Updated June 2024
It took me an astonishing three years to finally finish reading a book. Not because I’m a slow reader – I can devour massive tomes like Brandon Sanderson’s The Way of Kings in a single day. So, what was it about this particular book that made it such a protracted journey?
Let me set the stage. This book has been generating significant buzz, especially within the animal training community and among behavior analysts.
The book is How Emotions Are Made by Lisa Feldman Barrett, a psychology professor and neuroscientist. In it, she presents a compelling argument, in many eyes, that emotions are constructed rather than innate. While many behavior analysts embrace this idea, I find myself a dissenting voice, disagreeing with some of the book’s fundamental conclusions.
Swimming Against the Behavioral Tide
Before diving into my objections, let’s understand the core concept of the Constructed Theory of Emotions (CToE).
Unpacking the Constructed Theory of Emotions (CToE)
Barrett’s central argument is that emotions are not inborn but constructed. CToE posits that emotions are not simply our reactions to the world; they are our interpretations of it. Our past experiences shape how we understand incoming stimuli, and emotions are actively built from sensory input, prior learning, and language.
In her book, Barrett seeks “fingerprints of emotions”—evidence for innate facial expressions linked to specific emotional states or dedicated brain regions (“fear center,” “anger center”). She concludes that innate emotional facial expressions don’t exist. Smiling when happy, for example, is learned by imitating others. She also challenges the idea of distinct brain locations for emotions like sadness, fear, or anger, dismissing them as localized “brain blobs.” Instead, she supports research suggesting that each emotion is a whole-brain state, with emotional processing occurring throughout the brain.
She refutes the “classic” view of emotions as innate. “Human beings are not at the mercy of mythical emotion circuits buried deep within animalistic parts of our highly evolved brain: we are architects of our own experience” (p. 40).
Infants, according to Barrett, don’t experience emotions because they lack the conceptual framework to construct them. They feel affect—pleasant or unpleasant sensations—but not fear, sadness, or joy.
Barrett further proposes that without a concept to describe an emotion, one cannot perceive it. Bodily sensations might be felt, but precise labeling is impossible. This concept is particularly relevant when we Learn Ludicrous Emoticons and their meanings as a modern form of emotional expression. Just as we learn to associate specific emoticons with feelings, Barrett suggests that our emotional range is limited by our emotional granularity—the ability to construct and identify nuanced emotional experiences. Language is crucial; without it, there are only pleasant or unpleasant feelings. Specific emotion concepts emerge as we label them linguistically. A person with low emotional granularity might feel a stomachache in a stressful situation, while someone with a richer emotional vocabulary might recognize anger.
CToE extends this to animals, suggesting they don’t experience emotions but only affect. Lacking language, they can’t categorize emotions, experiencing the world as pleasant or unpleasant situations with varying arousal levels—but without emotions like fear, anger, sadness, or joy.
Our perception of animal emotions, CToE argues, stems from anthropomorphism and projection. We commit the mental inference fallacy, unknowingly applying our own emotion concepts to observed animal behaviors. A dog crouching with ears back and lip licking might be interpreted as fearful, but Barrett suggests it’s merely experiencing an unpleasant sensation, not “fear.”
“Construction views of emotion are frequently misinterpreted as saying “dogs don’t have emotions”[…] Such simplistic statements are meaningless because they assume emotions have essences so that they can exist, or not, independent of any perceiver. But emotions are perceptions, and every perception requires a perceiver. And therefore every question about an instance of emotion must be asked from a particular point of view.” (p. 272)
In essence, CToE views emotions as concepts we create to understand our feelings in situations characterized by affect, which ranges from pleasant to unpleasant, with varying arousal. There’s no inherent “thing” called fear, rage, or happiness, for humans or animals.
This is my understanding of the book’s central themes and conclusions, particularly relevant to animal behavior and welfare. However, I have significant reservations about these conclusions. My initial reaction after reading the first chapter was, “This is clearly wrong.” I set the book aside, hoping someone would debunk it, saving me the trouble.
Years passed, and no critique emerged. Instead, I witnessed parts of the animal training world embracing CToE as dogma. At a conference, a leading behavior analyst even suggested discarding older emotion literature, hailing CToE as the new truth.
With no critique forthcoming, I decided to read the book thoroughly and write my own, in blog form for accessibility and ease of revision. Consider this a work in progress, subject to evolution as my understanding deepens. Science is, after all, about observation, experimentation, and open discussion, with theories evolving as we learn.
