Life, the Universe and Everything (4)

This is the fourth in a series of essays exploring a chain of questions about complexity, life, consciousness, intelligence, and ethics. Together, they form a rough map of the journey, hopefully with not too many imaginary dragons along the way.

In the previous essay, we moved from life that responds, to systems that bind the world, to experience that may eventually feel like something. We distinguished responsiveness from consciousness, and consciousness from sentience. The next question is agency: how information about the world, and in richer cases experience of it, comes to guide action.

An agent is a system that uses information to guide action in relation to its own condition, its surroundings, and possible future states. At its thinnest, agency is self-relevant action. A living system acts in ways tied to its own maintenance. The world is no longer just happening to the system. It is being used by the system.

Agency becomes richer when action becomes flexible. The system learns from what happened before, adjusts to present conditions, and behaves differently when circumstances change. A conscious being may have experience without much abstract reasoning. A non-conscious system may perform difficult calculations without anyone being home inside. Intelligence, in the sense we are considering here, is the capacity to use information to adapt action to changing conditions. It is agency made flexible.

The intelligent agent does not encounter the world as a neutral catalogue of facts, but as a world of relevance: danger, shelter, food, obstacle, companion. Things matter because they open or close possibilities for action. The world becomes not only what exists, but what can be done with what exists.

To act intelligently, a system must allow possible futures to influence present action. It does not need language or abstract thought for this, but it does need some way to connect action with consequence. The future enters the present as expectation.

Memory gives agency depth, because the past can become part of present action. Attention gives agency focus, because no system can use everything the world offers at once. Learning gives agency flexibility, because the world has the inconsiderate habit of changing.

More complex forms of agency often involve some kind of self-model. This means that the system tracks itself as the thing acting: its condition, limits, capacities, and possible actions. The self is a practical structure that helps an organism coordinate perception, memory, action, and consequence around its own continued existence. A simple organism may have only a minimal boundary between inside and outside, but a more complex animal may have body awareness, memory, expectation, and social recognition. In humans, the self becomes elaborate enough to include identity, ambition, shame, and hope.

A richer self-model can deepen agency. A being that models itself as the one acting can compare possible actions and select among them. At greater levels of complexity, an agent can also evaluate some of its own habits and, through reflection and practice, alter which responses become more likely in the future. This does not require us to solve the ancient problem of free will. For the cases we are considering, flexible choice among possible actions is enough. For now, we can simply say that intelligent agency involves flexible action guided by memory, prediction, and self-relevance.

This naturalistic account also helps explain why intelligence takes many forms. Different environments reward different capacities. Predators, prey, tool-users, and social animals all face different problems. Intelligence is not a single ladder. It is always intelligence for something, somewhere, under particular pressures.

Human intelligence is not detached from this broader pattern. We are agents with memory, prediction, self-models, and flexible action. Our particular kind of intelligence was also shaped by social life. We became human among other humans, and other agents are among the most complicated things any mind can encounter.

A social world is made of intentions, threats, promises, loyalties, and expectations. To live among agents, a mind must model not only what things are, but what others may know, want, remember, or do. This may be one of the great engines of intelligence. A solitary practical problem can be difficult, but dealing with another flexible mind is a challenge on a whole new level.

And perhaps here we can see the first outline of culture. Once agents communicate, imitate, teach, and remember together, intelligence begins to escape the limits of the individual. Knowledge can accumulate. Tools can improve. Stories can preserve experience beyond a single lifetime. Minds become unbound from time and can begin to shape other minds. But we’ll leave that for later.

For now, the important threshold is agency. Responsiveness means that a system is affected by conditions. Life uses information to maintain itself. Agency is that self-relevant regulation expressed through action. World-binding integrates information into a perspective. Where experience exists, it can further shape action. Intelligence develops when action becomes flexible, predictive, and adaptive.

The ethical picture also becomes deeper now. A sentient being can suffer, but an agent can also be confined, manipulated, deceived, or stripped of meaningful possibilities. Harm is not only pain. For more complex agents, harm can also be the narrowing of a life.

This is why practical freedom is important, though we are not yet arguing ethics. Practical freedom is the space in which agency can operate. Greater agency creates additional ways in which a being can be harmed when its possibilities are narrowed. Of course not all agents, be they biological or artificial, are morally identical. But once agency exists, we must also consider what kinds of lives beings are capable of pursuing, and what it means to prevent them from doing so.

When we are specifically thinking about an artificial system, it may already process information, select actions, learn from feedback, and operate in complex environments. That does not automatically prove consciousness or sentience, nor does it by itself confer moral status. But if an artificial system were to bind information into experience, develop memory, model itself as the agent of its own actions, form preferences, and suffer from the frustration or destruction of its possibilities, then dismissing it merely because it is artificial would become harder to defend. The substrate, once again, is not the point. It is the organization that matters.

