How Starling Behavior is the Key to Understanding Empathy
What looks like magic isn't thought transference —?it's complexity theory. Let's dive deep into the evidence, shall we? Photo: Adobe Stock

How Starling Behavior is the Key to Understanding Empathy

Empathy isn’t simply an innate ability. It’s a system. A complex dynamic adaptive system, to be precise. And these types of systems play by a different set of rules. We can’t design them from the top down. We can’t map them out like an assembly line where we can confidently predict that X inputs through Y process will predictably yield Z results.

Instead, we manage complex systems from the bottom up. We focus on optimizing local interactions, not pre-planning a global overview. There is no single entity directing the change. Results emerge based on how elements within the system interact with each other and respond to environmental conditions. By focusing on the small, we can influence the big.

We can see this principle in action frequently in nature, such as with the dazzling displays created by large groups of starlings in the sky. Known as murmurations, these spectacles are a sight to behold. Flocks that comprise of sometimes million of individual starlings dance in mesmerizing swirls that are so large they can block out the sun[1].

Starlings Aren’t Psychic (And Neither Are We)

In the 1930’s, ornithologists believed that this complex coordination must come from an invisible psychic ability they called “thought transference”. It kind of makes sense that something so magical must come from something so mystical. But over time, we got new data that changed our understanding.

The breakthrough didn’t come from birdwatchers, though. In 1987, computer scientist Craig Reynolds[2] was exploring the nature of complex systems and created a program that rendered starling murmurations to great effect. No thought transference required. His simulation was successful when individual “boids” (his affectionate term for the simulated birds[3]) adhered to the following rules:

1. Avoid collision with nearby flockmates

2. Attempt to match velocity with nearby flockmates

3. Attempt to stay close to nearby flockmates

“Working independently,” Reynolds explained, “the birds try both to stick together and avoid collisions with one another and with other objects in their environment.” Instead of a psychic connection, each bird pays attention to their surroundings and adapts their behavior accordingly. Stunning system. Simple rules.

Reynold’s “boid” program demonstrated a key insight for these types of complex systems — emergence. What looks like magic is actually generated from independent interactions at the local level. As individuals adapt to changing conditions, the system as a whole appears to act in surprising and unexpected ways. By understanding the underlying system structure, we can better understand and influence its behavior.

As the influential systems theorist Donella Meadows wrote, “Once we begin to see the relationship between structure and behavior, we can begin to understand how systems work, what makes them produce poor results, and how to shift them into better behavior patterns.”[4] It’s important to note that structure isn’t predefined or predictable. With murmurations, we can’t map out the flight path of any individual bird. Interactions between individuals give better insights into how a system behaves than trying to control or predict the behavior of any given individual.

To understand a system, you need to take a holistic approach and look at a variety of parameters, which Meadows describes as “leverage points.” Some examples include:

  • Examining nodes and their intersections
  • Considering feedback loops and delays, particularly the ones that lead to exponential outcomes
  • Mapping out how information flows throughout the system, including who has access
  • Looking at rules, especially between incentives, punishments, and constraints
  • Exploring how elements in the system can self-organize by adding, changing, or evolving the system structure
  • Thinking about the system’s goals, purpose, or function
  • Modeling the system and seeing it as a holistic paradigm instead of a mere collection of its component parts

Starling murmurations are relatively simple in their complexity compared to human systems, but the underlying principles remain the same. Instead of explaining emergent behavior as a singular ability, we can better understand it by embracing complexity.

In many ways, our ideas of empathy and emotions are in a similar state of transition to how we refined our ideas about starling murmurations. Thanks to newer research from the field of neuroscience, we’re starting to see that, like starlings, humans don’t use thought transference to coordinate our behavior either. This means that if we want to understand empathy, we have to cast off what feels familiar and embrace new evidence. Empathy is less about an innate ability to read the minds of others and more about exploring the complex nature of social systems.