My expertise lies in ethology, not neuroscience or statistics. Much of the book’s information is beyond my direct competence to assess experimental design and measurement validity. However, my evolutionary perspective as an ethology professor allows me to confidently raise objections to CToE.
From an evolutionary standpoint, the Constructed Theory of Emotions is fundamentally flawed.
Here’s why.
The Evolutionary Lens
When evaluating any theory about behavioral or physical traits in humans or animals, an evolutionary perspective is crucial. It acts as a litmus test: Does the theory align with evolutionary principles? If so, we can explore the details. If not, it’s likely flawed and needs reconsideration.
Does the theory make sense from the evolutionary perspective?
Evolutionary biology dictates that everything in biology must be evolutionarily sound, barring divine intervention or extraterrestrial influence. Our biological world, including humans, evolved under natural selection, where only the best-adapted individuals typically survive.
A key question in evolutionary biology is: “Would someone with this trait fare better or worse than someone without it?” In this case, “Would someone who constructs emotions fare better or worse than someone with innate emotions?” Which strategy is more effective for survival?
Consider a thought experiment: prehistoric humans living in a group. Imagine two emotional strategies due to random mutations: Innate Emotions (fear, anger, sadness, etc.) and Constructed Emotions (learning emotional responses through experience and labeling affects).
Picture yourself, with constructed emotions, digging for roots on the savanna when a saber-toothed tiger charges. CToE suggests you’d experience unpleasantness and arousal, but without prior experience with saber-toothed tigers, you’d need to experiment to find the best response. Run? Yawn? Freeze? Keep digging? Trial and error would determine success.
However, in situations like a tiger attack, errors can be fatal. Of the options, only running offers a chance of survival.
Now, consider another prehistoric human with innate emotional responses, like running from danger. Upon seeing the tiger, they’d experience fear and instinctively run or exhibit other fear-related behaviors.
The individual with innate fear responses is far more likely to survive a tiger attack than the one experimenting through trial and error. In subsequent generations, genes for innate fear responses will become more prevalent than those for constructed emotions, eventually leading to the extinction of the “experimenter” strategy.
This is natural selection.
My initial rejection of How Emotions Are Made stemmed from this: CToE violates evolutionary theory. Learned emotions are not an Evolutionarily Stable Strategy (ESS). Innate emotions, a more effective strategy, would inevitably dominate over evolutionary time.
Evolutionary perspective is essential for understanding behavior. Theories must be evolutionarily sound. How Emotions Are Made lacks this adaptive perspective entirely. Barrett never discusses the adaptive value of emotions.
Darwin is mentioned only to highlight variability in evolution (mutations introducing novel traits) and to mischaracterize his Expression of Emotions in Man and Animals as essentialist and lacking in natural selection thinking. Barrett overlooks that natural selection, the other core tenet of evolution, favors adaptiveness. Mutations leading to Constructed Emotions would be evolutionarily outcompeted by Innate Emotions.
Natural selection drives certain gene variants to replace others. Traits vital for survival become evolutionarily stable. Variation exists around this stable mean, representing the most adaptive trait in the current environment. Darwin’s emotion book is not about essentialism but adaptationism. Emotions evolved for their immense survival value, benefiting those with these genes over those without. While not every modern human emotion has direct survival value, the core emotions identified by Jaak Panksepp certainly do.
Variation in emotional expression across species reflects adaptation to different environments, not essentialism. Learning also refines innate predispositions.
Barrett misses the adaptive significance of emotions and their evolutionary origins. If language is needed for emotions, did they emerge during the Cognitive Revolution (70,000 years ago), with Homo sapiens (200,000 years ago), Homo erectus (millions of years ago), or H. habilis?
What evolved first: sensation/action or the ability to name the sensation? Barrett requires both for emotions. I argue sensation/action came first because action linked to sensation has clear adaptive advantage, while naming it is less crucial for survival.
How Emotions Are Made lacks this evolutionary perspective. Barrett focuses on modern human experiences—meeting friends, gifts, music, arguments—examples irrelevant to emotion’s evolutionary origins in high-stakes survival situations.
To understand emotion’s evolution, we must consider the prehistoric Environment of Evolutionary Adaptedness (EEA). Emotions evolved to enhance survival in critical situations.
Life for hunter-gatherers and early Homo sapiens was harsh, with high child mortality and short lifespans. Under such conditions, we were not “architects of our own experience” but subject to environmental forces.
