TL;DR
The brain evolved for immediacy and still runs that firmware. Slow, diffuse, planetary-scale threats find no purchase on circuitry built for snakes and rival tribes. Over millennia, humans built cultural architectures to compensate for what individual cognition cannot manage alone. Scientific institutions, legal systems, civic deliberation and social contracts that worked required enormous effort and social enforcement to hold together. Then came an economy optimised for frictionless speed that dismantled the slow institutions that had been managing them, and we are back to where evolution left us.
In 1987, I went to live in Zimbabwe. What a joy and a privilege that was for a greenhorn academic. A postdoctoral fellowship in Africa was dreamland. One of my first safari adventures was to Mana Pools on the banks of the Zambezi River. One morning we were back from a game drive and at the edge of the camp I spotted a snake that required investigation, for most in that part of the world are quite dangerous. “Oh, it’s okay,” I announced with unmerited surety, “just a young python.”
It was indeed an African Rock Python (Python sebae), not venomous and harmless enough for me to lie down on my stomach for a close up photograph. Not happy with this intrusion, the snake decided to strike, which I didn’t think it could. It missed, and I jumped back up almost as fast.
I escaped my lapse in instinct and sat back down, still intact and able to recount the story at dinner parties ever since. In the telling, it was clear that Westernised humans would not survive the perils of nature for very long without our machines, buildings and supplies. We have lost the knack that we must have had, given humans had lived with such perils for thousands of generations.
The truth is that we still have the mental acuity for survival. That wiring still dominates our thoughts. Our first thought is for the snake in the grass. What is coming next, and very soon after, is our second, third and fourth thought too. This now thinking is what kept us alive on the savanna. But it might be a liability for the scale and pace of the challenges posed by a population of 8 billion humans.
The problems that now threaten human systems arrive as trends, as parts per million, as basis points on a discount rate, as a fraction of a degree per decade. They are real, but they do not trigger the circuitry that evolved to handle immediate threats. The brain that scans for immediate danger finds nothing to lock onto, and so it returns to the present moment, which feels manageable, and files the rest under someone else’s problem or someone else’s century.
Human brains evolved for immediate threats and small tribal groups, and that hardware has never been upgraded. Short-termism, in-group loyalty, and scope insensitivity kept ancestors alive. They now filter out the slow, abstract, and planetary-scale threats that define the Long Emergency.
Evidence from evolutionary anthropology, neurology, ethnography and archaeology suggests that for approximately 300,000 years, Homo sapiens lived in small bands typically numbering 25-150 individuals, with social structures rarely exceeding Dunbar’s number, the sweet spot of approximately 150 people optimal for stable social relationships.
Survival in these small groups required a brain to process information because where our ancestors lived, immediate, tangible threats such as predators, hostile outgroups, resource scarcity, green tree snakes, and environmental dangers, were present every day. Structures such as the amygdala, which plays a key role in threat detection and emotional processing, are primed to respond to stimuli that are immediate, concrete, and emotionally charged. This prioritisation was advantageous when humans faced acute, short-term dangers like predators or social conflict. What we now call heuristics or biases helped make rapid, intuitive judgment and conserved cognitive resources. We were good at quick decision-making, even if not perfectly rational.
Many modern cognitive biases are direct extensions of this evolutionary tuning. For instance, the prefrontal cortex, responsible for long-term planning and abstract reasoning, is a more recently developed area of the brain and often defers to older, emotion-driven regions when decisions must be made under uncertainty or stress. This neural tension leads to systematic distortions in how we perceive risks, value rewards, and relate to others; distortions that are highly predictable and well-documented across cultures.
Temporal discounting, proximity bias, correctness bias, and in-group favouritism were all adaptive in a world of immediate decisions, where threats were physical, local, and fast-moving. Climate change, economic inequality, and global pandemics are none of those things. They are abstract, slow, and described in probabilities. The legacy wiring struggles to register them with the urgency the evidence warrants.
Of course, a brain that responds like this is not without benefits. Among other things, abstract thinking, symbolic reasoning, and cultural transmission are products of the same evolutionary process, running on the same neural substrate.
What the brain can do, under the right conditions, is remarkable. Humans can model future scenarios, consider consequences for generations, and plan for contingencies that have never been experienced. We can imagine our own deaths; a remarkable, difficult, and underappreciated capability. Clearly, the brain can handle abstraction, but it takes effort.
Some individuals and societies have demonstrated sustained ability to plan across generations and reason about abstract, long-term risks. Many Indigenous cultures maintained resource management practices across centuries, developing cultural frameworks precise enough to compensate for the short-horizon defaults of individual cognition. The knowledge was encoded in practice, story, and obligation rather than in spreadsheets, but the function was the same.
And then there is the man in the pure wool suit shorting AI stocks on the futures exchange. He responds to the immediate for future gain and is thankful for every bias.