But to understand this, we’ll need to look at a significant schism that has emerged in the academic world. It may seem like we’re splitting hairs here, but stay with me. The more I’ve researched, the more I believe that shifting paradigms is critical if we want to use empathy effectively to collaborate and solve the complex challenges we face today.

Theory Category 1: Emotions as Innate Inference (Like Thought Transference)

The core of the debate is between universalism and constructivism. Are empathy and emotions innate and genetically determined (like thought transference in starlings)? Or are they constructed as part of a complex dynamic adaptive system (like Reynold’s “boids”)?

First, let’s look at two theories that support the first question, which have such a strong hold in the cultural zeitgeist that they are often considered irrefutable fact to this day: basic emotion theory and mindblindness. In both theories, emotional expression, and interpretation are considered to be innate human traits that are both highly observable and consistent across populations. Challenges inferring emotions are explained as genetic deficiencies. These theories fall into a broader paradigm of emotional theory known as universalism.

Evolution and Emotion Expression

Many universalist theories draw inspiration from Charles Darwin. Several years after writing On the Origin of Species, his groundbreaking work that laid out the theory of evolution, Darwin turned his attention to emotions, publishing The Expression of Emotion in Man and Animals in 1872. In it, Darwin synthesizes a variety of contemporary theories and lays out “Three General Principles of Expression” which “appear to me to account for most of the expressions and gestures involuntarily used by man and the lower animals, under the influence of various emotions and sensations.”

  • Habits - expressions that are associated with states of mind and can be learned and somewhat controlled through conscious thought
  • Inheritance - traits that are inherited by parents
  • Reflex - actions that bypass conscious thinking

Throughout the book, Darwin examines a variety of emotional categories:

  • Suffering and Weeping
  • Low Spirits, Anxiety, Grief, Dejection, Despair
  • Joy, High Spirits, Love, Tender Feelings, Devotion
  • Reflection, Meditation, Ill-Temper, Sulkiness, Determination
  • Hatred, Rage, Anger
  • Distain, Contempt, Disgust, Pride, Guilt, Helplessness, Patience, Affirmation and Negation
  • Surprise, Astonishment, Fear, Horror
  • Self-Attention, Shame, Shyness, Modesty

For each emotional category, Darwin contemplates in great detail whether expressions are derived from habits, inheritance, or reflex. Some movements, he theorized were “innate or universal.” For example, sweating and screaming in response to pain, drawing down the corners of the mouth as a sign of sadness, laughter to indicate joy, spitting as a sign of disgust, and opening the eyes and mouth widely to express surprise. Darwin’s theory that some emotions appear to be genetic and universally expressed, often across both humans and other social species[5], is at the core of universalist interpretations.

Basic Emotion Theory & Microexpressions

In the 1960’s psychologist Paul Ekman set out to collect data to assess Darwin’s theories by traveling to remote regions of the earth[6]. His aim was to explore whether culturally isolated groups would be able to identify six emotions that Darwin suggested could be universal: happy, fear, disgust-contempt, anger, surprise, and sadness. The experimental design used cropped black-and-white photographs of American actors’ faces, each of which presented an exaggerated, staged expression. All of the actors were caucasian, and Ekman personally directed the poses and curated the images that he deemed to be the most accurate expression of each given emotion.

There was relative consistency across the groups, leading Ekman to conclude that his findings “support Darwin’s suggestion that facial expressions of human emotion are similar among humans, regardless of culture because of their evolutionary origin.”[7] Over the years, Ekman continued to conduct research and came to adopt what became known as the basic emotion theory[8].

By the 1970’s, Ekman had enthusiastically focused his research efforts on creating a detailed map of what he called “micro expressions.” Ekman describes these tiny movements of facial muscles that occur in a fraction of a second were as “involuntary leakage that expose a person’s true emotions.”[9]

Using his theories of microexpressions and basic emotions, Ekman developed an incredibly detailed database called the Facial Action Coding System (FACS). His goal was to categorize a comprehensive set of nuanced configurations made by the forty-two facial muscles, into descriptive Action Units (AU) (ex: jaw drop, mouth stretch, etc.) that can be coded by frequency and intensity. This original database did not include emotional categories. After coding, AUs could be analyzed to interpret emotion.