Emotions evolved to drive life-saving actions. Crucial emotions trigger physical responses:
- FEAR: Running or hiding from predators
- RAGE: Fighting when cornered
- CARE: Nurturing offspring
- LUST: Seeking mates
- GRIEF: Seeking companionship when alone
- SEEKING: Exploring for resources
- PLAY: Social bonding and learning
These core emotions (using Jaak Panksepp’s terminology) are evolutionarily sound. Innate responses in these contexts enhance survival and reproduction, making Innate Emotions an ESS, unlike CToE.
Emotions initiate actions vital for survival. This action-oriented view is key to understanding emotions. Modern human experiences like happiness meeting Uncle Kevin or nostalgia for Grandma’s baking are irrelevant to emotion’s evolutionary purpose.
Barrett writes: “An instance of emotion, constructed from a prediction, tailors your action to meet a particular goal in a particular situation, using past experience as a guide.” (p. 139) The flaw is assuming past experience is always available. In tiger attacks, this approach is maladaptive. Adaptive responses include innate predispositions refined by experience.
Barrett dismisses Panksepp’s work, stating: “some scientists still presume that all vertebrates share preserved, core emotion circuits to justify the claim that animals feel as humans do. One prominent neuroscientist, Jaak Panksepp, routinely invites his audiences to see evidence of such circuits in his photos of growling dogs and hissing cats, and in videos of baby birds “crying for their mothers”. It is doubtful, however, that these proposed emotion circuits exist in any animal brain. You do have survival circuits for behaviors like the famous four Fs (fighting, fleeing, feeding and mating); they’re controlled by body-budgeting regions in your interoceptive network, and they cause bodily changes that you experience as affect, but they are not dedicated to emotion. For emotion, you also need emotion concepts for categorization.” (p. 279)
This dismissal is puzzling. Barrett ignores Panksepp’s finding that emotional responses are triggered subcortically in specific locations. She acknowledges the four Fs but links them to “affect,” not “emotion,” suggesting a semantic debate rather than addressing evolved behavioral systems for critical situations.
Panksepp distinguishes three emotional processing levels: primary (7 core emotions, subcortical), secondary (learning, brain expansion), and tertiary (thoughts about emotions, cortex). Barrett seems to consider only tertiary level “emotions,” labeling the rest “affect.”
Defining “emotion” is crucial. Evolution provided core affective reactions with survival value, independent of language, shared across mammals. These primary reactions occur without words or concepts. I define these as emotions; Barrett does not.
Emotions are subjective feelings, bodily and mental sensations—joy, loss, terror. In modern life, subjective experience dominates our awareness. But feelings don’t explain emotion’s evolution.
Emotions didn’t evolve for feeling; they evolved to initiate life-saving action. “Emotion” is “energy in motion,” derived from a Latin verb “to move.” Emotions are innate responses to challenges. The four Fs are integral to emotion.
Therefore, we should find brain processing for core survival emotions. Innate emotions suggest dedicated brain regions. We expect core emotions to involve specific brain regions, not every emotion known to humans.
Panksepp identified seven core emotions: CARE, GRIEF, PLAY, LUST, SEEKING, FEAR, and RAGE. He triggered emotional responses by electrically stimulating subcortical brain regions in animals and humans, observing consistent emotional reactions and facial expressions linked to specific areas.
Panksepp found emotions triggered in subcortical areas and then spreading throughout the brain, contrasting the “classical” view Barrett attributes, which she misrepresents as emotions being localized and not spreading.
Panksepp triggered emotions only in subcortical areas, ancient brain regions shared by mammals and birds, not in the cortex. He also noted core emotions are most active in youth, diminishing as learned strategies become dominant.
How Emotions Are Made ignores Panksepp’s 30+ years of data, neither refuting nor explaining it away. Barrett claims no evidence for specific brain regions processing emotions, based largely on a meta-analysis.
Meta-Schmeta: A Critical Look at Meta-Analysis
Disclaimer: I’m an ethologist, not a statistician. My statistical understanding, while part of my PhD, is not my strength. My following critique may contain errors, and I welcome corrections from statistics-minded readers.
Meta-analysis combines data from multiple studies to achieve greater precision and is considered high-level scientific evidence. It’s meant to resolve controversies by summarizing a body of research.
Barrett and colleagues conducted a meta-analysis: “So, my lab set out to settle the question of whether brain blobs are really emotion fingerprints once and for all. We examined every published neuroimaging study on anger, disgust, happiness, fear and sadness, and combined those that were usable statistically in a meta-analysis. […] Overall, we found that no brain region contained the fingerprint for any single emotion. […] For me, these findings have been the final, definitive nail in the coffin for localizing emotions to individual parts of the brain.” (p. 21-22).
