Giants like Altavista, Google, Yandex took on a mission: gather all information that exists in the world, organize it, and make it universally available; provide people with a place where they can look at all this information and find anything they are looking for. [A,B,C]

Mission is complete. The bottomless ocean of information is washing people’s feet. Through its waters, people see a different picture of what knowledge is. Some (if not many) things that were learned and kept in one’s memory are now available by typing a couple of letters on a keyboard. It’s enough to ask a badly formulated question and get a ton of hyperlinks, behind one of which the answer is hidden.

Well, that was yesterday. Today we have AI. GPT Chat and his foster brothers answer questions coherently, without flushing out the internet garbage. People are, of course, running towards novel AI, putting a lot of pressure on its technological capabilities as well as on the challenges it presents to the concepts of authorship and identity. [D,E,F] It is no wonder that everyone is talking and writing essays about it. I won’t follow suit.

If I was to join this technological breakthrough, I would already be back in my R&D labs of ten years ago, where my prototypes were suffering for the lack of AI support. In the things that surface today, I see the echo of these prototypes.

But I won’t go back. Instead, I present a short play.

ACT ONE

ANDREAS is an ordinary librarian. He has a happy family, as ordinary as he himself: a wife, a son name BOB, and a dog named COOKIE. Bobby is five years old. He grows up quickly and discovers the world with eyes wide open, greedy for knowledge. Every day he has another ‘why’-s and ‘how’-s to ask his dad who knows everything.

His dad knows a lot indeed.

One day, Bob asks a question that his father was longing for. Bobby wonders why his dad knows so much, and how he can catch up. So, Bob gets to the library which is inconveniently located on the other side of the town. But that doesn’t stop him. Every day after school, Bobby rushes to the library and dives into books. He wants to become just like his father.

Bob grows up and learns different types of human love by practicing: he loves parents who love them back, know everything, and take care of him; loves Charlie the dog which knows nothing, and takes care of it. Eventually, Bob falls in love, then falls in love once again, and, while still at university, gets married.

He graduates magna cum laude and gets an ordinary office job. He has an ordinary happy family. The world belongs to him.

INTERMISSION

While Bob grows, the Internet is also growing, being of the same age. The Internet spreads the World Wide Web around the world and allow ‘search engine’ spiders to crawl it. The mission of those is ‘to gather all information in the world and make it available for everyone’.

Bob meets the Internet at his desk: they get acquainted via the web browser’s window. Bob searches the Internet for suppliers, customers, competitors; more and more he relies on the fact that there, on the Internet, ‘everything can be found’. He just needs to ask the right question.

The Internet search is dumb. It requires Bob to learn its language, a simplistic and rudimentary creole. Like a dog, it needs to be trained. Having raised Cookie, Bob understands it rather well.

ACT TWO

BOB is an ordinary office clerk. He has a happy family, as ordinary as he himself: a wife and a daughter named DAHLIA. Dahlia is five years old. She grows up quickly and has her own ‘why’-s and ‘how’-s every day. And a dad who seems to know everything.

Dad knows where to look. Remembering his own father, Bob answers all his daughter’s questions by searching the Internet. With trepidation, he awaits the day when Dahlia will ask him The Question.

The day arrives sooner than hoped, and Bob — much like his father — brings his child to his office. He shows her a computer and explains how to find answers: just ask your question, and the Internet Search will show you where to look. Dahlia is a little disappointed with what her father really knows, but only a little. She understands that the main thing to learn is how to ask.

Bob wants to give his daughter the very best. He doesn’t want her to travel across town to his office (and distract him), so, he buys a personal computer and wires the Internet home.

Soon, there is an addition to the family. Dahlia now has a younger brother, EUGENE. She is asked to care for him.

Dahlia grows up and learns different types of human love by practicing: she loves her parents who love her back and care about her despite not knowing much; loves her younger brother who eventually grows somewhat wiser, or at least different. Of course, Dahlia doesn’t like this development but hey, what can she do — Eugene is not a dog, after all.

Dahlia and her brother grow up and both graduate with high scores. Dahlia gets a computer science degree and Bob masters social studies. They find their life partners and have happy families. The world belongs to them.

INTERMISSION

While Dahlia grows, the Internet is also growing. Search engine companies have completed their mission: all information of the world is now online. If you try hard enough, you can and will find anything. You must try hard, though. The ocean of information is too deep.

