it increasingly challenging to generalize aesthetic characteristics based on traditional racial categories.28 For instance, the notion of distinct “Indian” or “African” features is becoming less relevant due to genetic intermixing. As a result, AI approaches that rely on such categories may not fully capture the nuances of evolving human beauty.
Furthermore, in treatment planning, AI tools may not account for the distinctions of different filler products used in treatments. For example, while Restylane® Lyft (Galderma; Lausanne, Switzerland) and Juvederm™ Ultra Deep (Allergan; Dublin, Ireland) share similar indications, their unique compositions and injection techniques necessitate tailored approaches. Overlooking these distinctions could lead to suboptimal or undesirable results. An AI tool that fails to incorporate this knowledge and experience could generate recommendations that lack the precision required, underscoring the continued importance of clinical judgement in aesthetic procedures.
While AI can quantify certain aspects of facial features, it cannot fully capture the subjective and deeply personal experiences of beauty that vary among individuals. Facial rejuvenation, while ideally informed by anatomy and the aging process, is also a practice grounded in subjective judgment.28 Therefore, the question arises: What is the role of AI-assisted objective measurements in guiding treatment plans, and how can they be integrated with the subjective perspectives of both the patient and clinician?12
Developing an “Aesthetic Eye” for Beauty
Developing an “aesthetic eye” for beauty requires a nuanced understanding of human experiences, cultural backgrounds, and individual identities. It involves an appreciation of the diversity and richness of human aesthetics beyond the measurable and quantifiable. While we can understand the mathematical, evolutionary, or neuroscientific underpinnings of beauty, the deeper we delve, the more we uncover the inherent subjectivity at its core. In fact, a comprehensive understanding of the objective aspects of beauty often underscores the significance of subjective interpretation and emotional resonance. Beauty is expansive and dynamic, encompassing a vast spectrum that cannot be fully captured by algorithms or indexed through an objective lens.
Johannes Honekopp’s research underscores this point, demonstrating that individual preferences (“private taste”) are as influential as shared standards (“shared taste”) in determining attractiveness.29 This finding challenges the notion of a universal beauty standard and has significant implications for the use of AI in aesthetic assessments. AI tools that aim to model beauty objectively do not account for the substantial role of individual preferences.
The challenge, then, becomes one of integrating these subjective experiences with the objective assessments provided by AI tools. AI-driven tools like the FAI and FYI can provide valuable insights and assist in clinical decision-making, but they cannot replace the nuanced understanding of human aesthetics that comes from experience, cultural awareness, and empathy. Therefore, by integrating AI tools with clinical expertise and patient preferences, healthcare providers can leverage the strengths of both approaches. AI can provide objective insights, while clinicians and patients contribute their subjective understanding of beauty, ensuring that treatment plans are both medically sound and personally meaningful. This collaborative, patient-centered approach can lead to more satisfying and personalized care, ultimately improving outcomes in aesthetic medicine.
The debate on the use of AI as an objective tool for beauty assessment highlights the complexity of defining and assessing beauty. It invites a broader reflection on how technology intersects with human values, and the importance of fostering an inclusive and empathetic approach in aesthetic medicine.
References
- Langlois JH, Roggman LA. Attractive faces are only average. Psychol Sci. 1990;1(2):115–121.
- Cellerino A. Psychobiology of facial attractiveness. J Endocrinol Invest. 2003;26(3 Suppl):45–48.
- Thornhill R, Gangestad SW. Human facial beauty: averageness, symmetry, and parasite resistance. Hum Nat. 1993;4(3):237–269.
- Valentine T, Darling S, Donnelly M. Why are average faces attractive? The effect of view and averageness on the attractiveness of female faces. Psychon Bull Rev. 2004;11(3):482–487.
- Baudouin JY, Tiberghien G. Symmetry, averageness, and feature size in the facial attractiveness of women. Acta Psychol (Amst). 2004;117(3):313–332.
- Mitchem DG, Purkey AM, Grebe NM, et al. Estimating the sex-specific effects of genes on facial attractiveness and sexual dimorphism. Behav Genet. 2014;44(3):270–281.