Does this meta-analysis definitively disprove brain regions for emotions?
I have significant doubts.
Meta-analysis requires data to be similar and measure the same thing in the same way. Heterogeneous data can obscure findings, risking false negatives. Combining heterogeneous data is a common meta-analysis mistake. One study estimates only 3.75% of meta-analyses are clinically useful, with 96.25% flawed, misleading, or useless.
Critical evaluation of meta-analyses is essential, even in peer-reviewed journals. Questioning Barrett’s meta-analysis seems warranted, given the low probability of its flawless execution.
Reviewing abstracts from the meta-analysis’s first 60 references revealed highly heterogeneous data, not measuring the same thing or collected uniformly.
Emotional reactions in these studies were triggered by:
- Film-induced sadness/amusement
- Neutral and negative scenes
- Angry and fearful faces/sadness
- Happy/fearful faces and voices
- Emotion words (passive viewing)
- Matching faces and words
- Beloved photos (love context)
- Bank robbery videos (victim context)
- Recalled emotional situations (sadness, happiness, anger, fear, disgust)
- Anger-inducing autobiographical narratives
- Angry prosody in meaningless speech
- Olfaction/tastes and core affect
- Faces paired with odors (neutral, pleasant, unpleasant)
- Chills-inducing music
- Speech preparation (social evaluation threat)
- Depressed vs. healthy viewing sad films
- Panic disorder vs. controls viewing anxiety images
- Borderline vs. controls viewing aversive/neutral images
Measurement techniques varied (fMRI vs. PET), as did the emotions studied, triggers, sensory systems, emotional processing levels (primary, secondary, tertiary), and whether studies assessed emotion experience, perception, memory, or categorization. Participant baseline emotional states also differed.
Furthermore, studies were conducted on humans aware they were in experiments. Authenticity of “emotions” triggered by, say, “listening to an autobiographic narrative meant to cause anger” in a lab is questionable. Would “real” anger be processed similarly? Is social evaluative threat (speech fear) genuine fear or embarrassment?
In essence: garbage in, garbage out. Meta-Schmeta.
Just because you can throw a bunch of numbers into the same mathematical pot, doesn’t mean you should.
Meta-analysis validity is population-specific. Barrett’s meta-analysis applies to people in contrived lab experiments with “emotions” triggered by stimuli while in apparatuses. Extrapolation to real-life emotions is unsupported. We lack data on intense negative emotions due to ethical constraints in such experiments.
Another concern is Barrett’s voxel-based brain data analysis. Dividing the brain into tiny 3D cubes (voxels) to find “brain blobs” can yield false negatives or positives based on voxel size.
Small voxels: If voxel size is too small, structural brain variations mean the same region activation might activate different voxels in different brains, leading to false negatives.
Scenario 1 – small voxels. Activation (the red/yellow smudge) occurs in the same region of the same brain blob, but since that particular blob differs in size in the two brains, different voxels would be scored in the two brains (6G and 7H, respectively). In other words: a false negative. The risk of a false negative is increased with reduced voxel size.
Barrett herself notes brain microcircuitry variability: “No two brains are exactly alike. They generally have the same parts, roughly in the same place, connected together in pretty much the same way, but at a fine-grained level, in their microcircuitry, they have vast differences” (p. 230). This statement undermines the voxel approach.
Large voxels: Conversely, large voxels risk false positives. Activation in different brain regions might activate the same large voxel.
Scenario 2 – big voxels. Activation occurs in different brain blobs, but the same voxel is scored (4D). In other words: a false positive. The risk of a false positive is increased with increased voxel size.
Voxel size choice in Barrett’s study might be biased to prove no brain blobs exist, favoring false negatives to “nail the coffin” shut.
Even with a balanced voxel size (if achievable), it might only be valid for certain emotions and brain regions in some brains, requiring recalibration for others. Without aligning voxels with neurological structures like amygdalae or hippocampi, finding balance is questionable. We risk false negatives or positives, with biases influencing our choice.
Meta-analyses are controversial. Minor rule violations can mislead. Subjectivity in design and execution risks personal biases influencing results.
John Ioannides, in a critique of meta-analysis trends, suggests: “Ideally, people who have no stake in the results should perform systematic reviews and meta-analyses, excluding not only those with financial conflicts of interest but even those who are content experts in the field.”
