[Essay] Humanity as Dr. Jekyll & Mr. Hyde: The Symptoms, Patterns, and Drivers
This essay is adapted from the Frankly published on February 20th, 2026 titled, “Humanity as Dr. Jekyll & Mr. Hyde: The Symptoms, Patterns, and Drivers.”
This year, the plan is to spend more time articulating the various (and increasingly relevant) responses to the more-than-human predicament. But before that, I’ll need to dive into the various scenarios ahead of us, current theories of change and what they’re missing, probabilistic planning, shortfall risk, and only then the broad categories of interventions with various subcategories.
Today’s topic underpins and precedes all these and is a deep and long one.
On a recent Frankly, I asked: “Why is it that most individual people day-to-day seem ‘better’ than the picture of humanity that is currently formed from our media and institutions?”
Part of my conclusion was that once systems scale, a small minority with dark-triad traits develop outsized influence and shape institutions and culture. This has gotten me thinking a lot more about scale itself – and about the patterns and drivers that show up once populations grow from small to large to huge.
I think this lens can help us look beyond the drivers of one particular issue: global heating, inequality, war, AI, or polarization. Rather, it can help us identify the forces that underpin all of them. When we zoom out like this, we can see that these problems aren’t isolated at all – they reinforce one another and behave like a system.
A lot of my earlier work (almost 20 years ago!) focused on the behavior of individual humans and small groups: steep discount rates, cognitive biases, supernormal stimuli, addiction, status, in-group/out-group bias, and the like. These are important to understand, especially for recognizing and maybe steering our own personal behavior. However, the behaviors of individuals and small groups have decidedly different dynamics than groups in the millions or billions.
The interconnected, 21st century crises are not emerging because humans suddenly became stupid or lazy – or even particularly malicious. But the same traits that helped our tribal ancestors coordinate, survive, and adapt start to become damaging and destabilizing at a civilizational scale.
I’m beginning to view this story as a kind of species-level phase shift. Humanity at small scales is Dr. Jekyll – but it morphs into Mr. Hyde once the scale exceeds some inflection point. So to illustrate the effects of this difference in scale, I’m going to outline three distinct layers of the more-than-human predicament:
The problems we can see – the symptoms
The recurring system-level patterns that produce them
The deeper forces underneath that accelerate and lock these patterns in place
If we don’t separate these layers in our conversations, we end up arguing at the wrong level and talking past each other – even when we might agree on the values and stakes. In action, this means we often attempt to fix symptoms while quietly reinforcing the same dynamics that produced them.
N.B.: Along the way, I’m going to say some things that may sound provocative at first. A lot of our familiar labels – like capitalism or colonialism or patriarchy – describe real harms, but they’re often describing downstream expressions. I’m trying here to point at the deeper machinery underneath.
Symptoms
I’ll start with the symptoms – the issues front and center in the metacrisis zeitgeist – before we go underneath to patterns and lastly the drivers. These are issues that most of The Great Simplification community is well aware of, so I’ll be super brief here.
This list includes: global heating, biodiversity loss, soil degradation, exceeding 7 of 9 planetary ecological boundaries, rising inequality and poverty (at the same time as all-time stock market highs), geopolitical tensions and war risk, polarization, attention fragmentation and psychological strain, widespread depression, anxiety, and loneliness, and much more.
These are usually each treated as separate issues, with different vocabularies and experts. In practice, however, they arise together, accelerate together, and their ‘solutions’ often push against one another.
This list – and you all know it’s much longer than what I just said – is what I’m going to call the “symptoms,” not as a way of dismissing them, but in the diagnostic sense. Calling them symptoms is a way for us to acknowledge that something deeper is driving them.
A final backdrop worth explicitly naming is the biophysical constraints underneath all these phenomena that are non-negotiable. Energy and materials have biophysical costs. Net energy matters more than gross energy. Feedbacks in the natural world are delayed and often initially unknown. Decline in both natural and human systems tends to be faster than ascent.
