The ecosystem of cognitive bias — Ten machines, one mind
THE MACHINERY OF BIAS · PART TWO OF FIVE
Picture a Tuesday at work. On your way to the morning stand-up you pass the VP's office, and something is off: moving boxes, flat-packed and stacked against the glass. Nobody mentions them in the meeting. By lunch, a message lands in the team chat — have you heard? Twenty per cent headcount reduction. The decision's already made. Nobody knows who heard it first, or from whom. It doesn't matter. By three o'clock the claim has a life of its own: repeated in the corridor with a knowing look, reshaped in a private channel, and by evening it sits, carefully worded, in somebody's LinkedIn post about reading the signs in our industry. Nobody has checked whether any of it is true. Watch what happens anyway.
That rumour — invented for this series, though I suspect you have lived some version of it — is going to travel with us from here to the final post. Because it shows the thing this whole journey is about: at every stop, the claim is the same, and the machinery working on it is completely different. The chat is not the corridor. The corridor is not the feed. And none of them is the quiet place, months from now, where the claim resurfaces as a "fact" everyone somehow knows.
We talk about cognitive bias as if it were one thing that happens in one place — a glitch in an individual head. It isn't. There is an entire production and distribution system for it, ten machines working around a single mind, and you live inside it. This series is a map of that system — and this post is the whole map at once.
And let me set the size of that claim before we start, because the size is the point. The picture most of us carry of cognitive bias comes from the famous lists — if you have seen the wheel poster of the named biases (the Cognitive Bias Codex: roughly 180 entries, collected and grouped by Buster Benson, drawn by John Manoogian III), you have seen the best of that tradition. Learn the names, the story goes, and you can patch your own reasoning. But counted across the whole system rather than just inside the head, tjust over a thousand catalogued biases and primitives — 1,030 as of August 2026The famous lists cover, in this series' terms, mostly the products of two machines out of ten. The other eight run in places the bias literature barely visits: feeds, prices, procedures, records, the words themselves. That is why one word in this post's title matters more than any other: ecosystem. Not a list — a production and distribution system, with creators, reshapers and control infrastructure, arranged around exactly one mind And that is the promise of these five posts: by the end of this one you will hold the whole map at once; by the end of the series you will have seen where biases are actually made, how they travel — and what actually stands in their way.
Introduction — Where this journey started
This journey started somewhere between the autumn of 2024 and the early spring of 2025, when it was hard to open a news feed without being told two things at once: that AI was biased in its outputs, and that we were approaching the day it would wake up — consciousness, singularity, doomsday. The point, as the story went, where we can no longer understand what the machines are doing, because they have passed our own intellectual capacity.
And I kept stumbling over the same question: if we don't understand what consciousness is, how exactly would we recognise it when it appears in a machine? How do we plan to measure where the border to the singularity runs, when we haven't understood our own brain well enough to say what capacity we are even talking about? The honest answer seemed to be that we would know we had crossed the line only after we had crossed it. We still don't know enough about our own cognitive development to measure and judge — and yet there we were, judging.
The bias claims bothered me in a different way. As an AI enthusiast I was intrigued — but I also felt a growing urge to push back, because blaming AI for everything is itself a sign of the times: a way of escaping change, and escaping responsibility. We were projecting our own problems onto a technology we didn't understand — and, for the most part, still don't. Because here is the thing: a cognitive bias comes from a human, or a group of humans. Not from a synthetic counterpart. When a machine's output looks biased, what we are looking at is coloured content that people once created, reflected back at us. We blamed our own problem on the mirror.
So what is a cognitive bias, actually? When you meet them in social media and memes, you get the picture of a glitch — a fault in the reasoning, a bug you could patch if you just learned its name. But there is an empirical science behind them, and it says something quite different: biases are part of our pattern recognition — a protection, a defence mechanism for how we navigate reality. Against that,
"AI is full of biases" felt like a ridiculous claim: something I knew was false but could not yet prove. And that gap — between knowing and being able to show — is what set this whole thing off. I needed to go to the bottom of it: what the biases are, what actually triggers them, where they are created — when, and why.
I should say something about why I take on a quest like this at all, because it explains the spirit of everything that follows. I am, by nature, an intellectual omnivore — curiosity is the driver here, and what it wants is to find out how everything works together. But a quest like this only works if you carry a certain metacognitive humbleness into it: knowing that you don't know everything — knowing, some days, that you can't even see how much you don't know. That awareness of my own limits is not a burden. It is exactly what makes the work challenging, and honestly, what makes it fun. Because the reward comes every time a piece fits — the same quiet pleasure as laying a puzzle: you find the piece, then the big pieces start fitting together, and suddenly a part of the map appears that you had no clue about a moment before.