Whilst we can comprehend planetary-scale challenges, doing so requires conscious effort and supportive cultural and technological systems. This framing helps explain why climate change, biodiversity loss, and other global challenges require special effort to sustain. It also suggests that systems designed to work with evolved psychology rather than against it stand a better chance of enabling the collective action the scale of those problems demands.
There is a risk of overstating how deterministic these cognitive biases are, given they create tendencies rather than dictate outcomes. Minds naturally process information, and motivation makes it possible to design systems that channel those tendencies rather than fight them. This is what has happened.
Modern information environments and economic systems often exploit cognitive vulnerabilities, amplifying distraction, polarisation, and inaction.
Modern information ecosystems operate primarily on what Tristan Harris, co-founder of the Centre for Humane Technology, calls an attention extraction business model, where revenue comes from maximising engagement rather than delivering societal value.
Algorithms amplify content that triggers emotional responses because outrage, fear, and tribal identity generate higher engagement. People stick around to say what they think, argue, and support the tribe. The architecture of social media is optimised for attention, and attention is easiest to capture when the content triggers emotions.
The bite-sized nature of modern media exploits the same vulnerability. Cal Newport’s argument in Deep Work is that the modern knowledge worker faces constant interruption severe enough to limit sustained concentration. Studies suggest the average worker maintains focused attention for 3 to 5 minutes before switching tasks. That is well below the threshold required to understand complex systems or generate meaningful insight.
Digital platforms also reward controversy over clarity. For example, a post that presents atmospheric data clearly and objectively gains modest attention. The same information, framed to imply controversy, achieves exponentially greater reach. The algorithm did not distort the science, but it distorted who heard it, and how.
Economic structures amplify cognitive biases as reliably as information systems do. Quarterly reporting cycles reinforce temporal discounting by rewarding immediate returns over long-term sustainability. Externalised costs exploit narrow framing by hiding the true impacts of consumption from the people making consumption decisions. GDP as the primary success metric encodes the same preference. It makes quantifiable growth legible and leaves well-being and sustainability off the ledger.
Information and economic systems aren’t uniformly exploitative, but their default settings tend to amplify cognitive vulnerabilities rather than correcting for them. This makes perfect sense when the bias delivers the response from the many that the institution desires. It is, after all, the path of least resistance.
Information environments could reward slower and deeper thinking, build information literacy as a core educational competency, and redesign recommendation systems to counterbalance rather than amplify bias. Economic systems could extend reporting timeframes beyond the quarterly cycle, incorporate success metrics broader than GDP, make externalities visible through pricing or transparency requirements, and develop governance structures with standing to represent future generations.
They could, and all it requires is treating cognitive architecture as a design constraint rather than a fixed liability. All of this sounds plausible, and it makes the attention to bias a bit of an excuse. We can’t help it because our savanna brains give us the tendency to respond immediately and draw us towards conflict.
It may sound excusable, but I am not expecting a global awakening where eight billion people collectively discard their smartphones and relocate to eco-villages. I wrote with that naive assumption in my book, Missing Something that reads like wishful thinking. The attention economy is a multi-trillion-dollar gravity well. The economic incentives to harvest human attention are too large, and the algorithms too effective, for a spontaneous mass uprising to occur.
A fracture is more realistic, and the early tremors of this cognitive split are already visible.
There is a genuine market for digital minimalism. Gen Z and Millennials are intentionally swapping high-powered smartphones for minimalist e-ink devices like the Light Phone, or installing text-only launchers on their screens. They are not doing it for nostalgia. They are doing it as a self-defence mechanism against digital burnout.
Governments are slowly waking up, proposing social media bans for minors and placing guardrails around algorithmic manipulation. Policy moves at a glacial pace compared to technology, so the macro change will take decades. The micro change is where the real action is. Owning the newest, most powerful technology was once a mark of status. The tables have turned. A screen-free life, genuine unavailability, and the capacity for deep uninterrupted concentration have become luxury goods.
A low-level worker in the modern economy is often compelled to be hyper-reactive, answering pings, monitoring dashboards, and responding to notifications throughout the day. The executive class, elite creatives, and top-tier engineers are the ones who can disappear for four hours into a deep work block to solve a single high-leverage problem. The split is already a socioeconomic reality.
But don’t be fooled, this is not corporate altruism. It is raw capitalism. Companies are discovering that expecting employees to be available on messaging platforms around the clock destroys the bottom line. Constant context-switching produces burnout and poor strategic decisions. Forward-thinking organisations are adopting asynchronous communication because deep focus is the only reliable way to produce high-value intellectual work.
If the analysis holds, the future is a stark and uneven cognitive class divide.
Those with the psychological literacy, resources, and discipline to engineer their environments will hold the monopoly on deep focus, critical thinking, long-horizon wealth accumulation, and emotional stability. Those trapped in the hyper-calibrated, dopamine-optimised loop will remain the product. Perpetually over-stimulated, anxious, short-sighted, and susceptible to outrage.