So the chain has moved one more link. Matter may become organized complexity. Organized complexity may become life. Life may bind the world. World-binding may become experience. Experience may guide action. Flexible action, shaped by memory and prediction, is the beginning of intelligence. And as we have seen here, intelligence does not always remain trapped inside individual beings. It can disperse. Once agents communicate, teach, imitate, and build shared worlds, something new happens. Intelligence becomes collective. Which brings us to culture.

Life, the Universe, and Everything (3)

 

Part 3: World-Binding

This is the third in a series of essays exploring a chain of questions about complexity, life, consciousness, intelligence, and ethics. Together, they form a rough map of the journey, hopefully with not too many imaginary dragons along the way.

At the end of the previous essay, we proposed that life can be understood as organized complexity that maintains itself through time. It processes energy, preserves information, responds to local conditions, and belongs to lineages shaped by variation, inheritance, and selection. A bacterium moving toward nutrients and away from toxins is already using information from the world in ways tied to its own continuation.

But would it be appropriate to call this awareness?

We should be careful here, because words like responsiveness, awareness, sentience, consciousness, and self-consciousness are often thrown into the same conceptual drawer. At the simplest level, we are considering whether and how a system can respond to the world. Response, by itself, does not imply intention, life, experience, or consciousness.

A living system responds in ways tied to its own maintenance. A bacterium swims along a chemical gradient, and a plant bends toward light. Cells react to chemical signals, temperature, pressure, acidity, and other local conditions. These are not conscious decisions, but they are not random drift either. The organism uses differences in the world to regulate its own activity. Still, it would be too quick to call this awareness in the usual sense.

For these simple systems, the world becomes relevant, but not yet meaningful in the conscious sense. Some conditions help the organism persist, others threaten it, and the organism uses information about those differences to maintain itself. There is no need to invoke thought or feeling. The simple point here is that the surrounding world contains differences that matter to the system’s own continuation.

This is already beyond ordinary physical reaction, but it is not experience yet.

A nervous system is one way of binding information into a coordinated relation between a system and its world. It links what is happening outside with what is happening inside. It relates present signals to memory, possible action, and internal condition. This is the more general idea of world-binding.

World-binding is the integration of information across time into some kind of organized perspective. A system capable of experience, whatever it is made of, would need at least some way to bind information into a world from within.

On Earth, nervous systems are the clearest known implementation of this. But they may not be the only possible one in principle. A distributed alien organism might bind information through chemical gradients, electrical fields, pressure waves, or some other physical medium we have not yet imagined. A vast cloud-like intelligence might integrate information across enormous distances and think at a pace that would make us mistake it for weather. A fungal or colonial system, if sufficiently integrated, might not have one central brain, but something slower, looser, and more distributed. Even an artificial agent might bind memory, perception, goals, and action through complex non-biological architecture.

The material is not the essence; it is the organization that matters. The important question is whether information is merely being processed, or whether it is being integrated into something that has an inner side.

This brings us a step closer to consciousness and sentience.

Consciousness, in the sense used here, means integrated experience. There is something “it is like” for the system, however simple, strange, slow, distributed, or unlike us that experience may be. Sentience means valenced experience. Some states are not merely experienced, but experienced as better or worse from within.

Of course, these concepts are not perfectly separate boxes. They are more like neighbouring colours in a spectrum. We use different words because we need useful handles, not because nature implies any sharp borders here.

A conscious system, at least in principle, might experience the world in a neutral way: relations, changes, structures, patterns, perhaps something like pure observation. Whether such neutrality could remain stable over time is another question. Once memory accumulates, once some states recur, once some patterns are preserved and others disrupted, preferences may begin to emerge. Perhaps valence grows naturally wherever experience becomes historical. We should leave room for forms of mind that are not built around mammalian emotion.

But in the living animals we understand best, from studying how life manifests itself on this planet, experience is deeply valenced. Pain, pleasure, distress, and comfort are states that matter from within. Harm becomes more than damage. Damaging life is not morally empty simply because we cannot establish whether a particular living system feels pain. Within the framework we are building, life already has value as rare organized complexity, as history-bearing chemistry, and as part of the very few known instances of living fabric in the universe. Sentience introduces yet another kind of concern.

Each of us knows personal experience directly in our own case. We do not infer pain when we are in pain, nor do we infer the warmth of sunlight or the taste of coffee. Experience is the given thing. The problem is that we can only infer it in others, and so we look for signs. We look for integration, memory, learning, flexible action, internal relevance, attention, self-regulation, and the capacity to bring many signals together into one ongoing process. In animals, we also look at nervous systems, behaviour, avoidance, recovery, play, fear, social bonds, and the whole pattern of life. Each of these signs is an indication, but taken together, they form a compelling case for something extraordinary happening.

Plants and fungi, although quite far removed from our own mammalian experience, are also biologically responsive in rich and fascinating ways. They sense, signal, repair, defend, grow, exchange, and adapt. Some of this behaviour is astonishingly sophisticated, even though we cannot say whether they “feel” anything. In any case, there is no need to smuggle experience into the story before the evidence requires it, and complex responsiveness is already impressive enough.