These phenomena are features of physics and ecology. I’ve talked about this a lot, but human systems – markets, technologies, and institutions – are bound by those constraints, whether we design with them in mind or discover them the hard way later.
Now that we see the symptoms, we can move to the more interesting questions:
Why these problems?
Why do they show up together?
And why now?
Systemic Patterns
When we zoom out across history and across societies, the same kinds of outcomes and cycles keep appearing. Today, I’ll label these recurring outcomes as systemic patterns. Once you start looking for them, they show up again and again across cultures and political systems.
These patterns are not accidents, but they’re also not human moral failures. What I’m doing here is objectively describing human behavior in large groups, not complaining or blaming.
I’m going to name six systemic patterns here – the list is not exhaustive but when combined, they explain much of what we’re seeing right now in 2026 Common Era.
Systemic Patterns: Power-Law Concentration
In many systems, both within the natural and human worlds, outcomes don’t distribute evenly. In fact they do the opposite: they concentrate. In ecosystems, a small number of species capture most of the energy flow. In forests, a few large trees intercept most of the sunlight as well as hold most of the biomass. In river basins, most water ends up moving through a handful of channels. This is akin to something that many of you might have heard of: the 80/20 rule, where 20% of inputs in a given situation are responsible for 80% of the outcomes.
This same geometry expresses itself in human systems: a small number of firms capture most of the profits, a small number of platforms capture most of the attention, and a small number of countries capture most of the surplus energy and materials.
Sociologists call this the Matthew Principle after a biblical passage about the rich getting richer. It’s based on the idea that initial advantages tend to compound due to feedback loops. Those who start with more tend to get more, and those who start behind fall further behind. This isn’t because of malice, but because systems amplify early differences once scale enters the picture, and systemic power only compounds from there.
As we’ll see, once this power-law concentration sets in, it reshapes everything downstream.
Systemic Patterns: Overshoot and Depletion
The next systemic pattern is overshoot. Overshoot is an ecological phenomenon that describes what happens when a population grows beyond the long-term carrying capacity of its environment. That usually happens because the population finds a way to draw down stored stocks instead of living within ongoing flows – think accessing groundwater instead of rainfall or fossilized hydrocarbons instead of daily sunlight.
For a while, it all looks like success…but eventually the bill arrives. The ecosystem can only stay in overshoot by drawing down stocks – but depletion follows when those stocks are reduced faster than the flows that rebuild them. When that happens the system can no longer support the scale it once achieved. Commonly used examples of overshoot are the reindeer on St. Matthew Island or the Atlantic cod fishery on the East Coast.
Systemic Patterns: Arms Races
The third systemic pattern comes in the forms of arms races – an arms race happens when one person, player, corporation, or nation’s upgrade forces everyone else to upgrade just to maintain their position. Once one actor adopts a powerful new capability, others feel they must respond in kind. It’s not because they want to escalate, it’s because standing still or ignoring the new capability on the gameboard becomes too risky.
This often shows up in militaries, corporate competition, finance, resource extraction, and very clearly now in AI. Even actors who strongly prefer restraint eventually end up participating because opting out carries penalties.
Arms races aren’t caused by bad actors but merely by the fear of falling behind. They lock systems into trajectories that are really hard to exit.
Systemic Patterns: Jevons Paradox
The next systemic pattern is something I’ve discussed many times on this platform – Jevons paradox. When we make something more efficient, there’s a natural expectation that it will result in us using less of it. But efficiency lowers cost in large interconnected economic systems, which often expands use and demand for those who previously wouldn’t be able to afford certain things. It also frees up surplus to be spent elsewhere.
Modern cars get more fuel efficient, but then we drive farther and in bigger cars. Faster logistics and cheap shipping made it effortless to buy one small thing at a time, so we placed more orders, and more brown trucks showed up in the driveway. Efficiency improvements don’t automatically slow systems down – quite often they speed them up as freed up capacity is reinvested into more throughput.