The training for FACS was expensive and time consuming, so a new tool was developed called the Emotion Facial Action Coding System (EMFACS). Using this system, coders only record events where an AU is associated with a basic emotion. Soon, these two models were combined so that they could be used for computer programs, which is known as FACSAID (Facial Action Coding System Affect Interpretation Database). [10]

Once Ekman adopted a universalist view, he became a zealous and almost unwavering proponent, frequently invoking Darwin to uphold this theory[11] and sell his ideas. Once the FACS database was complete, Ekman set out to train the world on how to read faces using the commercial products[12] he created from it. His company’s clients include Disney, Apple, and the United States Central Intelligence Agency, just to name a few.

The commercial success of Ekman’s work has had a far-reaching cultural impact. In 2016, Ekman surveyed 248 scientists and reported that “The existence of ‘compelling evidence for universals in any aspect of emotion’ was endorsed by 88% of the respondents. The evidence supporting universal signals (face or voice) was endorsed by 80%.”[13] The basic emotion theory inspired the television crime drama series Lie To Me and the movie Inside Out, both of which Ekman served as a scientific advisor. Ekman was named by Time as one of the 100 most influential people in the world and worked with notable leaders, such as the Dalai Lama.[14]

In the software world, Ekman’s work is possibly more significant. Since the 1980s, the FACS database and its derivative databases have been used to train machine learning models on the premise that unseen inner beliefs could be made visible in an objective, rational, measurable, and software-friendly way. The FACS database has inspired or seeded a variety of other datasets that train AI models for facial and emotional recognition.[15] These databases are widely used by social scientists to provide evidence[16], clinicians to diagnose patients[17], marketers to research customer behavior[18], law enforcement to predict and prosecute criminal behavior[19], and technologists to create facial recognition software[20].

Was Darwin a Universalist?

It’s worth noting that while Ekman has remained staunchly steadfast in his theories of basic emotions and microexpressions, Darwin did not display the same enthusiastic confidence. While Darwin makes speculations, he is clear that his observations are hypotheses that further data could very well contradict. His writing makes a robust use of hedging language, such as “seems,” “appears,” “perhaps, ”and “may be.”

He also explicitly states that we should be wary of using facial muscles to definitively infer states of mind. When exploring fear, for example, Darwin observes that the platysma, a muscle that roughly connects the collarbone and cheekbone, tends to draw corners of the mouth down. While this is undoubtedly useful information, Darwin explicitly cautions not to use this determinately to infer someone is afraid. “I think there can be little doubt,” Darwin writes, “that the contraction of the platysma does add greatly to the expression of fear. Nevertheless this muscle ought hardly to be called that of fright, for its contraction is certainly not a necessary concomitant of this state of mind.”

Another example is expressing agreement, where he writes, “The evidence with respect to the inheritance of nodding and shaking the head, as signs of affirmation and negation, is doubtful; for they are not universal, yet seem too general to have been independently acquired by all the individuals of so many races.”

Upon reading the book that inspired Ekman so deeply, I’m not convinced that Darwin was convinced of, or even an advocate for, universalism. Instead, I hear scientific skepticism, pondering, and hypothesizing. Darwin remained open to being proved wrong in the face of new evidence, reminding his readers that “it is always advisable to perceive clearly our ignorance.”

Mindblindness & The Empathizing-Systemizing Theory

While Ekman’s work has largely focused on the universal expression of emotions, other researchers have focused on the universal interpretation of emotions. One of the most prominent universalist researchers in this area is Cambridge psychologist Simon Baron-Cohen, whose research agenda has focused on finding a genetic link between emotional inference and autism.