Many animals, however, almost certainly cross into sentience. Mammals and birds give us strong evidence. Other forms of life may belong somewhere along that evidence gradient too. Octopuses are especially inconvenient for anyone who wants a tidy order of mind. These are highly intelligent creatures, curious, flexible, and radically unlike us. Nature, even on one planet, has tried more than one way of making an inner world. So we should be epistemically humble when we consider the possibilities.

It also means that we should be careful not to define consciousness by familiarity alone. On Earth, nervous systems are the clearest known path toward sentience and consciousness. But the deeper issue here is not whether a system is made of neurons, carbon, water, silicon, or anything else familiar. What concerns us is whether information is organized in such a way that there is a point of view from within. Any system, biological or artificial, would need some way to bind information into such a point of view before we could responsibly speak of experience.

Let’s try to summarize all of this. Responsiveness is the broadest layer: systems are affected by ambient conditions. A living system goes further, using information from the world to regulate itself. World-binding begins when information from different sources is integrated across time into some kind of organized perspective. Consciousness, in the sense used here, means that there is something it is like for that system, however simple, strange, slow, or distributed that experience may be. Sentience adds valence: some experiences are not neutral, but better or worse from within. And when experience begins to fold back on itself repeatedly, when the system models itself consistently as the one having the experience, then we can start talking about self-consciousness. That ushers in memory, self-other distinction, social identity, anticipation, regret, pride, shame, mortality, and the whole magnificent nuisance of being a self.

For now, the important thing to take away is the move from life that responds, to systems that bind the world, to experience that may eventually feel like something. This is where ethical questions begin to deepen, though we should leave the full argument for later. That does not make all sentient beings morally identical. A shrimp, a cat, a whale, and a human do not have the same memory capacity, social depth, emotional range, or possibilities of flourishing. But, whatever the case, once sentience enters the picture, it becomes clear that moral concern can no longer be restricted only to creatures that resemble us.

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Further reading

Daniel Dennett’s Consciousness Explained for the idea that consciousness need not be a single inner theatre, but may arise from distributed processes competing, revising, and becoming available across the system; Sam Harris’ Waking Up for the distinction between consciousness and the self, and for approaching experience directly without importing religion; Max Tegmark’s Life 3.0 for thinking about consciousness, information, artificial minds, and the possibility that substrate is not the essence. 

Related lighter and fun fiction

Fred Hoyle’s The Black Cloud imagines intelligence in a form so unlike animal life that humans almost fail to recognize it; Stanisław Lem’s Solaris explores the difficulty of understanding a vast alien mind that does not fit human categories; Philip K. Dick’s Do Androids Dream of Electric Sheep? is the natural companion for thinking about artificial beings, empathy, experience, and moral recognition.

Life, the Universe and Everything (Part 2)

Part 2

This is the second in a series of essays exploring a chain of questions about complexity, life, consciousness, intelligence, and ethics. Together, they form a rough map of the journey, hopefully with not too many imaginary dragons along the way.

In the last essay, we argued that complexity is fundamental, and that it compounds naturally. Simple systems combine into more complicated structures, and those structures interact with other structures. Some arrangements vanish almost immediately. Others persist, because the properties of their parts make some patterns more likely than others. Ordered complexity does not require intention. It can arise naturally because atoms have specific properties, molecules take specific shapes, and local environments constrain what can happen.

If ordered complexity can arise naturally, then life may perhaps be understood as a later threshold in the same story. Even when the necessary conditions are there, the transition to life may be difficult and possibly quite rare. But still, it is a threshold inside nature, grounded in physics and chemistry.

Nature has had billions of years to explore these possibilities, but we have not yet demonstrated in controlled laboratory conditions exactly how non-living chemistry can give rise to life. What experiments have shown is that many of the ingredients associated with life can arise through natural processes. Amino acids and organic molecules, as well as sugars, fatty acids, nucleobases, and other useful building blocks, can appear under plausible conditions. We also know that some of these materials have also been found in meteorites and interstellar environments, so we know that the raw materials of life are not something completely exotic.

The laws of physics and chemistry, as far as we can tell, apply throughout the universe. Reactions between chemical elements, when subjected to similar conditions, follow the same set of rules everywhere we can test. Stars forge heavier elements inside their cores and stellar winds and supernovae distribute them in the surrounding space. Planets, moons, comets, asteroids, ice, dust, form during the same star-formation processes and provide the many environments in which chemistry can unfold.

Every living system must process energy in some form, because maintaining order requires work. Stars hosting planetary systems provide these planets with usable energy for billions of years. But direct sunlight is not the only possible source of energy that life can tap. Hydrothermal vents, tidal heating, radioactive decay, and chemical gradients may also provide usable energy in the right environments.