- Perrett DI, Lee KJ, Penton-Voak I, et al. Effects of sexual dimorphism on facial attractiveness. Nature. 1998;394(6696):884–887.
- Borráz-León JI, Rantala MJ, Luoto S, et al. Self-perceived facial attractiveness, fluctuating asymmetry, and minor ailments predict mental health outcomes. Adapt Human Behav Physiol. 2021;7:363–381.
- Cohen JL, Rivkin A, Dayan S, et al. Multimodal facial aesthetic treatment on the appearance of aging, social confidence, and psychological well-being: HARMONY Study. Aesthet Surg J. 2022;42(2):NP115–NP124.
- Little AC, Jones BC, DeBruine LM. Facial attractiveness: evolutionary based research. 2011;366(1571):1638–1659.
- Thornhill R, Gangestad SW. Facial attractiveness. Trends Cogn Sci.1999;3(12):452–460.
- Sattler S, Frank K, Kerscher M, et al. Objective facial assessment with artificial intelligence: introducing the Facial Aesthetic Index and Facial Youthfulness Index. J Drugs Dermatol. 2024;23(1):e52–e54.
- Greywal T, Dayan SH, Goldie K, et al. The perception bias of aesthetic providers. J Cosmet Dermatol. 2021;20(6):1618–1621.
- Prendergast PM. Facial proportions. In: Erian A, Shiffman MA, eds. Advanced Surgical Facial Rejuvenation: Art and Clinical Practice. Springer Berlin Heidelberg; 2012;15–22.
- Holland E. Marquardt’s Phi mask: pitfalls of relying on fashion models and the golden ratio to describe a beautiful face. Aesthetic Plast Surg. 2008;32(2):200–208.
- Langlois JH, Roggman LA, Casey RJ, et al. Infant preferences for attractive faces:rRudiments of a stereotype? Dev Psychol. 1987;23(3):363–369.
- Yarosh DB. Perception and deception: human beauty and the brain. Behav Sci (Basel). 2019;9(4):34.
- Langlois JH, Kalakanis L, Rubenstein AJ, et al. Maxims or myths of beauty? A meta-analytic and theoretical review. Psychol Bull. 2000;126(3):390–423.
- Cunningham MR, Roberts AR, Barbee AP, et al. “Their ideas of beauty are, on the whole, the same as ours”: consistency and variability in the cross-cultural perception of female physical attractiveness. J Pers Soc Psychol. 1995;68(2):261–279.
- DeBruine LM, Jones BC, Unger L, et al. Dissociating averageness and attractiveness: attractive faces are not always average. J Exp Psychol Hum Percept Perform. 2007;33(6): 1420–1430.
- Senior C. Beauty in the brain of the beholder. Neuron. 2003;38(4):525–528.
- Takahashi K, Yotsumoto Y. Testing the reproducibility of the effects of transcranial direct current stimulation: failure to modulate beauty perception by brain stimulation. Front Hum Neurosci. 2022;16:767344.
- Ishizu T, Zeki S. Toward a brain-based theory of beauty. PLoS One. 2011;6(7):e21852.
- Kampe KK, Frith CD, Dolan RJ, et al. Reward value of attractiveness and gaze. Nature. 2001;413(6856):589.
- Zhang W, He X, Lai S, et al. Neural substrates of embodied natural beauty and social endowed beauty: an fMRI study. Sci Rep. 2017;7(1):7125.
- Di Dio C, Macaluso E, Rizzolatti G. The golden beauty: brain response to classical and renaissance sculptures. PLoS One. 2007;2(11):e1201.
- Nakamura K, Kawabata H. Transcranial direct current stimulation over the medial prefrontal cortex and left primary motor cortex (mPFC-lPMC) affects subjective beauty but not ugliness. Front Hum Neurosci. 2015;9:654.
- Greywal T, Dayan SH, Goldie K, et al. The perception bias of aesthetic providers. J Cosmet Dermatol. 2021;20(6):1618–1621.
- Hönekopp J. Once more: Is beauty in the eye of the beholder? Relative contributions of private and shared taste to judgments of facial attractiveness. J Exp Psychol Hum Percept Perform. 2006;32(2):199–209.