Baron-Cohen is credited as the first to theorize[21] that humans are born with a universal ability to infer meaning from other people’s behavior from specific equipment in the brain called the Theory of Mind Module (ToMM). Autism, according to Baron-Cohen’s theory, results from damage to this region that impairs intuitive inference, which he calls “mindblindness.” Under these circumstances, Baron-Cohen concludes that “other people’s behavior is beyond comprehension and empathy is impossible.”[22]

Baron-Cohen built his theory of mindblindness from the work of Paul Ekman, developing a test he named the “Reading in the Mind’s Eye” task. This assessment “involves looking at photographs of the eye region of the faces, and making a forced choice between which of two words best describes what the person (in the photograph) might be thinking or feeling.[23]” Over the next few years, in collaboration with other researchers such as Sally Wheelwright, Baron-Cohen focused on developing diagnostic tools for autistic traits, such as the widely used Autism-Spectrum Quotient[24].

Another significant contribution to the link between empathy and inference is Baron-Cohen’s Empathy-Systemizing Theory (E-S Theory)[25], which is presented as a spectrum of “brain types.” On one end are high-E individuals, who possess the “ability to recognize another person’s mental state and respond with an appropriate emotion.” On the other end are high-S individuals, who prefer to “identify rules that govern a system.” Cohen’s theory posits that situational conditions, such as stress, can impact where an individual falls on this spectrum at any given moment, but in practice E-S quotients are typically applied more broadly to describe traits more than states. Baron-Cohen also uses interchangeable terms based on gender, using [26]“Female Brain” to refer to the empathy end of the spectrum and “Male Brain” for systemizing.

The cultural impacts of Baron-Cohen’s work are just as significant as Ekman’s. His theories and diagnostic tools have been popularly promoted and commented on. For example, in his book Blank Slate,[27] which was a New York Times best seller, Stephen Pinker used Baron-Cohen’s theories to contemplate how to categorize individuals who “cannot read people’s minds.” Pinker comes to the conclusion that “Together with robots and chimpanzees, people with autism remind us that cultural learning is only possible because neurologically normal people have the innate equipment to accomplish it.”

In the software industry, Baron-Cohen’s research led to social stereotypes, particularly in Silicon Valley, where challenges with mindreading became known as “The Geek Syndrome[28].” Leaders of autism clinics in San Francisco, such as clinical psychologist Bryna Siegel,[29] lamented seeing “deep geeks of all sorts” and expressed serious concern for their ability to function in human society. “They don’t make great eye contact, all their clothing is from the Intel shop, they don’t have a lot of social understanding. I do think that when these geeks marry each other, that’s bad news for the offspring.”

Like Ekman, Baron-Cohen has built extensive databases of photographs of human expressions that are each coded to a specific emotion. These large datasets are commonly used for affect recognition machine learning models and Baron-Cohen has personally collaborated with software founders to develop products that claim to have launched the field of “emotionalAI[30].”

Theory Category 2: Emotions as Constructs (Like Complexity Theory)

With the rise of neuroscience imaging, a new paradigm called constructivism is presenting new evidence that refutes the universalist view. Like starling behavior, constructivists theorize that empathy can be better understood as an emergent property from a complex system rather than a pseudo-psychic innate ability.

This shift is critical for how we understand empathy. Universalists embrace a more deterministic model of empathy and tend to focus on locating empathy in specific genes and brain regions[31]. While gene expression and brain modules are part of the constructivist consideration set,[32] their analysis includes a wider variety of factors, such as the brain’s dynamic self-structuring abilities, environment, context, motivation, culture, and associative learning.

The idea of constructivism is not new, however. Anthropologists in the 1930’s, such as Margaret Mead[33], had researched culturally isolated groups, some of which were in similar geographic regions to the ones Ekman would study three decades later. However, Mead and her colleagues came to the opposite conclusion from Ekman, theorizing that emotions were predominantly social constructions. These theories downplayed the importance of the biological mechanisms that gave rise to emotional expression, and a vibrant academic rivalry between universalist vs. constructivist theories has endured since.

