Your Mind Is Not Like a Computer; It Is Like An Ecosystem: Minding Your Metaphors About the Mind

I am what is often referred to as a “high-achieving dyslectic.” From a very early age, I was made aware that my mind simply worked differently than other people’s. Fortunately, while in elementary school, I was surrounded by caring special educators (including my mother) who taught me to embrace my uniqueness. But it was not until I started studying philosophy and psychology in college that I realized just what an advantage my dyslexia was.

Make no mistake: in some contexts I am truly disabled. Put me in a spelling bee or have me proofread a paper, and you might be shocked that I ever graduated high school. However, I have come to realize that my dyslexia is a blessing because it forced me to reflect upon the nature of my own mind. From an early age, I was never under the impression that what worked for others in school ought to work for me. I was free to embrace a nontraditional approach to schooling and my own learning. And as I deepened my understanding of psychology, I came to see that I had actually been developing a fundamentally different “working model” about the nature of the mind. The metaphors I used to make sense of my own mind (and the minds of others) were different from most — and this made all the difference when it came to how I pursued my own learning and education.

Metaphors and Meaning-Making

Recent work in cognitive linguistics has demonstrated that metaphors play an essential role in science and in cognition more generally. In their groundbreaking book, Philosophy in the Flesh: The Embodied Mind and Its Challenge to Western Thought, modern-day philosophers George Lakoff and Mark Johnson make this point very clearly. Metaphors form an inescapable and ubiquitous aspect of our meaning-making systems, especially when it comes to describing things we cannot see or do not quite understand, such as the human mind. We speak about things we do not understand as if they worked like the things we do understand. This can be a powerful aid to understanding, but it can also lead to distortions, errors, and a comforting illusion of knowledge where there is really mostly confusion.

Historically, scientific models of the human mind have evolved through a series of metaphors. Sigmund Freud used several metaphors to describe the mind, but the one with the most explanatory power was the metaphor of the steam engine. “Psychic energy” was understood as if it were steam compressed within a chamber. Bottle up too much energy and tension, and it will eventually explode elsewhere as a neurotic symptom that you cannot understand. Sex, of course, was the great pressure valve for Freud, a necessary way to release potentially dangerous buildups of energy. The dynamic workings of the mind, which Freud used to explain psychopathology, were all metaphorically related to the basic mechanisms that drove the machines that propelled the Industrial Revolution.

This view fell out of favor in the 1960s when cybernetics came on the scene, and soon computers replaced steam engines as the dominant metaphor for the mind. By the 1980s, the metaphor of the “mind-as-computer” was fully embraced by the emerging field of cognitive science, and it continues to dominate thinking today. By now it has even seeped into the popular culture and become a part of our everyday school vernacular. According to this metaphor, the brain is hardware and the mind is software. The mind is fundamentally about “information processing,” and our individual information processing units vary only in terms of their speed and memory capacities. Smart students have a lot of RAM and fast download speeds. Students who are struggling just “don’t have the bandwidth.” If students follow the right programs and sub-routines, they will encode the right information, which will be stored in memory and made available for retrieval later. Self-help websites today talk about “hacking your mind” to improve your performance, while countless tutors and even some widely used curricula orient their pedagogy almost entirely around the idea that the mind can be treated like a computer.