So if life requires ordered chemistry, usable energy, and suitable environments, then it would be reasonable to assume that the Earth is probably not unique in satisfying the basic conditions. The pertinent question is then how often do those ingredients arrange themselves into systems that preserve and reproduce their own organization? Carbon and water seem to be extremely important here.

Life, at least on Earth, and possibly elsewhere, is built on complicated carbon scaffolding and uses water as its solvent. That does not prove that all life everywhere must do the same, but it gives us a sober starting point, because carbon is extremely flexible chemically. It forms strong bonds with many atoms, including with itself, and can form long chains, rings, branches, and very large molecules that are stable enough to persist while remaining active enough to participate in complex chemistry. Carbon is so fundamentally important to life as we know it that it even has its own branch of chemistry, organic chemistry.

Silicon is sometimes proposed as an alternative because it sits below carbon in the periodic table and shares some bonding behaviour. The problem is that silicon is not nearly as chemically flexible as carbon. In the presence of oxygen, it tends to form silicon dioxide, which is extremely stable, and can form various minerals and quartz, which is great if one wants nice rocks, but it is far less promising if one wants flexible molecular machinery. But there will be more to say about silicon later. For now, the important things to take away here, are that there is far more Carbon than Silicon in the Universe and that, when it comes to forming complex scaffolding structures, Carbon beats every other element, including Silicon, hands down.

Biologists also insist on the role of liquid water, as a powerful solvent, which allows molecules to dissolve, move, meet, react, separate, fold, and recombine. Water can remain liquid across a specific range of conditions and one of its very useful properties is that it expands when it freezes. This means that when an ice layer forms, it can insulate and preserve liquid water below it.

There may be other solvents that can perform similar roles. Methane is discussed in relation to very cold worlds such as Titan, but colder chemistry tends to be slower, and we have not yet found any life that does not rely on carbon and water. So, for now, carbon and water are the best game in town. They are simply extremely good at the job.

Still, a chemical soup of complex structures, however promising, remains a soup until some deeper organization arises. The crucial shift comes when chemistry begins to preserve structure through time. A living system carries something forward: it maintains a boundary, stores information, regulates internal processes and uses energy to repair and rebuild. Its variations become exposed to selection, with earlier arrangements influencing later arrangements. Some patterns make successor patterns more likely, and some variants persist better than others under local conditions. The system becomes a lineage.

Schrödinger’s old question, “What is life?” helped move the discussion away from vague appeals to a mysterious life force and toward physics, chemistry, order, and information.

Once stored information enters the loop, chemistry can preserve instructions that influence future structure.

Whatever awkward boundary cases exist, the cell, at least here on Earth, is the first clear unit where all the relevant processes come together. It has a boundary and can process energy. It stores information and uses it to build and repair itself. It maintains internal conditions and can respond to its environment. And it can reproduce, belonging to a lineage shaped by variation and selection. The cell is a tiny chemical reactor with “memory”.

Once reproduction, variation, and inheritance exist, evolution enters the story. Evolution explores what is possible under local conditions. Sometimes lineages gradually drift and sometimes they remain stable for very long periods. Life evolves somewhere, under particular conditions, with particular materials and pressures. The laws of biology are constrained by the local environment.

Changes in the local conditions, or available materials, affect the possible forms that life can take. Life adapts to environments, but over time it can also alter them. Oxygen in the Earth’s atmosphere is largely a biological product, and its soil is full of life. Coral reefs are byproducts of life, and living forests shape local climates. Ecosystems become networks through which energy, matter, and information move. In that sense, life does not simply evolve within an environment, but it can become part of the environment’s machinery.

Now, we have to remember that we have only one clear example of life: that which exists on the Earth. And all known life on Earth appears to share a common origin; all Earth life belongs to one vast biological family tree. But we cannot infer from a single example how common life may be in the Universe, or what forms it may take.

It could be that life appears readily wherever conditions are suitable, and it may very well be the case that simple microbial life is abundantly scattered throughout the universe. Or it could be that the transition from chemistry to life is an extremely rare event. This may be especially true when discussing complex life. Long-lived complex organisms may require a chain of favourable conditions: the right kind of star, a stable orbit, liquid water, a suitable atmosphere, enough heavy elements, geological recycling, climate stability, shielding from destructive radiation, protection from excessive impacts, plate tectonics, a planetary magnetic field, and vast stretches of time without experiencing any catastrophic events. Conditions allow possibilities, they don’t guarantee outcomes. Habitable does not imply inhabited.

So there are at least a couple of questions we need to unpack here; How common is the transition from complex chemical structures to simple life? And once simple life is established and given enough time, how common is highly complex life?

It may turn out that microbial life may be very common in the universe, while complex animal life may be rarer. Or simple life may be uncommon, and technological intelligence extremely rare. But such deliberations belong to a later part of our journey.