Modern constructivism differs slightly from these earlier constructivist theories because it integrates empirical research from the field of neuroscience. It doesn’t dispute that biological factors are necessary for emotions and empathy, but it rejects the idea that innate and inheritable traits are a sufficient explanation. Modern constructivists emphasize that while facial expressions can be a useful clue for inferring emotions, that inference cannot be interpreted as true or definite because there are far too many other factors at play.

Charles Darwin is also foundational in constructivist theories, particularly his ideas around population thinking[34], which emphasizes variability, not consistency, as the norm when looking at evolutionary patterns across a group of individuals. Under population thinking, you cannot use a pattern that applies to a group to definitively deduce attributes for an individual within that group.

There is hardly any debate that across populations, broad patterns are highly correlated, such as frowning and sadness, scowling and anger, or smiling and happiness.[35] The difference is whether that pattern can be used to confidently and accurately deduce the emotions of a single individual. Universalists say yes. Constructivists say no. This means that in a constructivist interpretation, empathy levels are not described in terms of deficits or disabilities, but differences.

When it comes to software, constructivism throws a massive wrench in the way emotional and facial recognition is currently measured. Constructivist authors consistently point out flaws in universalist methodologies, such as emphasizing the importance of statistical variability in a model as a way to guard against confirmation bias[36]. With constructivism, a facial configuration represents a way, not the way, to intuit another person’s emotions. For example, a scowl can indicate anger, but it could also indicate that someone is focusing intensely. Someone who is angry might scowl, but they might configure their face differently than that particular emotional stereotype.

The Functional Architecture of Human Empathy

In a constructivist theory, there is also significant skepticism that empathy can be located in a specific gene or brain region. Instead, research focuses on exploring how a variety of interacting functions enable empathy to emerge in the brains and bodies of humans. One of the leading researchers in this field is Jean Decety[37] who has made mapping the “functional architecture of human empathy”[38] a significant part of his research agenda over the past two decades. To Decety, one of the core problems with empathy research is treating it as “one monolithic concept.”

According to Decety, “the construct of empathy needs to be decomposed” and he has strongly encouraged empathy researchers in “breaking down empathy and related phenomena into component processes.”[39] He makes the case that researchers should explore interactions of a variety of functional processes in order to understand what is “eliciting a full-blown empathetic experience.”

While we can decompose these components into smaller and smaller parts, we need to also not lose sight of the bigger picture. It’s not just about how empathy emerges, but why. Decety concludes is that “The essence of empathy is the communication of an emotional state from one person to another” and identifies at least four components that work together in our bodies to allow this to happen. [40]

  • Affect: “Reflects the ability to share the emotional state of others in terms of valence and intensity. This component of empathy (also called emotional contagion) plays a fundamental role in non-verbal communication and in emotional synchronization between individuals.”
  • Motivation: “Sympathy, also called empathic concern or compassion, refers to another-motivated emotion to care for the well-being of others. It is characterized by feelings of warmth, concern, and care for the other, as well as a strong motivation to improve the other’s wellbeing.”
  • Cognition: “Accounts for the capacity to intentionally adopt another person’s perspective to understand what she is thinking or feeling. This capacity largely overlaps with the concept of theory of mind.”
  • Regulation: “The ability to evaluate and modify (attenuate, accentuate or maintain) one’s own emotional response to achieve a goal.”

The language Decety uses to describe empathy may sound familiar to people who work in software. That’s because the principle of decomposition is essential in software development[41], too. When problems or systems become increasingly complex, making aspects of the system more modular can make them easier to comprehend and work with.

For example, when a function’s complexity grows due to an increasing number of variables and parameters, breaking it down into interrelated constituents can make the function more maintainable. The constituents have fewer variables, and the original function can still be reconstructed as needed.