The companies have their mission complete; what seems an achievement, becomes an existential threat to them. What should they now do with hundreds of thousands of the smartest people on Earth? They need a new mission.

It presents itself: ‘The Internet should give correct and concise answers right away, without the need to search’. The Internet should do more than just help people with their search. It should give answers, for real. The Internet must understand the language humans speak and respond in kind. Times of ‘search creole’ must end.

The Internet search (as was it called before) gets smarter. It is no longer a sort of a dog, not even a toddler. In some areas, the Internet is smarter than man.

ACT THREE

DAHLIA is an ordinary digital professional. She has a happy family, as ordinary as she herself: a husband and twins: GABRIEL and GIDEON.

Her brother, Eugene was less fortunate. A tragedy shattered his happy family. It took both Eugene’s and his wife’s lives. Only the son survived. His name is HARRY.

Dahlia takes her nephew in, but has no special love for him. Harry reminds her of her younger brother. So, Harry gets to live in a closet under the stairs.

Harry has questions, but there is no one to answer them. He must look for answers all by himself. He has no friends, so he befriends knowledge. He enters law school in absentia, faking his age, and passes the Bar.

There is no one to answer the questions that Gabriel and Gideon have, either. Dahlia goes missing at work, as does her husband. Luckily, the twins have Harry: a black sheep that is kept in a closet and ordered to run errands. Harry never becomes a full member of Dahlia’s happy family.

Gabriel, Gideon, and Harry grow up. Who will they become?

What will become of the twins that hardly saw their loving parents; the twins that used to rely on their black sheep cousin in every aspect? They don’t consider Harry a real boy.

Who will become of Harry? A boy that lived in a closet for all his life. A boy that knows of love like this: that even this family doesn't consider him equal, while at the same time they can’t do without him.

What will they become? To whom the world will belong?

CURTAIN DROP

Once, in a Buddhist monastery, a cat wandered in the meditation halls and distracted monks. So, each meditation time, that cat was tied to the hall’s door. Time passed, and now there is a specially groomed cat that must be tied to the door for a meditation to start.

It took monks several lifetimes to forget the reason why the cat was tied, but in the digital ecosystem time flies much faster. Metaphors that helped people understand what each thing was for are long gone.

Fifty years ago, every office clerk knew what ‘inbox’ is for. And it was helpful, to show that label in the electronic mail interfaces. Now it is just a label with no meaning. People must memorize it and recall not the experience but knowledge.

Do you still remember what ‘save’ icon meant? And why we use ‘chain link’ next to the URL links? Why we call ‘#’ an anchor? All those were experience-based metaphors that are long gone. They need learned knowledge and cognitive effort to be recalled.

Of Icons and Labels

The tradition of labelling buttons with texts and icons is not that old. It all started around XVIII century, when manufacturers started putting labels on tools they made. Labels at the time were needed to distinguish one knob from another, but not more than that.

Everything changes in the 1960s, when the lady Ms Production met the gentleman Mr Marketing. Two things happened roughly at the same time.

First, mass production led to mass market. One tool was produced to fit many markets in many countries. Thus, text labels became a problem — one can’t put all versions of the word ‘play’ next to a small button of a tape-machine. Pictograms — now known as icons — were born. They compacted a label into a symbol, quite often depicting the tool’s internals. The ‘play’ icon was a tape-machine record-head descending the tape. And the ‘stop’? The same record-head, this time ascending.

Second, more and more tools were produced for mass consumers. Not for professionals, who learned how to use their tools from fellow professionals. For laymen, regular people. Those had no idea what each knob was about. Their idea for ‘play’ was that the tape will start to roll, and the music will start to play.
Of course, designers felt the marketers’ need to educate. After all, the former was paid by the latter. Half a century past, we all use interface controls which were designed to educate us.

We Don’t Need No Education

Let’s think in contrary. How would we design a digital interface that won’t be needing no education?

Even more, how could we design an interface for a digital tool that is not based on previous experience with other tools? How can we throw away our dozens of years of digital experience?

How can we unlearn our preconceptions and build an interface based on pure perception? Especially if the interface is more complex than a doorknob.
The answer is... allegory.

折り紙, Origami

Origami literally means ‘folded paper’. Deemed one of the most ‘Japanese’ things ever, it originated in China. People sacrificed money to gods by burning it. As gold doesn’t burn well or (this is important) willingly, a paper solution was born. A paper-made golden ingot looks like a golden ingot but is in fact a piece of paper. And if the gods can be fooled, why can’t we?