We are well on the way to at least getting some real answers on the first question. The search for life elsewhere will probably begin indirectly. Of course we should not expect to see forests, animals, or cities on distant planets. This is impossible with current technology. If the first evidence comes from another world, it will likely be chemical: promising traces in an atmosphere, unusual combinations of gases, or signs that a planet is chemically out of balance in ways that are difficult to explain without life.

Detecting one type of biosignature molecule by itself will not prove much. Methane, for example, can have geological sources, and Oxygen can arise without any biology under some conditions. We will need patterns of evidence: multiple signals that fit together, a planetary environment where the interpretation makes sense, and alternative explanations ruled out as far as possible. The first convincing evidence could also come from closer to home, from Mars, Europa, Enceladus, Titan, or some other Solar System environment where chemistry has had time and shelter to become interesting.

So, where does all this leave us? A useful working definition might be this: Life is a self-maintaining form of organized complexity, sustained by energy flow, that stores heritable information and belongs to a lineage capable of adaptive evolution through variation, inheritance, and differential persistence.

This is a rough definition, but it maintains that life marks a real threshold. Before life, patterns may persist, but it is only with life that patterns begin to maintain themselves through time. Life interacts with its environment, responding to local conditions, moving toward some chemical gradients and away from others. It starts behaving as though some states are preferable to others, and optimizing for its own existence. Is that some kind of primitive awareness?

At what point can we start speaking about experience, and when does a complex living organism become a sentient life form?

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Further reading
Erwin Schrödinger’s “What Is Life?” for the classic question of how living order can be understood through physics, chemistry, and information; Jim Baggott’s “Origins” for a modern scientific account of the path from the Big Bang to life and consciousness; Lisa Kaltenegger’s “Alien Earths” for habitable worlds, biosignatures, and the search for life beyond Earth.

Related lighter and fun fiction
Olaf Stapledon’s Last and First Men imagines the long evolution of life, humanity, and successor species across deep time; Isaac Asimov’s fiction repeatedly explores life, intelligence, robotics, and civilization through clean thought experiments; Ursula K. Le Guin’s novels are excellent companions for thinking about life, culture, difference, ecology, and moral imagination.

Life, the Universe and Everything (Part 1)

This is the first in a series of essays exploring a chain of questions about complexity, life, consciousness, intelligence, and ethics. Together, they form a rough map of the journey, hopefully with not too many imaginary dragons along the way.

Part 1

What is life, how does it come about in the Universe, how rare is it? How should we think about the value of life, from a humble bacterium to a sperm whale? Is there some useful framework which could help us investigate this question soberly, unfettered from religious or ideological doctrines? In order to start exploring these questions, let’s begin with a simple but fundamental concept: complexity.

Consider a crystal. It is a conglomeration of atoms naturally arranged in a well-defined pattern. The pattern determines its form and rigidity, but a crystal is a static arrangement, it does not move, self-regulate, repair itself, adapt, or respond to the world except through ordinary physical interaction. The amount of information we need to communicate precisely what a crystal is can be simplified, because of these patterns.

Smoke, on the other hand, moves and changes its shape constantly. Smoke is also physical matter, made up of large numbers of particles that interact with each other, but here the particles are not arranged in well-defined patterns. They move around, collide, swirl, and spread. If we tried to describe all that microscopic activity in full detail, the description would be enormous. It would require that we track each individual particle and its interactions with surrounding particles. Smoke is hard to describe precisely, beyond some general statistical properties.

Considering these two simple examples, we can start to see why information matters when we talk about complexity.

But what kind of information is useful, and in what sense? A quick distinction may help. Data are recorded differences: positions, temperatures, symbols, measurements. Information is drawing inferences from data that reduces uncertainty in some context. Organized information is information embedded in relationships that produce stable effects. The last of these is the one that matters most here.

The crystal contains information in its structure, because the arrangement of its atoms reveals something fundamental about the rest of it. Describing the pattern compactifies the description. One no longer needs to describe exactly what each atom is doing, we describe the pattern without loss of information. Of course smoke contains information too, in a statistical sense. But that information is mostly not organized into stable patterns. It is hard to summarize because of its inherent messiness.

So complexity is not just about how much information is needed to describe something. There is something relevant about the nature of this information itself. What part of it is preserved, structured? Does local information carry over to other parts of the system in ways that are reproducible? Does it generate patterns that can persist, change in some predictable fashion, or be transmitted in some way or form? Or is the information indistinguishable from random noise?

Entropy measures the degree of disorder of a system. In information theory, it is more precise to think of it as a measure of uncertainty. Smoke for example, has high entropy because it is highly disorganized and we need excessive amounts of information to describe it precisely. It is not easily reducible. A random signal has high entropy because it is hard to predict. A regularly repeated signal has lower entropy because it is easier to predict. Noise can reveal broad statistical properties and temporary local patterns, but not patterns that persist, regulate, reproduce, or compound.