- Hughes BL, Camp NP, Gomez J, et al. Neural adaptation to faces reveals racial outgroup homogeneity effects in early perception. Proc Natl Acad Sci USA. 2019;116(29):14532–14537.
- Dayan S, Romero DH. Introducing a novel model: the special theory of relativity for attractiveness to define a natural and pleasing outcome following cosmetic treatments. J Cosmet Dermatol. 2018;17(5):925–930.
- Dayan S, Demesh D. The illusions of time, truth, and aesthetic medicine. J Cosmet Dermatol. 2020;19(5):1266–1267.
- Pai VV, Pai RB. Artificial intelligence in dermatology and healthcare: an overview. Indian J Dermatol Venereol Leprol. 2021;87(4): 457–467.
What Does it Mean to Be Beautiful? Exploring the Limits of AI-Driven Beauty Assessment
Categories:
J Clin Aesthet Dermatol. 2025;18(4):24–27.
by Emmaline Ashley, BA, MCh (Hons), MBBChBAo (Hons), PgCert Derm, PgDipAes; Lee Walker, BDS, MFDS, RCPSG, MJDF, RCS (Eng); and Priyanka Chadha, MBBS (Lond), BSc (Hons), DPMSA (Lond), MRCS (Eng), MSc (Lond)
Drs. Ashley and Chadha are with Acquisition Aesthetics in London, United Kingdom. Dr. Walker is with B City Clinics in Liverpool, United Kingdom.
FUNDING: No funding was provided for this article.
DISCLOSURES: The authors declare no conflicts of interest relevant to the content of this article.
This paper examines the multifaceted nature of beauty, encompassing evolutionary, biological, neurological, cultural, and individual factors. It explores the limitations of objective assessments, such as artificial intelligence (AI) algorithms like the Facial Aesthetic Index and Facial Youthfulness Index, which often fail to capture the diversity of individual preferences and cultural standards. While AI tools can provide valuable insights into facial features, their use in aesthetic medicine should be approached with caution, recognizing the importance of subjective perceptions. We emphasize the need for a collaborative approach that integrates AI insights with clinical expertise and patient involvement to achieve personalized and satisfying outcomes in aesthetic medicine. Ultimately, beauty is a complex and subjective experience that cannot be fully defined or assessed objectively, and successful aesthetic interventions require a holistic approach that values both objective data and individual perspectives.
Keywords: Beauty, facial attractiveness, artificial intelligence, aesthetic medicine, ethics in medicine, facial symmetry, evolutionary biology, facial averageness
Introduction
Defining beauty is a difficult and elusive concept that has long challenged philosophers, artists, and scientists alike. Historically, medical and biological research has focused on quantifiable aspects, such as facial averageness,1–4 symmetry,2,3,5 and sex-specific physical traits.6,7 However, beauty is multifaceted, extending beyond the physical and into the realms of neuroscience, psychology, and philosophy.
While there is ongoing debate about what it means to be beautiful, there is a consensus that possessing beauty is regarded as a beneficial attribute. Facial appearance significantly impacts psychosocial wellbeing and, by extension, an individual’s perceived quality of life.8–10 Beyond this, facial attractiveness also has a significant impact on our social interactions.10,11 Therefore, within the realm of aesthetic medicine, there is a keen interest in obtaining an objective understanding of beauty in order to optimize patient care.12
In recent years, the reliance on digital tools and artificial intelligence (AI) for objective facial assessment has grown, culminating in innovations such as the Facial Aesthetic Index (FAI) and the Facial Youthfulness Index (FYI), two tools designed to assess facial features.12 The FAI analyzes various facial characteristics, such as skin texture, symmetry, and wrinkles, to generate a holistic rating of attractiveness on a seven-point scale.12 The FYI, derived from the FAI analysis, specifically measures the perceived youthfulness of a person’s face. These tools, developed through analyzing vast datasets across diverse demographics, aim to offer unbiased, standardized assessments.
However, the inception of such tools into aesthetic medicine raises certain ethical, philosophical, and practical questions about the nature of beauty and the role of objectivity in its assessment. Can an inherently subjective and multidimensional concept like beauty be adequately captured by algorithms and objective indices? The risk lies in reducing beauty to a set of quantifiable metrics, potentially neglecting the rich tapestry of cultural norms, individual preferences, and emotional responses that contribute to our perception of beauty.