Today’s origami is a form of art. A drawing made by folding. A symbol aimed for human imagination, but not as a pictogram, not as an ‘icon’.

Origami symbols are not ‘words’, they are poems. They convey rich feelings, themselves being just a poor piece of paper.

Here is an origami of a rabbit.

Here is a poem.

Sweet carrot’s crunched
By my little friend. My sleeves
Are suddenly wet.

The author of both wants to give us an emotion. Neither rabbit’s dimensions, nor its genus, nor even its colour or the texture of its fur.

A feeling.

All human people are capable of feelings.

How to Design with Allegory

The Allegory Paradigm, taken to extremes, stops us from using symbols borrowed from any tool that our users should have used before. At least, from digital tools.

We must stop borrowing each other’s UI controls.

Including text — in cases when it serves as a symbolic label, not as the message itself. This essay is a message, while the ‘followers’ in ‘25 followers’ next to it — is not. The notion of ‘followers’ is a convention, based on the learned concept of ‘following’.

Instead of asking the user to learn or guess what ‘follower’ means, we should create an impression of those ‘25 followers’ in a way that will give the user a feeling what it means for them. Why should they care about the number 25 at all?

Is twenty-five a lot?

Why do we care how many people there are? Of course, being alone is different from being in a small group of friends, and that is different from being in a crowd. Those are different feelings. And our goal here is to express this idea, in a poetic, sensual form that will pass the cognitive filters of our users and hit their minds directly.

Is there anyone important?

Why do we care which people we are with? Of course, being in a group of friends is different from being in a group of strangers; different from being locked in with your nemesis. Those are different feelings. And our goal stays the same.

We are designing then, for direct perception, not for preconception.

Designing for Virtual Reality

Virtual Reality gives us an opportunity to rethink and reconsider how we interact with digital products and with people in digital environments. Let’s not waste the opportunity.

VR products showcase a variety of interfaces that are somewhat similar to each other. They form several well-explored groups:

Meta UI: Heads-up-display interfaces that are placed between the user’s eyes and the world that the user is in. They only exist for the given user and neither other users nor the user’s avatar can see them.

Spatial UI: Interfaces that are put in the world and travel with user’s avatar, being at a fixed distance from the user. Again, nobody except the user can possibly see them.

Diegetic UI: Interfaces that belong to the world, being its natural part.

The latter group of interfaces is often praised for its potential for immersion and in some cases even called ‘no-UI’ to signify how far it has gone from what a conventional UI is.

However, even this group bases its existence on the same paradigm: each of the UI controls is presented as a metaphor of a tool, previously learned in another context.

The approach is reasonable and well-founded. When we meet a tool that looks like some another tool, we leverage our previous experience. If we see a pen, we remember another pen we used before. If we see a knob on a door — the infamous example of affordance — we remember another door that led us to this one. If we see a button, we click. I mean, we press it.

As designers, we are tempted to put an icon on the button to explain what it is for; an icon that will help our users to recall the actual object and to transfer the metaphor. Once we do so, we betray the affordance: we will turn back to the conventional paradigm of ‘labeling’.

Design for Tomorrow’s Yesterday

While the mainstream design paradigm is aimed for recognition of experiences previously learned, it mandates users to remember lots of things that don’t have deep meaning for them. It mandates designers to educate users with their designs. It mandates marketers to perpetuate patterns that are already learned.

To build a novel virtual reality interface, we should find concepts that appear directly in user’s eye, skipping the cognitive recollections and address the user’s perception and user’s senses.

We should build our interfaces on allegory, and to do so, we should discover deeper meaning of the things for which we build the UI.

We should design things as they are, not as they are for, today. Because the today’s ‘for’ will pass, but the things’ ‘are’ will stay.

How refreshing
The whimmy of a packhorse
Unloaded of everything!
— Shigematsu Sōiku

Scale-Free Networks

At the beginning of this century, scale-free networks (or graphs) raised a lot of noise in the circles that none of us belong to. These networks have many amazing properties; I’ll be looking at the most important of these.

Those networks and graphs are everywhere. With a microscope, one find them in protein interactions; without one — in a heap of broccoli at a market stall. These graphs are in our phone books, in social networks; they are deeply embedded in the network of transport and in the architecture of modern computers. Scale-free graphs describe well how the Internet works and how everything built on top of it works.