At the micro level, gains seem like restraint and savings, but they become acceleration at the system level. This is a powerful pattern explaining the growing heat engine of the global economic superorganism.
Systemic Patterns: Tragedy of the Commons
The fifth pattern is often called the “tragedy of the commons.” Many of the most important challenges we face require coordination across large groups: climate, oceans, weapons control, AI alignment, and financial stability. The problem is that the short-term incentives facing individual humans, firms, or nations rarely align with the outcomes that would benefit the long-term well-being of society – or the biosphere – as a whole.
The key point is that acting responsibly feels like a cost when others don’t also act responsibly.
In a game theory sense, defection and selfishness actually feels rational to us in the short run across many domains. Each actor protecting themselves in isolation ends up degrading the shared system that everyone depends on. The result is that trust erodes, making further defection even more likely.
This is the tragedy of the commons expressed at scale – even when most participants understand and care about the problem, systems drift toward outcomes that none of us explicitly want or choose.
Systemic Patterns: Simplification
The final pattern is simplification. As systems grow more complex, optimized, and interconnected they also become more fragile. They start to require more energy, tighter coordination, and fewer interruptions just to keep functioning.
This is sometimes called complexification, a concept popularized by Joseph Tainter – who was an early guest on the podcast if you want the longer explanation.
When shocks arrive or resources tighten, complexity becomes a liability. Systems respond by shedding what they can no longer support: ecosystems lose species and complex life, institutions narrow and cut back on services, and economies lose diversity and optionality of both jobs and goods and services.
Simplification is what happens when a system can no longer afford its current complexity. It shows up again and again in both natural and human systems.
Given the scale and interdependence of the modern human project, any simplification ahead is unlikely to be minor – which is why I insert the adjective “Great” before I use it.
Digging Deeper
Those are six systemic patterns:
Power-law concentration
Overshoot and depletion
Arms races
Jevons paradox
Tragedy of the commons
Simplification
These patterns describe repeated loops of our system – but they don’t explain why these things keep happening. To understand why these patterns appear across cultures and technologies, we need to drill down to a deeper level.
Before I start describing the drivers, there’s a critical context shift I want to highlight. Other podcast guests have said it in various ways: John Gowdy, Lisi Krall, Luke Kemp, Joe Tainter, and many many others actually. They’ve said that there was a distinct phase change in how human behavior expressed itself before and after agriculture. For most of our history, the traits that made humans successful were the exact same traits that kept us in balance with each other and with nature. In small groups, our instincts worked as checks and balances rather than accelerants. Social status was earned face-to-face every day. Power was visible and bounded by the tribe. Resource use was constrained by our muscles, time, and proximity to the things we were doing. Consequences from our actions arrived quickly enough that we could learn from our mistakes.
Small scales acted like a throttle – or muzzle – on aggregate human behavior. They limited how far our errors could travel.
Scaling up changed everything.
As stable climate and agriculture enabled human systems to grow larger, faster, and more interconnected, these adaptations and instincts didn’t disappear – they stayed with us and were amplified. When that amplification outgrew restraint, the character of the entire system changed.
This wasn’t a moral failure per se, rather a profound Jekyll and Hyde phase shift for Homo sapiens: from Dr. Jekyll at small tribal scales to Mr. Hyde at larger population scales.
With that context we can talk about the deep drivers underneath the patterns.
The Deeper Drivers: The Maximum Power Principle
The first deep force is what ecologists call the Maximum Power Principle, which I’ve talked about before, so I’ll keep it short. Across biology, ecology, and human systems, there’s a recurring tendency: systems that capture and use energy more effectively tend to outcompete those that don’t. Plants that grow faster shade out others, animals that secure more energy reproduce more successfully, and societies that mobilize energy at scale tend to dominate territory, production, and wars.