A system this powerful and this profitable will find a way to charge for the exit. Those who manage to engineer their way out are comfortable enough that they have no reason to dismantle the machine that produced the problem. The system does not need to suppress revolt. It just needs the people capable of leading one to feel they have already won.
The brain evolved for immediacy to ensure survival. Exactly as expected. A rustle in the undergrowth meant a predator, near and immediate. A drought hit the valley you could see from the ridge. A thrown rock travelled in a predictable arc. Problem, response, consequence was a tight loop and the scale was small. Human neurobiology was forged in this environment where problems were local, immediate, and linear.
The problems we now face are global, systemic, and exponential. Economic shifts, algorithmic feedback loops, climate systems, and information warfare are huge at every level and the human brain has no native sensory organs or cognitive defaults to comprehend problems at this scale, let alone navigate them.
But the same brain also produced the cultural architectures that compensated because we are nothing if not adaptive. Because biology could not handle large-scale complexity on its own, humans spent thousands of years building the heavy machinery of civilisation to achieve what the individual could not. Universities, legal systems, and scientific methods were designed to slow thinking down and verify truth before acting on it. Religious, philosophical, and civic frameworks forced individuals to consider legacy, generational time horizons, and duties to the collective rather than to immediate impulse.
None of this happened naturally. These slow thinking institutions require immense energy, social enforcement, and deliberate education to maintain.
And here is the crux of the modern crisis. The digital, hyper-marketed environment did not merely exploit individual psychology. It also dissolved the machinery that had protected us from ourselves.
Efficiency, convenience, and frictionless monetisation became the supreme values. When a society is optimised entirely for frictionless speed, it accidentally destroys the institutions that require deliberate friction to function. Deep journalism was replaced by rage-bait clicks. Long-form civic debate gave way to the character-limited post. Deep community bonds were replaced by parasocial networks.
The conditions that once activated our highest-level cultural architectures, silence, patience, shared localised truth, institutional trust, have been systematically engineered out of existence.
Think about this as an ecologist observing a species whose habitat has changed faster than its genetics can track. It is a description of an ecosystem out of equilibrium.
If the observation is treated as exactly that, an observation, the next logical question shifts. The question is no longer how to fix a broken brain. It is what new cultural architectures can be built to survive the scale of the world we now inhabit, given that the old ones have been dismantled.
We can move past the self-help guilt trip that you lack willpower, and past the standard tech-industry critique that Silicon Valley is evil.
The current predicament is a mechanical and evolutionary mismatch. Not a spiritual crisis.
Notes & Sources (for the curious)
Evolutionary wiring and tribal scale
The human habit of prioritising immediate physical threats over diffuse, slow-moving hazards is deep evolutionary tuning. The amygdala registers acute danger well before the prefrontal cortex can process abstract planetary risk. The circuitry is old, and it does not update on request. Isbell (2006) sets out this ancient neural prioritisation through the Snake Detection Theory. The framework traces primate visual acuity back 40 to 60 million years, to persistent predatory pressure from snakes. Ancient perils shaped modern sight.
Homo sapiens lived in small nomadic bands for roughly 300,000 years. Social cohesion and stable community relationships evolved within that context, and they hit a hard ceiling set by brain architecture. Dunbar (1992) established that human neocortex size correlates with a maximum stable social group of approximately 150 individuals. The threshold is fixed and that wiring does not scale. At 8 billion people, the ancient social architecture that held small bands together simply breaks under the load, destroying cohesion.
Cognitive biases and temporal discounting
Modern cognitive biases are direct extensions of evolutionary adaptations built to conserve scarce mental energy. Mechanisms like temporal discounting and proximity bias systematically distort risk perception by devaluing distant rewards and downstream consequences. What worked on the savanna produces poor judgement at civilisational scale because the wiring was never designed for these problems. Kahneman (2011) documents how fast, intuitive neural architecture routinely overrides slower deliberative reasoning under conditions of deep uncertainty.
The failure of modern populations to follow basic nutritional guidelines reflects an environment deeply mismatched with evolved cravings for calorie-dense foods. Data from the US Centres for Disease Control and Prevention (2022) indicate that only 10 per cent of American adults meet recommended vegetable intake. Roughly 12 per cent meet fruit targets. Instinct trumps advice. Evolved biology drives consumer choices that flatly contradict modern public health mandates.
Primary Sources
Dunbar, R. I. M. (1992). Neocortex size as a constraint on group size in primates. Journal of Human Evolution, 22(6), 469-493.
Isbell, L. A. (2006). Snakes as agents of evolutionary change in primate brains. Journal of Human Evolution, 51(1), 1-35.
Kahneman, D. (2011). Thinking, fast and slow. Farrar, Straus and Giroux.