What do I mean by ‘scale-free network’? It all started with D.S. Price who studied the citation graph in scientific papers: ‘who’ mentions ‘whom’ in a never-ending chain of white papers about chains of white supremacy. Mr. Price established that the number of mentions is distributed according to the Pareto law (or ‘power law’). That explains perfectly why the citation network is liberated of scales (it is so obvious and self-evident, that even I didn’t get it. So, I won’t go in details here).

It wasn’t Price, though, who came up with the idea with the name. This is common among inventors: one person discovers a thing, and it gets named by another. (Who came up with the Bezier curves first? Hint: not Bezier).

There was a Hungarian-American (yet Romanian by birth) mathematician by the name of Albert-László Barabashi. He had an idea, novel at the time, to replicate Price’s work in the context of the World Wide Web: take blog posts instead of whitepapers and fashion bloggers instead of academics.

The Barabashi’s ‘apple’ might have given birth to the Google ‘apple tree’ and then to a billion-dollar advertising business, but the mathematician was interested in something else. They all are, aren’t they?

He was interested in the properties of these ‘scale-free networks’ and in the reasons for these properties to emerge.

While Barabashi was busy with the puzzle of the ‘scale-free networks’ and their properties, the business world was having a bash over a wide class of the systems that fell into the definition of ‘scale-free’.

There were a plenty of those: biological, sociological, technological. If there is a word ending in ‘-ical’, there are scale-free graphs in it.

Everyone around was talking about scale-free networks, and quite soon some went from talking right into doing: they started to design such networks, measure their properties and optimise.

One of the greatest discoveries about these networks is that they have very fast signal propagation. In such a network, the distance between two nodes is small.

Highly convenient property for a travelling salesman. For a transport network designer, it can help people to save on gasoline. Designer of microchips? Save the industry on conductive materials. IT department architect? Save money on routers and cables. Social networks are F-A-B for marketing. Yet, let’s not get ahead of ourselves.

Several years have passed and the critics have appeared. Some scientists have questioned whether scale-free networks are ubiquitous. Some even claimed they can’t be found in real world at all.

A heated discussion flared up. As it usually happens with heated discussions, everyone turned out to be a mathematician.

Barabashi himself took part in the heat. All the provided real world examples, so he said, were full of features for which the generalized model of scale-free networks didn’t account.

Well, almost all the examples. One of the varieties of real-world networks still fit well into the model. These are networks created by humans. Roads, computers, everything digital. And social networks. More precisely, some of those.

The Internet Is a Big Village of Skyscrapers

Everything that happens on the Internet is very well described by the power law and scale-free network models. Conway’s law provides an explanation: organizations design systems that mirror their own communication structure. As one might say, if a carpenter from Liverpool builds a shed, it’ll have a roof with a Scouse ascent.

We created computers based on microchips and integrated boards — all these components have the ‘scale-free properties’ we coveted. Then we connected these computers into a network, also of a ‘scale-free’ kind — to optimise throughput.

Immediately, life sprouted from nothing in this network — just like fleas on an alley cat. The emergent World Wide Web, or just ‘The Web’, was quickly dubbed a ‘global village’. I can still remember these times. But it was only recently that I realized how far from the truth this turned out to be. Almost in Orwellian way.

We live in an environment enriched and powered by Internet-connected devices. In turn, our habitat — this digitally-enhanced Earth we created — creates us. We are no longer a subject of Conway’s law, but an object of it.

It’s no good. Every rotation of the digitalised planet makes us less and less human. Now, it is time to talk about how it all happened.

Brave (Small) World

Let's start at the beginning. Every quest begins in a village, which is a small world where anyone knows everyone. Not six handshakes are needed, not even three, to connect any two of the village drunkards at the only tavern there is.

We study this social network — not ‘Facebook’, but a ‘Tavern 2.0’ where everyone shakes hands with each patron coming in. Then we walk by another hundred or thousand of similar villages with similar taverns. We walk until we see a few patterns emerge.

Such social networks are called ‘small worlds’ and have some similarities to scale-free networks. Yet they have differences, and those differences are all that matter.

What Are the Properties of Small World Networks?