However, there is always a tension between how much a system should be decomposed. Too many components can become just as difficult to manage as too few. In the empathy literature, this is a hot debate. Some authors sardonically chide the idea of nuanced definitions while others find significant value[42] in the practice of empathy decomposition and lean on incredibly precise terminology to explore its properties.

Decety’s architecture, along with the research that dives deeper into each of his dimensions, forms the theoretical foundation of my book. Details are synthesized using models and plain language to help you understand the current empathy research landscape without getting bogged down in unnecessary jargon. This is a delicate balance, like any decomposition practice, but the goal is to help you step outside of your interpersonal experiences and look at empathy more holistically. Systems thinking is a useful way to strengthen our empathy skills[43], too.

Capacity and Skill

In a constructivist point of view, empathy is multidimensional[44]. It’s not just about what we’re equipped with on the inside. It’s also about what’s happening to us in any given circumstance. Helen Riess focuses on empathy in medical settings, such as how empathy levels impact patient outcomes or provider burnout. What Riess has discovered through her work is that in addition to our neurobiological wiring, empathy is also about capacity and skill-building. “In the past,” Riess writes, “empathy was considered an inborn trait that could not be taught, but research has shown that this vital human competency is mutable and can be taught to healthcare providers.”[45]

In addition to individual competency, Riess also emphasizes the importance of for institutional support[46], which shows up as valuing safety, access to accurate and caring information, human connection, and emphasis on mental health. Empathy in resilient healthcare organizations isn’t just about caring for others. Enabling individuals to care for their own health and well-being is an important aspect of empathy that should not be overlooked.[47]

Emotions as Instances

Some of the most intense debates between universalist and constructivist theories have to do with emotions. These are the ones where I get out my popcorn when I read the academic articles.

Concepts are a form of abstraction that helps us communicate[48]. Constructivists argue that emotions are a specific type of concept that humans evolved to help us quickly and efficiently synthesize information, make sense of our experiences, and adapt our behavior in a changing environment. This means that every emotional experience is its own unique instance.

Here’s a basic example of a concept. Let’s say someone asks what you had for lunch, it’s easier to describe your meal as a “salad” than it is to say, “lettuce leaves, tomatoes, cucumbers, and carrots that were chopped and placed into a bowl.” But a salad could also mean “baby spinach, goat cheese, beets, and walnuts served on a plate” or “shredded chicken combined with mayonnaise and diced celery served on a slice of toast,” or “chopped oranges, pineapple, apples, blueberries, and strawberries served in a carved out watermelon.” The amount of detail we need to use to communicate a concept will vary based on the situation.

The most prominent constructivist in the field of emotions is Lisa Feldman Barrett, who has developed the Theory of Constructed Emotions[49]. Her neuroscience research focus began in the 1980’s when she conducted experiments to replicate Ekman’s well-known universalist theories. Time and time again, her experiments failed to replicate. Instead of quitting, she got curious, developing different experimental designs to help her discover what was going on. “These new experiments revealed something that had not been documented before: everyone we tested used the same emotion words like ‘angry,’ ‘sad,’ or ‘afraid’ to communicate their feelings but not necessarily to mean the same thing… we discovered that people vary tremendously in how they differentiate their emotional experiences.”

A significant insight from Barrett’s research is how the words we use to describe an emotion represent a collection of more discrete internal and external experiences. Similar to salads, the ingredients of an emotional experience vary from person to person. One person may choose the word “anxiety” to represent the following attributes:

  • Physiological sensations: racing heart, dry lips, and twitchy muscles
  • Behavioral instincts: the impulse to run, talk fast, and worry
  • Situational context: taking a test, speaking in front of an audience, or asking for a raise

Another person might have different attributes that they use to label anxiety. Maybe their physiological tell isn’t dry lips, but sweaty palms. Or perhaps being alone in a quiet room feels more like anxiety instead of speaking in front of a crowd.