I want to be honest about where this exploration stands, because that matters for how you read it. Through this spring I ran regular check-ins on the research and news coming out of this field, and the progress is real but slow — a claim here, a finding there, seldom anything like a whole view. What follows in this series is built differently: the smaller building blocks rest on established, tested science, and many of them have been validated in this work along the way; the larger structure — how the blocks fit together into one system — is stated for what it is, a hypothesis built on those validated blocks. I would rather draw that line clearly than pretend it is not there.
And because the whole view is exactly what has been missing, this is a journey in five parts. It began with The Living Circuit — the machinery inside a single person, where values are built and biases are born. This post is the second: the ecosystem itself — ten machines, one mind, and how they hold together as one system. The third takes the machines apart: where biases are actually made, layer by layer, engine by engine. The fourth follows the movement: how a bias travels through the system as a signal — and how the journey of one claim actually ends. And the fifth closes the circle with the question everything else builds toward: what stands in the way — the protection, and the prediction that makes protection more than hope. The posts are big, and deliberately so — the subject does not survive being made small. At the end of each one we will step back onto the map, see where we stand, and where the road goes next.
And if you ask me now where it all finally lands — the most honest opening I can give you is the one this whole journey started from: I don't know. Let's find out.
A bias is made somewhere
In the piece that opened this journey — The Living Circuit — I made an argument I'll compress here, because everything in this series stands on it:
A cognitive bias is not an error the mind makes. It is a defence the mind mounts — what a motivational system does when it is protecting something it cares about, under pressure, while facing the world.
If that reframe is right, it has a consequence the textbook picture never faces: defences are mounted by machinery. Something does the defending. Something supplies the pressure. Something decides which comforting story is lying within reach when the pressure arrives.
The popular picture of bias — the alphabetical list of quirky mistakes, confirmation bias filed next to the halo effect — has nothing to say about any of that. It flattens every distortion into one list, as if they all happened in the same place, at the same speed, for the same reason. And that flattening loses exactly what matters. The pressure of a debt is not the pressure of a tribe. The pressure of a tribe is not the pressure of a trending number seen by a million strangers. And none of those is the pull of the body's own chemistry. Who applies the pressure? How fast does it move? How long does it hold? The list format cannot even ask those questions.
So here is the claim this whole post exists to unpack. The forces that make and move cognitive bias are organised into ten distinct layers — ten pieces of machinery, each with its own engine inside, its own tempo, its own way of handling what passes through it. And the framework's central claim is that these ten, together, are the complete production and distribution system for cognitive bias: where it is made, what amplifies it, what carries it, what locks it in, and where it lands.
Four words before we go on — the proper names, stated once so the metaphors stay on their leash:
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- Layer — the framework's formal unit: one distinct piece of machinery in the information ecosystem, with its own tempo and its own way of working on what passes through it. The layers are numbered L0–L9, and the number is each layer's permanent address.
- Engine — the framework's working term for what runs inside a layer, producing or reshaping what moves through it. Every layer has exactly one; no two are alike.
- Bias — the defence itself, and here is the boundary that organises everything: biases are made by human machinery, and only human machinery. Two layers make them — the person, and the groups people form.
- Primitive — what the other layers make and carry: not biases, but the parts, patterns and pressures that biases are made from and triggered by. The rest of the system does not put a bias in your head; it stocks primitives within your reach.
- Layer — the framework's formal unit: one distinct piece of machinery in the information ecosystem, with its own tempo and its own way of working on what passes through it. The layers are numbered L0–L9, and the number is each layer's permanent address.
A few of each, straight from the framework's register (a snapshot, August 2026), so the difference is concrete. Confirmation bias and loss aversion are biases — made inside a person's own loop. The bandwagon effect is a bias too — made on the group's seam, not in solitude. Doomscrolling and the filter bubble are primitives of the media machinery; the anchoring trick — the first number shaping every number after it — is a primitive of the economic machinery; jargon that gates who may even join a conversation is a primitive of the archive.
That is the whole vocabulary you need for this post. The next post opens the engines themselves; today we are walking the whole system at once.
Why layers at all?