• The distance between the nodes is small (just like with scale-free networks).
• The main supporting structure is ‘hubs’. In ‘small worlds’, there are many small clusters: tightly connected cliques that are then interconnected by a small number of links (scale-free networks don’t work like that!).
• ‘Small worlds’ are highly assortative.

Assortativity is like this: people tend to make connections with their own kind. Birds of the feather make a movie together. Rich men have rich man’s clubs. To this comparison, we will return a tad later. Now, it is time to answer the question we haven’t even asked ourselves yet.

The Two-Phase Evolution

How complexly organized systems are born from the soup of random connections? How does social order emerge from social chaos? With ants, it is achieved simply: just feed them barley. With people it is a bit different.

Once, someone offered me a witty explanation: music festivals. Who that someone was, I can’t recall; I was at a festival.

Each village lives its own life: everyone gets to know each other; people communicate and establish close and long-term ties. They visit the ‘Tavern 2.0’ social network and tweet away their food afterwards.

Once a year, an event happens to which the inhabitants of several villages come together. Not all of them, but some. Usually, the most active and the most attractive. There they listen to music for three days, covered by rain and mushrooms. They make connections alright, but these are much less close than the connections within their own village.

There are two phases in the life of such a society: the strengthening of local ties and the creation of short-lived ties with distanced peers. One can call them ‘local’ and ‘global’ phases which establish permanent and temporary connections respectively. While global phase is a period of enrichment, the local one becomes the time to digest.

These phases alternate and so, according to the researchers, the social structure of ‘small worlds’ emerge. There were a lot of good things going on within this small-world-branded society. Festivals, at the very least.

A People, Liberated

The formerly strong boundary between ‘local’ and ‘global’ worlds is now gone. Anyone can meet a person from the other side of the world and send them an aubergine emoji. The Internet has done a great job of liberating people from their ‘locality’.

The ideologists of this liberation say, ‘now one can choose for oneself what phase they are in’. The phone in the pocket enables a person to switch between ‘local’ and ‘global’ phases every given second.

The Internet is always with us now. The tight circle of 100,500 contacts on Instagram, Facebook, and Tiktok is always vibrating in the pocket.

Social networks have gone from ‘six handshakes’ to hundreds, then thousands and hundreds of thousands of followers and followees. People relationships began to take the form of the environment they have to exist. Social media are turning our society into a scale-free network.

In a scale-free network, the ‘two-phase evolution’ doesn’t have a place to happen. Once the locality restrictions are removed, the phases cease to change, and the network of small worlds coverts into a scale-free one.

Sometimes, scale-free networks are called ‘ultra-small worlds’. Isn’t being ‘ultra-small’ even better than just ‘small’? Let’s find out by comparing ‘scale-free’ with ‘small world’.

Scale-Free Networks vs. Small Worlds

Those pixels on your screens don’t come for free, so I’ll introduce a notation to save us some screen space and electricity:

• C - clustering coefficient (how densely the nodes are interconnected)
• L - average path length (average distance between nodes)

Here's how these coefficients look for different types of networks:

• Ordered network: C+, L+ (strong clustering, long path)
• Random network: C–, L+ (no clusters, long path)
• Small world: C+, L– (many clusters, short path)
• Scale-free network: C–, L–– (super-connectors, very short path)

Here is what the ‘ultra-small’ means: the paths are shorter, and the clustering is sparser. No doubt, short paths are great — as we already observed. But what about clustering?

The scale-free hubs are called ‘super-connectors’. They help the signal to spread quickly amongst the networks. Once it reaches just a couple of such super-connected hubs, the world gets a pocket epidemic.

Super-connectors play the king of the hill: each super-hub has its own super-super-hub to which it is a mere pleb. Small worlds are organised in a different way. Instead of the pyramids of hierarchy, ‘clubs’ are formed. Surely, those clubs are still layered — there are clubs for ‘rich’ and clubs for ‘poor’. But even the poor have friends.

In a scale-free network, the highest probability is that a person only has one connection — the upward connection to their super-hub. In a scale-free networks a random person is — most probably — a loser. While in a small-world network the same loser has a company of five to seven other losers just like them. That is, each of them is a little less of a loser. Shouldn’t it be considered a win?

What Happens after Shizit Hits the Fans

While it seems that everyone smart is interested in AI, some are still stuck with animals and their social networks. Not only with Facebook, but also with those which other animals form. The scientists suspected the structure of these networks emerged due to natural selection, evolution, and other so-called ‘Darwinistic nonsense’ which is not nonsense at all. There should be some sort of connection at least.