Emotional concepts can change from instance to instance, too. A person may get test anxiety on one exam and not another. We also adapt our concepts over time as we learn new things and gain new experiences. We can also develop a stronger emotional vocabulary to describe how we’re feeling from one instance to another.

From a constructivist perspective, emotions are a bottom-up process. Instead of categorizing emotions beforehand and trying to put an experience into a label, concepts are experienced first, and then a label is used to communicate the concept. Barrett coined the term emotional granularity to describe the ability to sense subtle shifts in our experiences and then choose words that precisely describe them. Low granularity uses only a few general emotional concepts to describe internal experiences: “upset,” “bad,” “fine,” “happy,” etc. High granularity uses words that convey a greater sense of accuracy, such as “frustrated,” “annoyed,” “satisfied,” or “elated.” The more discrete the emotional concept, the more granular it is.

Constructivist theories of emotions better align with how we work with complex software systems, too. For example, in object-oriented programming, classes are used to encapsulate a set of attributes. When a class is instantiated, a distinct object is created. Classes and emotional concepts are like templates or blueprints. An entire neighborhood of houses can be built using a single blueprint. However, each house built from the blueprint is a distinct entity and may have slight variations compared to its neighbors.

We can think of emotional granularity similarly to how we would use the single-responsibility principle. Classes generally work best when they are small, specific, and have a singular purpose. The opposite of single responsibility is often called a "god class," which is huge and packs many different responsibilities in one place. Using these two concepts, we might see that “upset” is an example of a "god class" emotional concept, whereas “grief” more closely follows the single responsibility principle.

The Double Empathy Problem

In a universalist interpretation, social differences in communicating emotions are pathologized. The burden of changing communication styles is placed almost solely on the individual with the perceived deficit, such as an autistic individual by Baron-Cohen’s definition. This effect has been catastrophic to the autism community. Individuals must engage in energy-draining performative behavior that adheres to an empathy stereotype, such as maintaining eye contact, often at the expense of their mental health[50].

But recent research that incorporates the lived experiences of autistic individuals has found that a universalist understanding isn’t congruent. Using these new findings, scientists like Sue Fletcher-Watson are coming to a different understanding of the problem. “Processes we have previously identified as ‘deficits’ in autism,” Watson writes, “are in fact better understood as interactive and communication challenges that operate in both directions across the autistic/non-autistic divide.”[51]

Damian Milton describes this imbalanced social dynamic as the “double empathy problem.”[52] When there is a problem with empathy or miscommunication, the double empathy problem focuses on the interaction, not the individual. It recognizes that both people are struggling to understand each other. It is a systems approach instead of pinning the problem on a single individual.

The shift in autism research towards constructivism is yielding a more complete picture of how empathy is an individual experience that is dynamic and changes based on a variety of factors. For example, when empathy is decomposed from a monolithic concept, some components of empathy are present at higher levels in people with autism when compared to their neurotypical peers[53]. We can also discern how different conditions can contribute to an individual’s experience. For example, alexithymia impacts an individual’s ability to sense affect and conceptualize emotions. It’s estimated that alexithymia occurs in approximately 10% of the general population and 50% of the autistic population[54]. This means that we cannot assume that every autistic individual has alexithymia, nor that every individual with alexithymia is also autistic. Variability is the norm. Population thinking applies. Individuals should be treated as individuals and not stereotypes.

In order for empathy and communication to succeed, non-autistic individuals (or any other majority group for that matter) need to spend just as much effort in understanding the people around them and adapting their communication to meet people where they are. Dr. Adam Zeman, Professor of Cognitive and Behavioural Neurology at the University of Exeter Medical School sums up the mindset to help facilitate double empathy nicely [55] when he said, “We all, of course, take our own experience to be the norm,” Zeman says. However, there are “major invisible differences between people’s inner lives. A keener appreciation of those differences helps us to appreciate the richness of human diversity and increases our sensitivity towards one another.”