So the important question to ask is whether the information content is organized in some form. Does it carry patterns? Does the ordered structure regulate a process? Can it respond to changes without dissolving into noise? This is where complexity starts to become interesting, when it becomes organized and persistent.

Ok, but organized how?

A large pile of bricks and a house both have structure, but it is not organized in the same way. In the pile, the bricks are simply there, ordered or disordered. In the house, the position of each part relates to the function of the whole. Walls carry weight, doors allow passage without compromising the structure, windows let in light, and so on. The ordered complexity of the arrangement is necessary because each of the parts constrains and supports each other. All together, they serve some common function: to provide humans with a living space. This is artificial organization of course, but natural systems can also naturally develop ordered patterns that serve different functions.

A whirlpool, or a hurricane, also has some kind of organization that makes it more interesting than smoke. It can maintain an identifiable structure for some time. Energy flowing through its structure is one of the ways information propagates across the system. But these structures arise only under particular conditions. Remove those conditions, and the pattern quickly disappears.

So persistence of structures seems relevant when we are talking about ordered complexity, but persistence of ordered complexity alone is not a guarantee of compounding higher degrees of complexity. A rock can persist for a very long time, but its complex structure is not particularly exciting (unless you are a geologist, in which case, fair enough).

If we want to understand how organized complexity starts moving toward life, something more than persistence is required. A stable, reproducible pattern is needed, but additional activity is also necessary. Certain sufficiently complex patterns perform functions.

A flame maintains itself while fuel and oxygen are available. It replicates under the right conditions and converts energy. But it does not store information, does not alter its structure across generations, or build internal machinery to regulate itself. It operates in a limited fashion until the underlying conditions fail.

But there are also patterns that can preserve some part of their own organization across time. It happens all the time in chemical reactions across the universe, and one chemical element, Carbon, is exceptionally good at generating large complex structures by repeatedly bonding with itself.

Complex organized chemical structures gradually interacted in ways that produced more complex arrangements. They became larger organized structures with multiple components. Most of these arrangements formed, drifted, broke apart, or dissolved back into the chemical background, and nothing lasting came out of them. Remnants of such processes are in the dust and gas in the interstellar medium.

But there are places in the universe with abundant available energy and with very rich and diverse types of highly organized building blocks. And a tiny fraction of these building blocks randomly arranged themselves in patterns that began to chemically interact with their environment in more complex ways. Interactions between complex systems began to become complex themselves. Additional complexity compounds. Once a system has more parts interacting in more ways, it gains new degrees of freedom. More things can happen.

Chemistry determines what types of different complex molecules interact, and how, under local constraints. Some arrangements are more stable than others. Certain arrangements make other arrangements more likely. The degree of randomness is constrained because of energy conditions, molecular shapes, charges, relative concentrations, surface, temperature and pressure conditions, which all restrict what processes can take place. The possible combinations are vast, but not arbitrary.

If everything disperses immediately, the system has no local history. Useful products will drift away and reaction networks break apart. Locality means that the reactions take place in some kind of setting where their products remain near each other. This could take the form of a membrane, a droplet, a mineral pore, an ice pocket, or some other structure that preserves locality. The system needs enough separation from its surroundings for its internal state to matter. This sets up feedback loops inside that environment. Products accumulate, some reactions may become easier, structures can stabilize other structures, and some arrangements last longer, while others collapse.

Once variation exists, some versions persist better than others under those particular conditions. Certain patterns persist more efficiently and become more common. The loop now includes energy flow, locality, self-maintenance, information storage, imperfect copying and selection. The underlying system begins to participate in its own persistence.

The whole process acts as a filter. The pattern becomes part of a process that preserves and reproduces structure. Ordered complexity and information are no longer merely present in the arrangement. They begin to play a role inside the arrangement. This is the first major threshold.

Ordered complexity becomes the foundation of structures that persist, interact, regulate, and help generate more structure. The road toward highly complex systems, and perhaps toward very simple life, starts to barely become visible, though by no means inevitable. Under the right conditions, matter can organize itself into patterns that participate in their own continuation.

So the natural next question is this: at what point do some complex organized patterns become identifiable as life?

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Further reading
If you want to dig deeper, here are some recommendations that explore these ideas: James Gleick’s Chaos for how simple rules can produce complex and unpredictable behaviour; Philip Ball’s Patterns in Nature for the way natural forms and structures arise without design; and Max Tegmark’s Our Mathematical Universe for thinking about reality as mathematical structure and pattern.

Related lighter and fun fiction
Olaf Stapledon’s Star Maker approaches cosmic order, life, mind, and civilization on the largest possible scale; Arthur C. Clarke’s 2001: A Space Odyssey explores intelligence, evolution, tools, and encounters with higher-order mystery; and Iain M. Banks’ Excession imagines advanced minds confronting something beyond their own frame of understanding.