Why carve the world into layers in the first place? Isn't this just adding boxes for the pleasure of drawing arrows between them?
It's a fair suspicion, so let me show you the case that convinced me the layers are real — that they are found, not invented. It concerns the difference between your tribe and your public: between the group of people you actually know, and the population of strangers you perform for online. For a long time I treated those as the same thing at two sizes — the social world, small and large. The research says no. At roughly the size where you can no longer personally know everyone — the neighbourhood of Dunbar's famous hundred-and-fifty — the machinery of influence itself changes kind. Below that line, influence is normative: people you know, expecting things of you, face to face. Above it, influence turns informational: counts about strangers — how many, how fast, trending where — with the headcount doing the persuading. Strong ties give way to weak ones. The fear changes from being excluded by your group to catastrophic reputation loss in front of an anonymous audience. And correction — the system's ability to fix its own mistakes — slows by orders of magnitude.
Our rumour already knows this difference, even if we don't. In the corridor it is normative machinery at work: a colleague you know, lowering her voice, expecting something of you — discretion, solidarity, a reaction. And there, a single sentence from someone who was in the room can still kill it. But the LinkedIn post has crossed the line. Nobody knows anybody; what persuades now is the count — the reactions, the reposts, what "everyone in the industry" is apparently saying — and no sentence reaches everyone who saw it. A misunderstanding you could talk out by the coffee machine now lives in a feed that never quite forgets.
Same people. Different machinery. The tribe recovers; the population remembers. That is not one layer at two sizes — it is two layers, and treating them as one produces real misreadings: a panic can look finished in the room while it is still quietly hardening at population scale.
This gives us the criterion for the whole map, and it's worth stating plainly: a layer earns its place by a phase transition, not by size. Different machinery, different tempo, different persistence — its own layer. Not "media is big" or "money matters", but: the thing that happens to a claim inside a newsroom is mechanically different from the thing that happens to it inside a family, a market, or a language. Ten such transitions survived the work. Ten layers.
Which raises the obvious question: what are they?
The ten, in three roles
Here is the picture to hold for everything that follows. Imagine a market — not a metaphorical "marketplace of ideas", but an actual arrangement of stalls and machinery — built around one mind. At the centre stands the person: you. Around you, nine other layers, and every one of them leaves something where you can pick it up. That is the shape of the whole ecosystem, and it sorts the ten machines into three roles: some create, some reshape, and some route, record and program. Let me walk you around.
The creators — where signals enter the world
Layer 1 — the individual layer (L1)
The machine at the centre — the person, the one The Living Circuit spent twenty thousand words inside. Its engine is a loop, and the loop's parts are worth holding even at this height:
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- a circle of needs — the raw wanting, given shape;
- a ranking — deciding what is reached for first;
- values — paid for by belonging;
- a face — shown outward;
- a reflection — coming back from the world;
- the groups — doing the feeding.
Biases are made inside this loop, defending the values — that much you may already know. What the ecosystem view adds is the layer's role among the ten: the consumer. Every other layer stocks something for this one. The person is where bias is born, and also where everything the other nine produce finally lands.
Layer 2 — the social layer (L2)
The tribe: family, friends, workplace, congregation — and yes, an online community can be a full group in every sense that matters. Here is the first strange engine: a group wants nothing. It has no appetite of its own — it runs entirely on its members' borrowed wanting. What it does have is a face: the group's identity, which must be kept attractive and intact, and the group makes its biases on exactly that seam — where its values become its public face. It is fast, and it forgets fast: tempo in days and weeks. Watch the rumour hit this machinery: the team chat does not just pass it along — it fits it to the face. In one team the claim turns into gallows humour, because that team's identity is being unshakeable; in another it becomes a quiet loyalty probe — you're not polishing your CV, are you? Same claim, tailored to whatever face the group is keeping intact. The group is the busiest supplier on the person's side of the market — belonging, answers, standing, all handed over the counter, values riding along as the price.
Layer 9 — the public layer (L9)
The population of strangers, where people appear as numbers: the headcount, the trending number, the silence that counts as agreement. This layer is not a second factory doing what the group does at a larger size — that is precisely the phase transition of part two. It is better understood as the stage: it takes the tribe's material and works it at population scale, in front of everyone, with occasions all its own. The carefully worded LinkedIn post from our Tuesday lives here now, performing for people who will never know the building. This layer is slow, and it holds: months to years. The digital crowd never quite disbands.