The Mathematics of Beauty
The application of mathematical models in defining beauty aims to provide an objective framework for aesthetic assessment. Aesthetic clinicians are often initially trained to evaluate beauty and attractiveness using ratios and proportions, and in particular the golden ratio.13 Historically, concepts of beauty have often been modeled on Western-centric ideals.13 These ideals, while influential in shaping beauty standards, fail to account for the broader spectrum of human diversity. Take, for example, the division of the face into vertical fifths. It is taught in the neoclassical cannon that these should be quantitatively equal compared to the intercanthal distance.14 However, this principle fails to account for the diverse facial proportions observed in East Asian populations.14
Equally, the use of the golden ratio to define beauty has been a topic of debate and criticism.15 While some theories suggest that the golden ratio represents ideal beauty and proportion (for example, Marquardt’s Phi Mask15), this ratio is not universally applicable or relevant to all cultures and populations. It has been pointed out that this mask is ill-suited for Afro-Caribbean and East Asian faces, and represents more masculine European features.15 Mathematical models like the golden ratio, while offering a quantifiable approach to beauty, are inherently limited by rigid parameters. These models cannot adequately represent the diverse range of facial features and beauty standards found across different cultures and ethnicities. While mathematical models offer a starting point, a deeper understanding of beauty requires exploring its evolutionary and biological roots.
Concepts of Beauty in Evolution and Biology
A classic study underpinning the biological basis of beauty demonstrated that nine-month-old infants prefer to look at the faces of attractive adults over less-attractive adults.2,16 This early inclination towards certain facial features indicates a possible evolutionary basis for beauty standards, and suggests that the assessment of attractiveness has an element of being innate and universal. A meta-analysis of 919 studies involving over 15,000 observers confirmed a consensus on attractiveness, both within and across cultures.17,18
From an evolutionary perspective, sexual selection favors traits that exploit pre-existing sensory biases.2 The “good genes” hypothesis posits that visually appealing sexual traits advertise genetic fitness, and are therefore selected for.2 In other words, physical appearance can serve as a proxy for youthfulness, health, sexual maturity, and social status.19
Facial symmetry has also been linked to attractiveness.2,5,10 This may also have an evolutionary basis, where symmetry can reflect genetic health and freedom from disease.2,5 However, research suggests that only highly asymmetrical faces are unattractive, and that perfectly symmetrical composite faces may be less appealing than asymmetrical “normal” faces.5
Additionally, there is research that suggests that the more “average” a face is, the more attractive it is.2,5,10 The phenomenon of averageness is demonstrated by merging several real faces into a single, composite face. Surprisingly, this composite face often appears more appealing than the majority of the individual faces it was created from.2 This could be because when faces are fused into a composite, specific flaws are blended out.2 It may also be because average faces indicate possession of a more diverse set of genes.10
However, there is also evidence to support that while an average face is attractive, the most attractive faces of all are not the average—demonstrating a U-shaped relationship.2,5,20 In other words, distinctive faces are both the least and most attractive faces.5
The U-shaped relationship of attractiveness suggests that extreme uniqueness can be as compelling as average features. From an evolutionary standpoint, this pattern indicates that while average features might signal genetic diversity and stability, distinctive features might highlight unique genetic advantages or health signals.10 This implies that beauty standards are not only fluid, but can also embrace a wide range of appearances.
Additionally, emphasis on secondary sexual characteristics is often associated with attractiveness.6 Enhancing the distinctly female characteristics of a female composite face—such as a smaller chin, a tinier nose, and a larger forehead—makes the face even more attractive.2 Likewise, features such as prominent cheekbones and thicker lips are also rated as more attractive.5 These features are seen as indicators of a high estrogen-to-testosterone ratio, which is often associated with greater fertility.2,21
Beyond this, research shows that there is also a distinction made between faces that signal the “good genes” of an ideal mate (of evolutionary value), and a face that is simply aesthetically pleasing.21 The perception of facial beauty, especially of the opposite sex, triggers brain areas associated with reward and motivation, leading to behaviors aimed at attracting the opposite sex.21 This mechanism underscores the evolutionary benefit of recognizing and being attracted to traits that indicate genetic fitness and reproductive potential.