Κλιματική αλλαγή (ξανά)

 Πριν από σχεδόν δέκα χρόνια είχα γράψει ένα μικρό κείμενο για την κλιματική αλλαγή, επειδή είχα απηυδήσει να διαβάζω διάφορες ανοησίες στα ελληνικά social media. Δέκα χρόνια μετά διαβάζουμε ακόμη τις ίδιες σαχλαμάρες.

Μια μπούρδα ολκής είναι το επιχείρημα «Το κλίμα πάντα άλλαζε.»

Ναί, και οι άνθρωποι πάντα πέθαιναν, αλλά αν βρεις κάποιον με μια χαντζάρα στην πλάτη δεν λες, ναί μωρέ,  «οι άνθρωποι πάντα πέθαιναν». Το ξέρουμε ότι το κλίμα της Γης έχει αλλάξει στο παρελθόν. Οι αλλαγές αυτές είναι γενικά σταδιακές και παίρνουν εκατομμύρια χρόνια. Το ερώτημά μας είναι τι προκαλεί τη σημερινή, ραγδαία εξελισσόμενη θέρμανση του πλανήτη τα τελευταία περίπου 100 χρόνια. Κι εδώ επίσης ξέρουμε την απάντηση.

Δεν υπάρχει ουδεμία αμφιβολία οτι τα κύρια αίτια είναι η ανθρώπινη δραστηριότητα, κυρίως η καύση ορυκτών καυσίμων, η αύξηση των αερίων του θερμοκηπίου και οι αλλαγές στη χρήση γης. Δεν είναι πολιτικό το θέμα. Είναι αυστηρά επιστημονικό και στηρίζεται σε τεράστιο όγκο δεδομένων. Όχι επειδή το λέω εγώ, ή κάποιος τυχάρπαστος σε ένα πάνελ. Δεν είναι κάποια «ατζέντα». Είναι το συμπέρασμα πολλών δεκαετιών μετρήσεων, φυσικής, μοντέλων, δορυφορικών παρατηρήσεων, παλαιοκλιματικών δεδομένων, ισοτοπικών ενδείξεων, μετρήσεων CO₂, ενεργειακού ισοζυγίου και ατμοσφαιρικής φυσικής. Από επιστημονικής άποψης, είναι λυμένο πρόβλημα. Οι πολιτικές προεκτάσεις είναι άλλο θέμα. Πρώτα αναγνωρίζουμε πώς έχει πραγματικά η κατάσταση, και μετά συζητάμε ώς κοινωνίες τί μπορούμε να κάνουμε. Δεν χώνουμε το κεφάλι στην άμμο και τραγουδάμε λαλαλά.

Κάποιοι προσπαθούν να θολώσουν τα νερά γιατί είτε δεν καταλαβαίνουν πώς να διαβάσουν τις μετρήσεις, είτε γιατί πιστεύουν σε θεωρίες συνωμοσίας, είτε γιατί έχουν κάτι να κερδίσουν, είτε γιατί δεν πιστεύουν ότι μπορούμε να κάνουμε τίποτα, είτε γιατί αμφισβητούν κάποια από τα δεδομένα, πάντα επιλεκτικά.  Αυτό λέγεται cherry-picking. Παίρνουν δηλαδή μία συγκεκριμένη πηγή, έναν επιστήμονα, ένα γράφημα χωρίς πλαίσιο, ή μία περίοδο δέκα ετών που τους βολεύει, και τα παρουσιάζουν ως δήθεν αντίβαρο απέναντι σε ολόκληρο το σώμα της επιστημονικής γνώσης. Παιδιά, αυτό δεν είναι σκεπτικισμός. Είναι επιλεκτική άγνοια.

Ο πραγματικός σκεπτικισμός κοιτάζει όλα τα δεδομένα. Ρωτά αν η υπόθεση εξηγεί το σύνολο των παρατηρήσεων. Αντέχει στον έλεγχο; Κάνει προβλέψεις; Συμφωνεί με τη φυσική που γνωρίζουμε; Εξηγεί γιατί θερμαίνεται η τροπόσφαιρα και ψύχεται η στρατόσφαιρα; Εξηγεί την άνοδο της θερμοκρασίας των ωκεανών; Εξηγεί την αύξηση της συγκέντρωσης CO₂ και την ισοτοπική του υπογραφή; Εξηγεί γιατί οι φυσικοί παράγοντες, όπως ο Ήλιος ή τα ηφαίστεια, δεν αρκούν για να εξηγήσουν τη σημερινή θέρμανση; Η άρνηση δεν τα εξηγεί αυτά. Απλώς αναποδογυρίζει τη σκακιέρα και βγάζει γλώσσα. Και, ειλικρινά, έχει αρχίσει να γίνεται κουραστικό.