Layer 4 — the synthetic layer (L4)
The newest arrival — the machines that talk back: AI systems, recommendation engines, algorithmic feeds. This layer genuinely creates — its signals are new in the world; no human wrote this morning's feed in this order for you. But mark the boundary, because it is the hinge of this whole series: the synthetic layer generates signals, not biases in the person. The bias is still made by human machinery — yours — when the signal arrives. layer as it is built today — machinery with no needs of its own, nothing at stake, nothing to What makes this layer unlike every other creator is the absence of friction: it is always available, always patient, and nothing human ever interrupts it.
The reshapers — Nothing new is created, everything comes out changed
Layer 0 — the biology layer (L0)
Underneath everything, the oldest machinery of all — the body. Let me make it concrete, because "the body" can sound like an abstraction. This layer is your age, and everything it quietly resets about speed, stamina and appetite. It is the physiology you were born with: the reflexes, the chemistry, the sensitivity of your alarm systems — default settings that were dialled in before you had any say in the matter. In the ecosystem, this machinery has one role: the amplifier. The body does not deal in opinions; it deals in force. It filters what arrives and sets the default gains — how loudly each kind of pressure registers before any thinking starts. And it owns the one thing everything else in the ecosystem only borrows: the appetite itself, the raw wanting that every group, every platform and every institution points its machinery at. The body is upstream of force, not of meaning: it decides how hard a signal hits, never what the signal says.
Layer 3 — the media layer (L3)
Platforms, feeds, outlets, channels — the machinery of attention. Nothing original is made here; things pass through and come out louder, narrower, and re-labelled. From this layer's own register: doomscrolling, the filter bubble, the artificial scarcity of only two left — patterns of attention, not opinions. The layer works in sequences — not one message but the drumbeat of many, ordered, repeated, framed — and it works under an agenda that never shows at the input. Suppose our rumour escapes the building — a screenshot, an anonymous tip. What entered as twenty per cent, apparently comes out as "industry giant preparing sweeping cuts, sources say" — louder, narrower, re-labelled, and placed third in a sequence about economic anxiety that you did not order. You see the story; you do not see why this story, now, in this order. That invisible hand on the machinery matters, and we will come back to it.
Layer 7 — the economic layer (L7)
The least psychological-sounding layer, and one of the most underestimated — so let me say concretely what it is. It is the mortgage due on the first of every month, whatever else the month brought. The rent that takes half a paycheque before any choice gets made. The contract renewed — or not — every third month, so the future only ever arrives ninety days at a time. The debt that quietly decides which risks are thinkable at all. None of this supplies your mental furniture — no opinions, no stories. What the economic layer supplies is the situation: it shapes pressure in time. How fast it hits. How long it holds. Whether it ever lets go. Arrangements like these hold a person in place and then let the person's own machinery do the rest. If the media layer decides what a signal says and the biology layer decides how hard it hits, the economic layer decides how long you have to stand there while it does. And notice what that means for the rumour: with a year of savings between you and trouble, twenty per cent is a conversation topic; with a mortgage due on the first and nothing in reserve, the claim moves in — the economic layer decides whether you are ever allowed to put it down, and for some people the answer is not tonight, not this month, maybe not this year.
The control infrastructure — What can travel, what persists, what can be thought
Layer 8 — the cultural-linguistic layer (L8)
Language and culture together — the deepest of the three, and the one working as the ecosystem's operating system: vocabulary, worldview, and the ways of doing and saying that a culture deposits over generations. This layer decides what can be thought by deciding what can be said — and, just as powerfully, what is done without ever being said. Its defaults are loaded, not enforced: no wall stops you; the path is simply already laid. And it holds the ecosystem's strangest property: where it supplies no word, nothing is reached for. A thing your language cannot name is not forbidden to you — it is simply never sought.
Layer 5 — the institutional layer (L5)
Organisations as machinery: bureaucracies, companies, authorities, systems of measurement. Working as the ecosystem's router, this layer counts, replaces and distributes — and its signature move is the swap: the measure put where the thing was. You have met it. The grade standing where the learning was. The waiting-time target standing where the care was. The engagement score standing where the conversation was. Once swapped, the measure travels through the widest supply fan in the ecosystem — institutions feed more of the other layers than anything else on the floor. And our rumour has been carrying a swap from the start: twenty per cent is a number standing where colleagues' names and faces would be.