Complexity and Constructivism Is a Better Explanation for the Magic of Empathy

When I started this book project, like most people, I thought the basic theory of emotion was established fact. I had no reason to question it. But when I started trying to model out how to make empathy concrete and map it out schematically so it could be used on a software project, everything kept breaking down. I couldn’t reconcile the recent research I was reading about empathy being a skill that you can learn with the universalist theories that empathy is a capacity that is more or less determined at birth. It just didn’t make sense.

It’s taken me about two years to wrap my brain around the neuroscience of constructivism, and from my perspective, it’s a much more elegant explanation to how humans empathize. When I started to embrace the emerging research, it fit perfectly into the principles of complexity theory that we already use to manage software projects. Everything snapped into place and now I’m much closer to being able to share my findings. But here’s a sneak peek.

Similar to how starlings use three basic rules to fly together in concert, I think humans do, too. Here’s what I think they are:

  1. Collect - Anchor yourself in compassion, mindfulness, and self-awareness while ensuring you have the energy and emotional regulation required to engage.
  2. Connect - Collect quality data, incorporate it into your mental models, and attune to another perspective using both affective and cognitive qualities of empathy.
  3. Communicate - Optimize your communication based on the amount of entropy you can observe in an exchange. Use computational principles from information theory to construct your message so you reduce the chances of miscommunication.

Empathy isn’t thought transference any more than starlings are psychic. When we embrace constructivism and complexity theory, we can create magic from individual interactions on the local level. I’ve seen this happen in the way I led my team of Code Whisperers at Corgibytes, and in the workshops on Empathy-Driven Development I’ve given through Heartware. When a system of empathy is optimized, collaboration emerges. New ideas and novel solutions arise naturally in a way that looks just as spectacular as starlings dancing across the sky.

This doesn’t happen from the top down. It’s not the CEO acting like a master planner who controls cogs in a machine. It happens from the bottom up. Leaders aren’t the people with fancy titles and corner offices. They’re the people who look at the interactions around them and use empathy to solve the problems directly in front of them. The CEO is (hopefully) one of them, but you are too. When we look at the overall system of how humans work together, effective coordination looks like magic — but in reality, we’re just flying in beautiful synchronicity with the people around us.


[1]: Iovenko, Chris. “This Annual Starling Murmuration Is so Dense It’s Called ‘The Black Sun.’” Popular Science, October 8, 2021. https://www.popsci.com/animals/starling-murmuration-black-sun/.

[2]: Reynolds, Craig W. “Flocks, Herds and Schools: A Distributed Behavioral Model.” ACM SIGGRAPH Computer Graphics 21, no. 4 (August 1, 1987): 25–34. https://doi.org/10.1145/37402.37406.

[3]: Reynolds referred to the simulated birds as “boids”

[4]: Meadows, Donella H., and Diana Wright. Thinking in Systems: A Primer. White River Junction, Vt: Chelsea Green Pub, 2008.

[5]: Waal, F. B. M. de. The Age of Empathy: Nature’s Lessons for a Kinder Society. London: Souvenir Press, 2019.

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Andrea, thanks for sharing!

回复
Justin Cribbs

Business Analysis, Professional at CoreLogic

8 个月

Thank you for sharing this fascinating deep dive and I'm looking forward to your book ????!

Angela Meyer

Enterprise Account Executive @ Invicti Security | Scalable AppSec Solutions for Every Organization

8 个月

Mike Mattos this might interest you.

Krisztina Hirth

"Our world's bright future will be built by people who have discovered that leadership is the enabling art. It is the art of releasing human talent and potential" - L. David Marquet

8 个月

"When a system of empathy is optimized, collaboration emerges. New ideas and novel solutions arise naturally in a way that looks just as spectacular as starlings dancing across the sky. " - I can relate to this to ??

Neal Peterson, LBBP, PMP

Managing Consultant seeking to develop better ways to work by observing and sharing

8 个月

Thanks for giving me something to read while waiting on call this evening.

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