For most of human history, this tendency operated inside pretty tight constraints: small groups, low energy density, little storage, and with immediate feedback to their actions. Maximizing power expressed itself as local adaptation, not a runaway Superorganism. This matters because humans didn’t suddenly say, “I think we should now maximize power!” with the beginning of organized agriculture. We were always doing that. What changed was that the historic brakes on our behaviors and actions were removed.
Once fossil fuels entered the picture, this biological tendency went into overdrive. Suddenly, our success wasn’t constrained by muscle, land, or seasons – they were constrained only by access to dense energy and the ability to build more machines that could deploy it. Economic growth, military power, and technological expansion all became expressions of energy throughput.
The key is that maximum power never asks whether the system is wise, optimized for long-term stability, or whether outcomes are sustainable. It rewards speed, scale, and advantage in the moment.
Importantly, no one designed it that way – systems that didn’t follow this path were just outcompeted by those that did. Once societies organize around that logic, the maximum power principle acts like a gravity well: everything else bends around it and toward it. Power concentrates, feedbacks stretch, group identities harden, and time horizons shrink.
You might be asking, “How does this relate to the 80/20 rule?” I suggest maximum power explains the drive toward more throughput. The 80/20 pattern describes how gains and leverage concentrate once things scale.
The Deeper Drivers: Hierarchy Drift
A second driver – a really critical one – is what I’m going to label here as “hierarchy drift.” Before I describe it, I want to point out that a lot of the “isms” we argue about are real, but they’re actually downstream of something deeper. They’re what power and dominance morph into once scaled. By describing this, I’m aiming at the conditions that continue producing these systemic effects.
In small groups hierarchy was temporary and contextual – someone led a hunt, someone else knew plants, and someone mediated conflict. Status moved based on the situation, and authority shifted with the task at hand. Importantly, if someone abused power the costs were immediate and personal.
At larger scales, that changes. Because surplus can be stored, power can persist beyond a season or even a generation. Individual control detaches from one individual’s contribution to the broader group. Once that happens, the selection pressures shift. Systems stop selecting primarily for competence and begin selecting for strategies that win status and control. From there, power can be held onto rather than constantly renegotiated.
In small groups, coercive behavior is expensive – people see it, and they respond. At scale, it can actually be profitable because the costs are borne outside the core group – and at a later date. So the traits that would have gotten you pushed out of the camp start to look like “leadership” when the metrics reward domination, persuasion, and risk-taking without associated accountability. A small minority can steer outcomes once they control the socioeconomic chokepoints.
Control over resources leads to control over narratives as well. The ability to insulate oneself from feedback is critical because if a bunch of negative consequences were to show up immediately, the group would handicap or even eliminate the current power holders. This is what I mean by hierarchy drift – over time, people and institutions in control become less exposed to consequences of their decisions.
Once this dynamic sets in, it reinforces itself. Those with power shape the rules – rules that favor accumulating more power. Gradually, then very suddenly, the system begins selecting for dominance rather than stewardship. Cue the dark triad phenomenon and advantage – plus the agricultural, industrial, and perhaps artificial intelligence revolutions.
In this layer-model, patriarchy and colonialism typically show up as downstream expressions of hierarchy drift. They’re real – I’m just saying they’re downstream of something more fundamental.
Hierarchy drift isn’t unique to modern capitalism or any single political system. It is the phase shift in dominance and hierarchies with any large number of humans – we see it in empires, corporations, bureaucracies, religious institutions, and anywhere else scale and stored surplus allow for power to persist.
Power then stops being a temporary tribal role and has starts behaving more like property you can own. One doesn’t need evil intentions for this to happen.
The Deeper Drivers: Delayed and Distorted Feedback
Another core driving force which synergizes with hierarchy drift is delayed and distorted feedback. In small human systems, feedback used to be fast and hard to miss. If you overhunted your area, the game disappeared. If you poisoned a stream, people in your village got sick. Actions and consequences stayed closely tethered, which allowed for learning and course correction.