Layer 6 — the knowledge layer (L6)
Records, credentials, review, the whole apparatus of what officially counts as known. Working as the ecosystem's archive, it is a recorder that also edits: it gates what enters the record, and it weaves into the record a coherence the original sources never had. Then — and this is the part that should give you pause — it replays. What the archive holds re-enters the other engines years, sometimes generations, after the event. And what is deeply recorded defends itself by dependency: pull out a foundational piece and everything built on it trembles, so nobody pulls.
Ten machines. Three roles. One mind at the centre, and — one more thing, running under the floor, which we have already met: the appetite, owned by the body, borrowed by every layer above it. Hold that; it is about to matter.
What makes ten machines one system
A list of ten machines is not yet an ecosystem. What binds them? Four things, and each one changes how you read the world.
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- One consumer. Nine layers leave something a person can pick up — a cheap answer to hand, a good behind a wall, or the words themselves. And here is the correction this picture forces on the usual story: interaction in this ecosystem is stocking and reaching, not broadcasting. The layers do not inject anything into you. They stock the shelves; you reach. Every bias that lands, lands because a hand reached for something that had been left within reach. That is not a moral accusation — the reaching is done by machinery we have every reason to call human nature — but it relocates the event. The transaction happens at your end of the market.
- One current. The appetite lives in the body, and everything above borrows it. The person's engine sits on it. A group runs on it through its members. The media, institutional and synthetic layers — all of them point their machinery at a wanting that none of them owns. This is why the ecosystem coheres instead of being ten unrelated gadgets: a single current runs through the whole market, and it enters at the bottom.
- Interpenetration. The layers are distinct in machinery but entangled in material. Your beliefs turn inside the media machinery; your tribe's standing sits inside the economic grip; the institution's categories live inside your language. No layer contains only its own material — each one carries the others' cargo through its own moving parts. This is why you cannot fix anything by pointing at one layer: the thing you are pointing at is partly made of the other nine.
- The guards and the rings. Some of the machinery guards, and some of it remembers. The person carries a guard — awareness, the part of the loop whose job is seeing the loop. The group carries one too: vigilance — the same slot, opposite sign, a watch that protects the group's face and works against its members' clarity. And around several of the machines run rings. Some are held — a hand on the machinery: the media layer's agenda, the synthetic layer's business model. Some are deposited — laid down by use: the structural capital of institutions, the canon of the archive, the tradition of the culture. Nobody holds the deposited rings; nobody needs to. But they are not authorless in origin — they were laid down by human hands, pass by pass: every deposit was once somebody's workaround, somebody's habit, somebody's ruling. The hands are gone; the tracks remain; the machinery runs on them. The deposits are the ecosystem's memory — and its resistance.
And over all of it, one governing principle that I want to state carefully because it carries the ethics of the whole project: the layers are neutral. Harm is not a property of a layer — it is a property of a route. The same ten machines, the same three roles, describe a public-health campaign and a harassment campaign alike. The machinery does not know the difference. What differs is the path a signal takes, what falls into alignment along the way, and what gets switched off. Which brings us to the last thing this map has to show you: the system in motion.
The system in motion
Everything so far has been anatomy — the machines standing still. But the reason this map matters is what happens when a signal starts to move, and I want to sketch that here in principle, because the reader who has seen the whole once will recognise the parts when we return to them.
A signal is generated — by a person's engine, a group defending its face, a machine's feed, a trending count of strangers. The reshapers then work on it: the biology layer sets its force, the media layer sets its amplitude and its sequence, the economic layer sets its envelope in time — how hard it arrives, how long it is sustained, whether release is ever permitted. Most signals die somewhere along that path. But if one persists, the control infrastructure completes it, in a slow, specific order: language defines it as thinkable → institutions lock it into structure → the archive records it as truth.
And a signal that completes that route undergoes a change of state that I find genuinely chilling: it no longer needs its source. Nobody has to keep telling the story; the system now reproduces it. The word is in the vocabulary, the category is in the forms, the fact is in the record — and the record feeds back as tomorrow's criterion for what fits. That is how a claim outlives everyone who ever believed it firsthand.
Our rumour, for the record, is only a few stops in — a chat, a corridor, one carefully worded post. Whether it ever reaches a vocabulary, a form, a record — and what could interrupt it on the way — is later parts' territory, and I will not run ahead of it.
One more thing, and it is the single most practical sentence in this post. Across all ten layers, an active cascade has one consistent signature: the reflective register — synthesis, learning, release, reform — switches off. Not overwhelmed; switched off. Everywhere at once. Which quietly hands us the intervention principle this whole framework points toward: do not shout against the loud register. Re-activate the suppressed one.