Omitting Panksepp’s data while including heterogeneous studies in Barrett’s meta-analysis suggests cherry-picking. Findings may reflect biased data selection, heterogeneity, and false negative risk from voxel use.
The meta-analysis’s assumption that each emotion is processed in a single brain area (locationist perspective) is a straw man. Failure to find such localization doesn’t automatically support constructed emotions. Emotion processing might involve networks across brain regions, as Panksepp suggests. Brain regions function within networks.
Andrea Scarantino critiques Barrett’s meta-analysis:
“…are open to the possibility that there may be “widely distributed” networks for discrete emotions, but argue that their existence “would be consistent with a psychological constructionist … view” (sect. 6.1, para. 4). I strongly disagree. Constructivism posits that discrete emotions are not causal entities in their own right, but rather, effects of more basic psychological processes. The existence of networks for discrete emotions would strike at the heart of this idea, vindicating instead the natural kind proposal that discrete emotions have ontological status as causal entities and are driven by distinctive, though distributed, neural mechanisms. [The authors have] built their argument such that if criteria for the locationist argument are not met, it is assumed to be support for the psychological constructionist perspective. This is misleading, and fails to recognize other possible explanations.”
fMRI’s capture only initial emotional responses, missing temporal development. Panksepp favored PET studies partly for this reason.
In summary, Barrett’s meta-analysis finding variability in brain emotion processing is unsurprising due to heterogeneous data and potential cherry-picking. Voxel use may obscure findings and increase false negative risks. Real-life emotional reactions are poorly represented by contrived lab setups.
Distinguishing false negative from true negative results is impossible. Barrett’s meta-analysis is not a “nail in the coffin.” Classifying it by Ioannides’ criteria, it’s both flawed beyond repair and misleading.
Even without meta-analysis concerns, brain involvement in emotions is expected. Running from tigers requires brain orchestration without prior learning—innate emotional reactions orchestrated by brain regions.
Barrett notes: “I sometimes hear comments from emotion researchers who subscribe to the classic view: “what about these other 50 studies with these thousands of subjects, that show incontrovertible evidence for emotion fingerprints?” Yes, there are many such confirmatory studies, but a theory of emotion must explain all the evidence, not just the portion that supports the theory”. (p. 22)
While a valid point, current emotion studies don’t suit meta-analysis due to heterogeneity. Homogeneous meta-analyses risk bias, while heterogeneous ones risk false negatives.
Meta-analyses for emotion studies are a Catch-22.
- Homogeneous samples risk selection bias.
- Heterogeneous samples risk false negatives.
A meta-analysis needle cannot be threaded. Instead of demanding meta-analysis alignment, consider: if emotions are constructed, why do 50 studies show consistent brain region activation across thousands of brains? Shouldn’t construction imply complete variability?
Disturbingly, neurotransmitters are ignored. Barrett dismisses facial expression and brain region “fingerprints” but omits discussion of neurotransmitters (oxytocin, dopamine, endorphins, cannabinoids) in emotions and their synaptic distribution. How does CToE reconcile with neurotransmitter findings? Probably poorly.
Let’s move from brain regions to facial expressions—innate or learned, as CToE suggests?
Facial Expressions: Innate or Learned?
Barrett uses snapshots of partial facial expressions to argue emotion decoding is unreliable without context and shared learned expectations.
Rafael Nadal winning the Olympic Gold Medal. One may mistake his facial expression for terror if one doesn’t have the whole context.
I disagree. We evolved to interpret facial expressions in real-time, in relevant contexts, not from static partial images.
Evolutionary perspective is key. When are innate facial expressions adaptive? In social contexts to signal intent (benign or malign) or to adjust to environmental challenges (disgust face closing nasal passages, squinting protecting eyes).
Human smiles signal benign intent, not necessarily “happiness.” Recognizing benign or malign intent from a distance is evolutionarily adaptive.
Adaptive perspective is absent in Barrett’s book. She dismisses facial expression research, claiming smiles are learned from TV, rejecting innate facial expressions.
Barrett attributes to the “classical view” that “emotions are supposed to have universal fingerprints that everyone around the world can recognize from birth“. (p. 43). This is a straw man. Who argues this simplistic view? There are >92 emotion definitions in science. Which is the “classic” one?
Evolutionarily, not every emotion needs a specific facial expression, nor must recognition be innate from birth. Neither statement is evolutionarily necessary.