Scale breaks that relationship – as societies grow larger and more complex, actions and consequences get routed through systems instead of being felt directly or personally. Causes become harder to trace and responsibility becomes harder to assign. We burn fossil fuels today and most of the warming shows up decades and centuries later. We degrade soils now and see yield losses generations down the line. We throw something away and have no idea where the trash ends up or what pollution it causes halfway around the world.
When the true signal arrives, the system that caused it is often already locked in. This is how systems drift into overshoot without anyone intending them to.
Furthermore, distortion of the signal matters as much as delay. Information travels upward through layers of institutions, incentives, and narratives before reaching decision-makers. So the real signals get softened, reframed, or filtered out entirely. What reaches the top is rarely the full picture – it’s often simplified, sanitized, and as we see everywhere today, purposefully optimistic.
Because modern systems are tightly coupled, small distortions propagate into large errors and decisions are made using inaccurate information. By the time intervention becomes obvious, the cost of course correction is much higher than it would’ve been before.
Delayed feedback removes the natural brakes that once kept human behavior within bounds, and distorted feedback removes the clarity needed to respond effectively even when problems are visible. Together, they allow accumulation, pollution, and expansion to continue long past the point where restraint would have been feasible.
You can see how this force interacts directly with hierarchy drift: the further decision-makers are from consequences, the weaker the corrective signals become.
The Deeper Drivers: In-Group and Out-Group Dynamics
The next core driver is how humans divide the world into “us” and “them.” That instinct is, of course, ancient. In small ancestral groups, it ensured our survival and often supported essential cooperation.
As societies grow beyond face-to-face relationships, identity replaces what trust and feedback used to do. Group membership becomes a shortcut for judgment, and loyalty starts to matter more than accuracy.
As systems scale, competition between groups intensifies. Nations, companies, political identities, ideologies, and platforms each optimize for their own position inside a shared system. Costs get pushed outward and responsibility gets diluted – channeling directly into arms races and tragedy of the commons dynamics. Global heating, fisheries, and nuclear weapons are all clear examples of this.
Most humans are smart – we see the collective danger. But instead of wisdom or coordinated response, the first questions quickly become, “Says who?“ or “Who’s going to pay for it?” and “At whose expense?“ Decisions increasingly get filtered through identity before they’re filtered through evidence.
This instinct also shapes how information is processed. Signals that threaten one’s group identity get discounted, and warnings from outside the group are ignored or dismissed. Scientifically-grounded risks become harder to stomach than reassuring stories (even when those stories are false). This all makes it nearly impossible to comprehend the nuance, depth, and complexity of our situation.
Thus entire societies can understand a problem in theory and still fail to act. Our instincts never changed – the scale did.
The Deeper Drivers: Time Bias
The next, and next-to-last, driver is how humans value time. As biological animals, we discount the future heavily. This actually made sense for most of our 300,000 years as a species – if you lived in a small group with high mortality and real uncertainty, prioritizing the near term was adaptive. That instinct still exists.
The problem is that, once societies scale, time bias has huge downsides. Modern systems prioritize short-term gains over long-term viability – quarterly earnings and election cycles start to matter more than ecosystem health or infrastructure maintenance. Immediate brain stimulation matters more than reading, working out, or meditating.
Decisions that look rational in the moment start to accumulate into outcomes that, over time, are unstable.
As you can already guess, this shows up everywhere in our modern society. Overfishing outweighs restraint because the fish you leave today might be caught by someone else tomorrow. Extraction beats stewardship because the payoff to leaders is faster and more certain. At the individual level, steep discount rates feel normal and even logical. But at the system level, they slowly hollow out the future.
This time mismatch creates a skew toward short-term optimization, even when most people increasingly understand the long-term consequences.
This is different from the delayed feedback I mentioned earlier. Delayed feedback is about when consequences arrive. Time bias is about how we value the consequences versus the costs.
Together, they form a powerful social trap – as my PhD advisor Robert Costanza calls them – and they synergize with all the other core drivers I’ve outlined.