And there is.

Firstly, ‘small world’ networks have high clustering. It dampens the natural selection process: those who live together limit each other’s appetites.

Many ‘neutral mutations’ appear, which are equally inefficient from the point of view of natural selection. What it really means, each of us receives an individuality.

Small world network takes care of individuality. From humanistic perspective, it is an excellent argument in favour. 1:0, small worlds team is in the lead.

Secondly, ‘scale-free’ networks have super-connector hubs. They help the mutations to spread rapidly. These super-connectors do some random sampling of everything that comes to them and post the summary on Tiktok. Millions of potential memes result in one that skyrockets.

This is where the theory of neutral evolution comes to mind. When the natural selection does not occur, then evolution happens by genetic drift over neutral mutations — washing out some of them. In our world, natural selection is not really a huge factor, despite all the quarrels.

Scale-free networks favour less variety.

Small world network requires its members to invest in relationships. While in the world of Tinders and Tiktoks, things swing the other way.

In a scale-free network, relationships between members deteriorate. From the humanistic perspective, 2:0 for small worlds.

Artificial and Natural

There are people in academia who doubt the supremacy of the scale-free networks; those who don’t, keep the disclaimer — to build an adequate network model, one must know the nature of the source.

Real world always introduces imperfections, limitations, and restrictions. As we perhaps know from the above, it is exactly the limitations and restrictions that allow for ‘two-phase evolution’ to emerge. In the real world as in the nature.

But not in the systems we ourselves design with a purpose in mind. We want to optimise performance: faster signal spreading, less pathways. In those systems, we don’t need the helping hand of evolution. We are quite better off without it. We are gods of order.

For our single-minded purpose, scale-free fits the best. Signal is transmitted rapidly and with low overhead. We make ourselves part of it: with the help of internets, we transmit signals — memes! — quite rapidly.

In such networks, it is the ‘viruses’ who benefit the most: the novel coronavirus, the dubstep cat, the fake news.

Human society is not just a scale-free network. It is a part of an even greater one. The network of everything digital: it starts with semiconductors, then go up to microchips, devices, operating systems, apps. Then there are we. And up above — who is the digital super-connector to us? Google, Facebook, the so-called ‘megacorp’.

The super-connectors in this network need us, humans, to connect the layer of digital hardware with the layer of digital products and services.

The Megamachine

People, software, hardware, corporations — it is one single Mega-machine now. While its consciousness is dormant, it has only one task: to survive. The mega machine of which we are only a part wants to continue in the world.

To survive, the machine needs someone to replace its parts. Someone who changes microchips, charges batteries, pulls wires, makes new people and new digital products.

Thus, the machine itself developed a way to keep people locked inside. This way, people are indoctrinated in young age to become willful slaves who salivate at just a sight of a Kardashian’s ice bucket challenge. The machine (which we are a part of) learned to produce ‘digital content’.

The digital content is optimised to spread rapidly across the indoctrinated population. The quality of such content doesn’t matter, really. The only quality that matters is the volume of saliva it induces. That’s not a bar too high.

Every day, this bar is surpassed by hundreds of thousands ‘digital content items’: posts, videos, instagrams, tiktoks. That lucky that reaches the super-connectors first, gets to spread across the world.

What is happening in the super-connector world? Do they have their ‘rich man’s club’? Or do the play in the king of the hill? How many plausible search engines we have? How many social networks — given Facebook, Whatsapp, and Instagram is one? Winner takes it all.

What Should We Do?

So, the humanity tamed the scale-free network to serve our need for fast computing, fast delivery, fast communication. And we made it. Everything is fast now.

In return, we are now part of it. We built ourselves quite some scale-free slaves, and now they are ascended. They are making slaves out of us.

The bottom part of the scale-free network is made of silicon, the top one — of self-organising digital software. We are in the middle, the connecting tissue.

It is not Alphabet Co. at the top, but Google itself: a mega-machine of datacentres, cloud virtual machines, AI training farms, Android phones. It is not Meta Co., but a mega-machine built of Facebook, Whatsapp, Instagram, Cambridge Analytics, Oculus Quest.

Thankfully, not all is lost. Scale-free networks can ‘degrade’ back to small worlds, if limited wisely. Yet more restrictions mean less freedom. Will we return to the world that was too tight to breath? Or will we ascend?

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