Paul Ekman defends his facial expression research here, and Nature summarizes the controversy here.
A particularly jarring claim: “The historical record implies that ancient Romans did not smile spontaneously when they were happy. The word “smile” doesn’t even exist in Latin. Smiling was invented in the Middle Ages and broad toothy-mouthed smiles […] became popular only in the eighteenth century as dentistry became more accessible and affordable. The classics scholar Mary Beard summarizes the nuances of the point: “This is not to say that Romans never curled up the edges of their mouths in a formation that would look to us much like a smile; of course they did. But such curling did not mean very much in the range of significant social and cultural gestures in Rome.” (p. 51)
The claim that Romans didn’t smile and Latin lacks “smile” is dubious. Absence of evidence isn’t evidence of absence. Lack of smiling in Roman art may reflect cultural preferences for power projection over friendliness in portraiture, not absence of smiling.
The Roman emperor Caracalla. Friendly or powerful?
Subridere in Latin means “smile.”
Silent bared-teeth displays (benign intent) exist in gorillas, chimpanzees, orangutans, macaques—our closest relatives. Human smiling likely evolved from these primate displays. The claim that smiling arose in the Middle Ages is preposterous and contradicts comparative evidence.
Silent bare-teeth displays in primates tend to signal benign intent (in the contexts of greeting, submission, or sexual behaviour, for instance). It’s been hypothesized that the silent bare-teeth display is the precursor of the human smile, and that the relaxed-open-mouth-display (not shown here, but also seen in many primate species in playful situations) is the precursor of human laugher.
Barrett errs in dismissing all facial expressions as learned. Innate facial expression recognition is evolutionarily vital. Facial expressions are often more honest than verbal communication. Verbal emotion reports are censored and incomplete.
If facial expressions were solely learned, cultural variability would be expected, not the ubiquity of smiling in greetings or frowning in annoyance across cultures. Facial expression variability should mirror language variability if learned.
The Toxic Climate of Discussion
Why three years to read How Emotions Are Made? It was an aversive experience:
- Challenged core beliefs: I believe in innate emotions; the book argued against it.
- Condescending tone: Patronizing tone triggered indignation.
- Disagreement with studies: Disagreements made reading difficult. (Chapter 9 was an exception!)
Instead of conversion, the book reinforced my initial views. Sheer willpower and chocolate were needed to finish it. The Semmelweiss and backfire effects, cognitive biases, amplified my negative reaction.
However, the Constructed Theory of Emotions is genuinely flawed. Biases magnified my reaction, but the theory itself is weak.
Lisa Feldman Barrett concludes: “based on overwhelming evidence, the classical view has lost.” (p. 152). I remain unconvinced. My paradigm is unshaken. She doesn’t invite discussion but accuses “classical view” adherents of the mental inference fallacy and being unscientific:
“When mountains of contrary data don’t force people to give up their ideas, then they are no longer following the scientific method”. (p. 173). This is triggering. Questioning her theory is part of the scientific method.
While mental inference fallacy bias is acknowledged, it’s not the sole reason for disputing CToE. The theory lacks solid scientific basis. Discussion, not polarization, is needed. Emotion theory should integrate findings and be evolutionarily sound, acknowledging Panksepp’s work. Meta-analyses are problematic for this discussion due to false negative risks and data bias.
CToE addresses thinking about and classifying emotions, not triggers, responses, or adaptive outcomes. Frans de Waal distinguishes between emotions (objective, behavioral, affective reactions) and feelings (subjective, conscious experiences). CToE might be better termed the “Constructed Theory of Feelings.”
Why This Debate Matters
Why is this book so triggering and CToE’s popularity in animal training concerning?
It elevates humans and diminishes animals.
Outside academia, I help pet owners and animal professionals build harmonious relationships by acknowledging animal emotions.
Anxious horses refuse trailers. Panicked dogs shred furniture when alone. Terrified cats lash out at vets. Addressing emotions helps modify behaviors. Ignoring animal emotions limits our ability to help them.
There’s a darker side. Human-animal separation sanctions cruelty. Treating “them” (outsiders) poorly is a human tendency.
Jeremy Bentham (1789) on animal pain: “The question is not, can they reason? Nor, can they talk? But, can they suffer?”
Yes, animals suffer. Recent decades show animal consciousness, Theory of Mind, planning, cultural learning. We can’t know exactly what they feel, but assuming they feel nothing is wrong. They have emotions.
Acknowledging animal emotions and feelings reduces suffering.
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