Incidentally, this was the metaphor I instinctively rejected as a result of reflecting upon my own dyslexia. In part, I rejected it simply out of self-defense: If the mind is a computer, then I must have some faulty hardware. The idea that I was broken, defective, or somehow a lesser version of my non-dyslexic peers was a conclusion I was unwilling to accept (and one that I was actively encouraged to reject by some amazing teachers). But as my reflection deepened and my reading in philosophy and psychology expanded, it became increasingly clear just how terrible the mind-as-computer metaphor actually is. For one, computers have no emotion. All computers work in the same way, and process information in identical manner. Give two computers the same input, and you should expect to get the same output. Computers are not creative; they do what they are programed to do. They do not build knowledge, but merely process the knowledge put into them. They are not active, but passive. They are not internally complex. Even if they contain a “parallel processor,” computers are still best characterized in terms of a single central processing unit. This assumption of unidimensionality is why the IQ and other reductive standardized tests fit so well with the mind-as-computer metaphor: IQ is just a measure of the size and strength of your central processing unit. And so it goes, as oversimplification is piled upon oversimplification, until a conception of the mind emerges that plays directly into one-size-fits-all ideas about education and pedagogy. Now, any educators who are paying attention these days know that a one-size-fits-all approach to teaching and learning is a bad idea. Yet, as a result of the power of the mind-as-computer metaphor (and a host of other factors), the idea continues to infect most of our school programs to one degree or another.

The Mind as Ecosystem

A better metaphor (and the one I had intuitively built while growing up) can be traced to the great Swiss psychologist and epistemologist Jean Piaget. Piaget argued that the mind is best understood as an evolving organism — living, growing, and self-regulating in a metabolic relationship to its environment. More recently, a group of Neo-Piagetians, headed by Harvard University’s Kurt Fischer, has begun talking about the mind as an ecosystem. Fischer’s work can be found in the Journal of Mind, Brain, and Education, which he founded, or on the website for his Dynamic Development Laboratory at the Harvard Graduate School of Education (just Google it).

According to this view, the mind is best understood as a complex and dynamic system, always in process, always changing, growing, and becoming more diverse and differentiated. At the same time that they grow in internal complexity, ecosystems also become more integrated and specialized, filling up their niches and fostering symbioses. Ecosystems are composed of a wide variety of independent and yet co-evolving species, so there is not one central “unit” that can serve as an overall measure of the ecosystem. Rather, to understand an ecosystem, you must take multiple measurements in a variety of places across a variety of time scales. Ecosystems are also sensitive and actively responsive to the larger environments in which they are nested. They can be easily disrupted and thrown off balance, but they are also generative and creative, self-regulating, and self-transcending. They are adaptable, open systems, and are constantly in a state of dynamic equilibrium. As ecosystems evolve, they display nonlinear growth, with jumps, dips, regressions, and daily and seasonal changes and rhythms. Their growth is not simple and linear, but messy and dynamic. And no two ecosystems are the same. Every ecosystem is unique. Give two ecosystems the same input and you should not expect the same output.

To clarify, imagine that each different skill and idea you have is like a living organism; each grows relative to the time and attention it is given and as a result of being in some contexts rather than others. If all you do is put yourself in contexts where your attention goes into playing video games, then your skills and ideas related to video games will evolve. Some of these evolving video-game skills might form symbiotic relations with other skills, such as eye-hand coordination or skills for collaboration and humor. All of your skills and ideas are co-evolving, sometimes joining together to create higher-order skills, and sometimes differentiating into sub-skills as they are refined relative to environmental niches.

Your skills and ideas also compete for energy and exercise, as growing one set of skills, such as playing violin, takes up the time and energy that would be needed to grow a different set of skills, such as doing algebra. You are an ecosystem of co-evolving skills and ideas, each developing at a different rate, with complex symbiotic and competitive relations emerging among them over time. You are not simply smart or dumb, having either a fast or slow information-processing unit between your ears. Instead, you are an ever-changing, context-sensitive ecosystem in process, with no central tendency or summary statistic. You may have highly evolved skills in some contexts, and primitive ones in others. You may be on the verge of a major evolutionary leap forward (a great “Aha!” is on the horizon), while at the moment you appear to be struggling. The only thing normative is uniqueness, ceaseless change, and nonlinear growth.