However, our ability to recognize beauty extends beyond mate selection, suggesting that evolutionary adaptations have shaped distinct neural processes for assessing potential partners versus appreciating beauty in broader social contexts.21 This implies a complex interplay of neural mechanisms underlying our perception of beauty.
The Neuroscience of Beauty
Various studies have delved into the neural correlates of beauty perception. Initially, visual information is analyzed in the inferior occipital gyri, then progresses to the lateral fusiform gyrus and superior temporal sulcus for further examination.21 The fusiform gyrus plays a crucial role in recognizing faces and analyzing facial features like the eyes, nose, and mouth.17,21 Its processing speed is notably faster for faces considered attractive, facilitating swift recognition.17 Transcranial current stimulation can influence beauty perception, leading to changes in participants’ beauty rating scores of visual stimuli.22 This suggests that neural activity plays a role in shaping beauty perception and can be altered through external stimulation.
The superior temporal sulcus evaluates facial expressions and is linked to other brain areas involved in emotional processing.21 This area also conveys information to the nucleus accumbens and the anterior cingulate cortex within the orbitofrontal cortex, where beauty judgements occur and dopamine is released in response to perceived beauty.17 Functional MRI (fMRI) studies have highlighted these pathways, showing increased blood flow in areas of the brain associated with the recognition of beauty.23 Here, the amygdala plays a key role in the perception of beautiful faces.21 Overall, this suggests that observing and processing a beautiful image or person not only engages specific brain pathways, but also rewards the observer, reinforcing the inherent human attraction to beauty. Therefore, there is a complex interplay between attractiveness, social cues, and brain activity, revealing that beauty perception is not only visual, but also deeply connected to social and reward mechanisms in the brain.24
fMRI studies have also indicated that beauty perception involves both objective parameters (“embodied natural beauty”) and subjective social constructs (“socially endowed beauty”).25 Neural activities in the insula and amygdala correlate with the experience of objective and subjective beauty respectively, supporting the existence of these dual processes.26,27 This distinction underscores the complexity of beauty perception, as it involves both innate responses and culturally-influenced judgments.25 This duality means that while certain aspects of beauty are universally recognized, others are highly subjective and shaped by context and individual experiences.
Beauty and Culture
It is important to explore how cultural contexts shape perceptions of beauty and attractiveness, highlighting the role of familiarity, social learning, and cultural standards. The development of sophisticated human cultural groups has led to culturally specific notions of facial beauty.21
Humans engage in social learning, taking cues from those around them as to what is perceived to be attractive.10 The definitions of beauty vary across different regions, from countries to cities, and even neighborhoods—yet within a specific culture, these notions tend to be consistently understood and assessed, transcending differences in age and gender.28 A person is more likely to perceive higher attractiveness when evaluating another person from the same ethnicity.29,30 Research spanning various cultures reinforces this concept, revealing that individuals within the same cultural or subcultural group often share similar standards of attractiveness.28 Familiarity, fostered through shared cultural experiences, is a powerful driver of attraction and social reward.10
When a layperson is asked to judge attractiveness, a holistic method is typically employed, accounting for a myriad of factors including confidence, posture, genuineness, and adornments.28 Dayan31 proposed a novel model, the “Special Theory of Relativity for Attractiveness,” suggesting that the pursuit of physical beauty alone is not enough; people also desire to appear genuine and feel confident.32 In other words, attractiveness as a multidimensional concept comprising beauty, genuineness, and self-esteem, with “naturalness” being an interpretation of the optimal balance of these factors.32 It is a reminder that beauty, like time, is a relative concept, shaped by individual perspectives and cultural contexts.31
Beauty in Aesthetic Medicine
Clinicians’ perceptions of beauty and attractiveness are shaped by a multitude of factors, including cultural background, geographic location, peer influences, and social media.28 This diversity can lead to a range of aesthetic ideals among providers, resulting in subjective views on beauty, varying treatment priorities, and potentially disparate outcomes. It is crucial to also recognize that patients themselves exhibit a similar range of perspectives, and their individual preferences should be central to treatment planning. Importantly, patient perceptions of beauty do not always align with those of the practitioner. Given these challenges, one of the potential strengths of AI is its perceived objectivity.