The Deeper Drivers: Anthropocentrism
Last, but definitely not least, is a driving force that’s been normalized for so long it feels invisible: how narrowly we define “us” at larger scales.
Alongside power solidifying and accumulating as scale increases, our cultural sense of being part of nature tends to shrink. Power is not only over other nations, competitors, or humans, but also refers to dominion over the natural world. Dr. Jekyll loved nature. Mr. Hyde does too, but primarily as cheap inputs and waste sinks on spreadsheets. In physical terms, functioning ecosystems are the largest asset on any civilization’s balance sheet. Our institutions just don’t know how to count them.
So when energy, materials, or attention are allocated, the living world – culturally and economically – is treated as static, infinitely available, and politically silent. Once that boundary is in place, it’s hard to remove because drawdown of shared resources becomes rational and growth requires ecosystem liquidation.
As most of you are now aware, at civilizational scale the living world absorbs this damage quietly…until it no longer can. When the pushback finally arrives, it too will likely arrive at scale.
Conclusion and Reflection Questions
These are the deep drivers that keep the systemic patterns in place:
The Maximum Power Principle
Hierarchy Drift
Delayed and Distorted Feedback
In-Group and Out-Group Dynamics
Time Bias
Anthropocentrism
You might disagree with the specific symptoms, patterns, or drivers I’ve outlined. But I think separating the more-than-human-predicament into these layers is useful regardless. It helps us avoid arguing at the wrong level.
The truth is, despite our situation, none of the forces I’ve described here are bugs or errors in the human system. They’re extensions of traits that helped us survive and cooperate for most of our history.
I think this is where the Jekyll and Hyde framing is important.
In small groups, with visible consequences and tight feedback, our instincts kept us more or less in bounds. Power was negotiated, status was earned, and mistakes stayed local. That was our Dr. Jekyll phase.
As scale increased, energy abundance rose, and tools began to outlast relationships, suddenly those same instincts stopped being self-limiting. Power could be accumulated instead of renegotiated. Stories – including algorithmic ones – replaced lived experience. Complexity obscured consequences. That’s our Mr. Hyde phase – and I could argue we are late-stage in this phase at the present moment.
Mr. Hyde isn’t evil. He’s what happens when ancient instincts operate inside systems that move faster and reach farther than our moral intuitions were shaped for. The ground we’re standing on today is one where Mr. Hyde – for our species – has slowly but firmly taken the wheel. That’s a very different situation than most of our current solution narratives assume.
I want to close by offering a few questions to consider – and maybe for you to discuss with people in your life:
Are we trying to solve the right layer of the problem? Or are we repeatedly optimizing on the symptoms while reinforcing the forces underneath?
What would it look like for a system to recognize and assume human fallibility rather than human virtue? Systems that work even when people are tired, scared, status-seeking, and short-term oriented?
If many of our hardest problems come from instincts that once helped us survive, what does responsibility mean at a civilizational scale? Not blame or guilt, but responsibility.
How do we build systems where our ancestral “Jekyll” traits can persist even as scale grows large? We’ve seen partial answers in Mondragon cooperative enterprises, in commons-based resource management, and in cultures that deliberately shorten feedback loops. Are those solutions fundamentally local or is there a way to carry them forward without scale morphing them back into Mr. Hyde?
What does agency look like when no one is really in control, but dark triad types are the gatekeepers of our social structures? What kind of agency is still available to the rest of us?
And maybe the hardest question is this: if understanding these forces gives us better brakes, but not a steering wheel, when and how do we choose to slow down? Or do we only respond after the crash?
This was a long one, and perhaps a little bit of a downer. Lighter fare ahead, friends – well mostly.
Thanks for reading.
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Brilliant hypothesis, Nate. This framework brings coherence to so much of the seemingly illogical chaos unfolding around us. Thank you for the years and decades of inquiry and analysis that I know informed it. 🙏 🔑
When I run my Living in Earth Household course again, this essay will be a required reading. Thank you for this. Few essays hold our worlds so well.