When I first discovered these ideas in the work of Piaget, I felt as if I had finally found a metaphor that captured my experience and confirmed my nascent and inarticulate ideas about how the human mind really works. While studying with Kurt Fischer in graduate school, I had a chance to work closely with this idea of the “mind-as-ecosystem.” I came to see that it allowed me to understand differences in how people learn not as disabilities but as alternative pathways of growth. Unlike the computer metaphor in which variability between individuals is lamented as some kind of software glitch (amenable to a technical fix such as an ADHD drug or heavy doses of “drill-and-kill” test prep), the ecosystem metaphor suggests that variability is the norm. Variability should be expected and then leveraged. My dyslexia was a difference, not a disability. This always felt true to me, but now I could understand why.

The ecosystem metaphor also explained what I had experienced myself: that performance and ability are radically context sensitive. I knew that in some contexts, such as class discussions, I felt smart and empowered, while in others, such as when taking standardized tests, I felt incompetent and victimized. But if the mind is both context sensitive and dynamically self-regulating, then this variability in performance makes sense, and these are no longer contradictory experiences (change the context and you change what the mind can do). Relatedly, the idea that different skills and ideas evolve at different rates also rang true and helped to explain why so many individuals just seem so lopsided, with strong skills in some areas, such as mathematics, but weak skills in others areas, such as interpersonal relationships. But perhaps most important, the mind-as-ecosystem metaphor explained why traditional forms of schooling always seemed so insane and counterproductive to me.

Changing Your Metaphors Changes Everything

As I continued with my graduate studies and became increasingly involved with the world of K–12 schooling, it became clear that one of the main reasons we stick with simplistic metaphors such as the “mind-as-computer” is because they do not challenge our status quo systems and processes. Fundamentally changing our dominant metaphor for the mind would require fundamentally changing our educational practices. It would make us change everything, from standardized testing to classroom activities. There are a few examples of schools that orient around such an alterative metaphor. The Landmark School in Boston has explicitly been using Fischer’s work for years, catering directly to students with a wide variety of learning disabilities and finding remarkable success. But this is rare thing. Most schools are suited to meet the needs of only a very narrow range of students, and at times actively exclude more diverse minds.

As all this sunk in, I partnered with Fischer and Theo Dawson to build a nonprofit dedicated to reforming standardized testing infrastructures, based on the new science of learning and the new and better metaphors for the mind it implies. For the past 20 years, high-stakes testing has been a defining feature of most post-industrial educational systems, effecting and directing the lives of more than 50 million people each year. The goal of the nonprofit — Lectica, Inc. — is to supplant these traditional forms of standardized testing and usher in a new status quo in which each student can be viewed as a unique and evolving ecosystem of skills and ideas. The goal is to wean all schools of their long reliance on high-stakes summative testing and shift to the use of learning-science based diagnostic assessments. According to the Neo-Piagetian view operationalized by Lectica — one supported by a growing body of research on the brain and learning — testing should be low-stakes, embedded, and formative, with numerous assessments peppered diagnostically throughout the curriculum to support the individual development of each and every child.

With Lectica up and running, I turned to what had always been the heart of the issue for me: the injustices done to students as a result of their being viewed and treated like something they are not. These metaphors about our minds matter because they impact how we understand and work with students. My dissertation, Social Justice and Educational Measurement, has been published as a book. It focuses on the social justice issues involved with contemporary testing regimes and argues that part of securing a more just future for all students requires changing the way we think about the nature of the mind and how to measure it.

Educators are not computer programmers, and students are not passive machines. Instead of this old, narrow and harmful way of thinking, we ought to move toward a view of educators as environmental stewards tasked with nourishing complex ecosystems; each one autonomous, creative and unique, each worthy of respect. One metaphor contributes to the perpetuation of educational injustice and the deepening alienation of our students; the other leads to a more just and creative future for education.


Zachary Stein was educated at Hampshire College and Harvard University. He is the academic director of the activist think-tank at the Center for Integral Wisdom and a member of the core faculty at Meridian University. His book Social Justice and Educational Measurement was published by Routledge in early 2016. You can find out more about his work here:, or contact him at

Article originally published in Independent School magazine (National Association of Independent Schools), Fall 2015; published here by permission from the author.