To bridge the gap between subjective perceptions and objective assessments, AI tools offer several potential benefits. In order to be objective, clinicians are initially trained to focus on anatomy and mathematical proportions, as discussed previously.14,28 In this context, AI can be an effective teaching aid and learning tool, helping clinicians to objectively understand and quantify facial features. AI can standardize assessment processes, facilitating the training of new practitioners in aesthetic evaluation. By providing a data-driven approach to facial analysis, AI can support clinicians in making informed treatment decisions.
However, given all that has been previously discussed about the complexity of beauty, the use of AI in beauty assessment presents challenges. One concern is the risk of overgeneralization due to limited dataset diversity.33 AI algorithms often rely on datasets that may not adequately represent the full spectrum of human diversity, including various genders and ethnicities. This can lead to recommendations that do not align with the unique aesthetic ideals of diverse patient groups.33 Additionally, while interracial mixing contributes to the richness and diversity of human appearance, it also makes it increasingly challenging to generalize aesthetic characteristics based on traditional racial categories.28 For instance, the notion of distinct “Indian” or “African” features is becoming less relevant due to genetic intermixing. As a result, AI approaches that rely on such categories may not fully capture the nuances of evolving human beauty.
Furthermore, in treatment planning, AI tools may not account for the distinctions of different filler products used in treatments. For example, while Restylane® Lyft (Galderma; Lausanne, Switzerland) and Juvederm™ Ultra Deep (Allergan; Dublin, Ireland) share similar indications, their unique compositions and injection techniques necessitate tailored approaches. Overlooking these distinctions could lead to suboptimal or undesirable results. An AI tool that fails to incorporate this knowledge and experience could generate recommendations that lack the precision required, underscoring the continued importance of clinical judgement in aesthetic procedures.
While AI can quantify certain aspects of facial features, it cannot fully capture the subjective and deeply personal experiences of beauty that vary among individuals. Facial rejuvenation, while ideally informed by anatomy and the aging process, is also a practice grounded in subjective judgment.28 Therefore, the question arises: What is the role of AI-assisted objective measurements in guiding treatment plans, and how can they be integrated with the subjective perspectives of both the patient and clinician?12
Developing an “Aesthetic Eye” for Beauty
Developing an “aesthetic eye” for beauty requires a nuanced understanding of human experiences, cultural backgrounds, and individual identities. It involves an appreciation of the diversity and richness of human aesthetics beyond the measurable and quantifiable. While we can understand the mathematical, evolutionary, or neuroscientific underpinnings of beauty, the deeper we delve, the more we uncover the inherent subjectivity at its core. In fact, a comprehensive understanding of the objective aspects of beauty often underscores the significance of subjective interpretation and emotional resonance. Beauty is expansive and dynamic, encompassing a vast spectrum that cannot be fully captured by algorithms or indexed through an objective lens.
Johannes Honekopp’s research underscores this point, demonstrating that individual preferences (“private taste”) are as influential as shared standards (“shared taste”) in determining attractiveness.29 This finding challenges the notion of a universal beauty standard and has significant implications for the use of AI in aesthetic assessments. AI tools that aim to model beauty objectively do not account for the substantial role of individual preferences.
The challenge, then, becomes one of integrating these subjective experiences with the objective assessments provided by AI tools. AI-driven tools like the FAI and FYI can provide valuable insights and assist in clinical decision-making, but they cannot replace the nuanced understanding of human aesthetics that comes from experience, cultural awareness, and empathy. Therefore, by integrating AI tools with clinical expertise and patient preferences, healthcare providers can leverage the strengths of both approaches. AI can provide objective insights, while clinicians and patients contribute their subjective understanding of beauty, ensuring that treatment plans are both medically sound and personally meaningful. This collaborative, patient-centered approach can lead to more satisfying and personalized care, ultimately improving outcomes in aesthetic medicine.
The debate on the use of AI as an objective tool for beauty assessment highlights the complexity of defining and assessing beauty. It invites a broader reflection on how technology intersects with human values, and the importance of fostering an inclusive and empathetic approach in aesthetic medicine.
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