How a cascade actually runs — its shapes, its speeds, what makes one ignite and another die — is the fourth part's territory, and what can be done about any of it is the fifth's. What I need you to take from this section is only the shape of the whole: signals are made, reshaped, and — if nothing interrupts — defined, locked, and recorded, until the system remembers them on its own.
The observatory
Let me land the one sentence this whole map compresses into, because it is the sentence that changes how the world reads: nothing in this ecosystem is injected into you — everything is stocked, and reached for. The layers cannot make you believe anything. They can only arrange what is within reach when your own machinery, under pressure, goes reaching — and they are very, very good at the arranging. Once you hold that sentence, the daily experience of feeds, headlines, prices and rumours stops being a story about what is being done to you and becomes a story about what is being left near you. Different story. Different questions. Different places to push back — which is exactly where this series is heading.
So what is this map for? Not for blame — part four should have dismantled that ambition. The layers are neutral; harm is a route, not a place. And not for verdicts on the people around you, either. The honest use of a map like this is closer to what an observatory does: all ten layers in view at once, including the ones a signal is not touching, because where a signal isn't is part of the picture. A mirror, never a verdict — the same discipline this whole project has tried to hold from the start.
And the map hands you three questions you could not ask from inside the old alphabetical list. Which machine is this coming through? — a colleague who knows you, a feed that doesn't, a form, a price? Is this my tribe or the numbers? — because the tribe can be talked with, and the numbers cannot. And who stocked this within my reach? — because everything you reach for was left somewhere first. You will not always get answers. But asking moves you from inside the machinery to in front of it, and that is a different place to stand — the same place you would stand in any market you walked into with money in your pocket, asking the ordinary, sane question of every shelf: who put this here?
Here is where we stand on the journey, then. The map is on the table: ten machines, three roles, one mind, one current. Somewhere out there, the boxes are still stacked against the glass, and the rumour is still moving — we will meet it again at every layer it touches. What the map cannot show from this height is the machinery itself — what actually turns, inside each layer, when a bias is made. That is the next part: we take the machines apart, one engine at a time, and it is where this whole expedition started for me. The origins of bias — where your biases are actually made.
And the question I'll leave open until then is the one the market has been holding all along: if the shelves are stocked by machinery, and the reaching is done by machinery — where, exactly, in this whole ecosystem, is the part that is you?
Disclaimer
This post is a personal exploration, and the views in it are my own. The framework it presents is a working synthesis: its smaller building blocks rest on established, tested science, and many have been validated in this work along the way; the larger structure — how the blocks fit together into one system — is a hypothesis built on those validated blocks, and I have tried to say throughout which is which.
The workplace rumour that runs through this series is invented — a teaching device, not a reported case. No real event or route is being charted.
This piece was made with heavy AI assistance, and I'd rather be transparent about exactly how. The underlying framework was built and stress-tested across many long working sessions in dialogue with Claude — including blind derivation runs, pre-registered checks, and failed predictions reported as failures. The writing was drafted with Claude from my material and direction, and edited by me. The voice and the argument are mine.
Sources & further reading
The machinery of bias — this essay is part two of five.
The full journey:
- The living circuit (part one)
- The ecosystem of cognitive bias (part two)
- The origins of bias (part three)
- The signal — how bias travels (part four)
- What stands in the way — the protection, and the prediction (part five)
- The ecosystem (concept map)
- The register (cognitive bias concept map)
- The cascade flow (concept map)
- The state (engine state concept map)
Standing on — the heritage this series gratefully builds from: the Cognitive Bias Codex — Buster Benson's grouping of the named biases and John Manoogian III's wheel visualisation — the best-known map of the territory this series widens.
On the tribe/population transition: Robin Dunbar on the ~150-person limit of personally maintained relationships; Deutsch & Gerard's classic distinction between normative and informational social influence; Mark Granovetter, "The strength of weak ties."
On the appetite: Kent Berridge & Terry Robinson's work on the wanting/liking distinction in the brain's reward machinery.
On institutions and their ceremonies: John Meyer & Brian Rowan, "Institutionalized organizations: formal structure as myth and ceremony."
THE STIMULUS EFFECT | Podcasts
The living circuit: How your values are built — and where your biases are really born
The origins of bias — Where your biases are actually made
The signal — How bias travels
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