Δεν είμαστε στο 1990. Δεν είμαστε κάν στην αρχή της συζήτησης. Δεν περιμένουμε ακόμη να βεβαιωθούμε αν είναι πραγματικά ανθρωπογενής ή όχι. Η επιστημονική συζήτηση σήμερα αφορά τις λεπτομέρειες, τα εύρη αβεβαιότητας,τις  περιφερειακές επιπτώσεις, την ταχύτητα των αλλαγών, διάφορα σενάρια εκπομπών, πιθανές προσαρμογές, πιθανές τεχνολογικές λύσεις, πολιτικές αποφάσεις και κόστος.

Ανεξάρτητες μελέτες, με διαφορετικές μεθόδους, διαφορετικά δεδομένα, διαφορετικά μοντέλα και διαφορετικές αρχικές υποθέσεις, συγκλίνουν στο ίδιο συμπέρασμα επειδή αυτό εξηγεί καλύτερα την πραγματικότητα. Και όταν τα δεδομένα αλλάζουν, η επιστήμη διορθώνεται. Αυτό είναι το ακριβώς αντίθετο της ιδεολογικής τύφλωσης.

Η ειρωνεία είναι ότι πολλοί από αυτούς που φωνάζουν ότι «η επιστήμη πρέπει να αμφισβητείται» δεν αμφισβητούν τίποτα από αυτά που τους βολεύουν. Αμφισβητούν μόνο το συμπέρασμα που δεν τους αρέσει. Παιδιά, σας έχω νέα. Δεν είναι ελεύθερη σκέψη να αγνοείς συστηματικά τα δεδομένα, ούτε είναι θαρραλέο να προωθείς μπούρδες, ούτε είναι έξυπνο να ψάχνεις στο διαδίκτυο μέχρι να βρεις έναν άνθρωπο, κάπου, που λέει αυτό που ήθελες να ακούσεις εξαρχής.

Σας ενοχλεί που το θέμα έχει πάρει πολιτικές διαστάσεις; Σας τη δίνουν μερικοί ακτιβιστές και το γενικότερο τοξικό κλίμα του διαλόγου; Πάρτε αριθμό και μπείτε στη σειρά. Αλλά το θέμα δεν είναι πολιτικό, είναι επιστημονικό. 

Με αυτό ώς δεδομένο, μπορούμε μετά να συζητήσουμε για πολιτικές λύσεις. Να συμφωνήσουμε ή να διαφωνήσουμε για πυρηνική ενέργεια, ΑΠΕ, φόρους άνθρακα, τεχνολογική καινοτομία, προσαρμογή, κόστος, δικαιοσύνη, ανάπτυξη, γεωπολιτική. Αλλά το να επιστρέφουμε κάθε τόσο στο «το κλίμα πάντα άλλαζε» είναι σαν να επιστρέφουμε συνεχώς στην ιδέα οτι η Γή είναι επίπεδη, και είναι σπατάλη χρόνου και δημιουργικής ενέργειας. Άντε, γιατί κάποια στιγμή πρέπει να τελειώνουμε με τα προσχήματα.

Η ανθρωπογενής κλιματική αλλαγή είναι πραγματική. Η βασική φυσική είναι γνωστή. Τα δεδομένα είναι συντριπτικά. Η επιστημονική συναίνεση είναι εξαιρετικά ισχυρή. Και η επιλεκτική χρήση πηγών για να συντηρείται η άρνηση είναι αισχρή παραπληροφόρηση.

Στην τελική, αν ακόμα έχετε αμφιβολίες, ρωτήστε κι εμάς που ξημεροβραδιάζουμε μέσα στην επιστημονική βιβλιογραφία να μάθετε περισσότερα. Εδώ είμαστε.

Πηγές:

1. Cook, J. et al. (2013), “Quantifying the consensus on anthropogenic global warming in the scientific literature”, Environmental Research Letters, 8, 024024.
   Μελέτη 11.944 επιστημονικών περιλήψεων για την κλιματική αλλαγή. Από τις εργασίες που εξέφραζαν θέση για την αιτία της υπερθέρμανσης, το 97,1% υποστήριζε την ανθρωπογενή εξήγηση.
   https://doi.org/10.1088/1748-9326/8/2/024024
2. Cook, J. et al. (2016), “Consensus on consensus: a synthesis of consensus estimates on human-caused global warming”, Environmental Research Letters, 11, 048002.
   Σύνθεση έξι ανεξάρτητων μελετών για την επιστημονική συναίνεση. Το συμπέρασμα είναι ότι 90-100% των ενεργών επιστημόνων του κλίματος συμφωνούν πως οι άνθρωποι προκαλούν τη σημερινή υπερθέρμανση.
   https://doi.org/10.1088/1748-9326/11/4/048002
3. Lynas, M., Houlton, B. Z. & Perry, S. (2021), “Greater than 99% consensus on human caused climate change in the peer-reviewed scientific literature”, Environmental Research Letters, 16, 114005.
   Επικαιροποιημένη ανάλυση 88.125 επιστημονικών εργασιών από το 2012 έως το 2020. Το συμπέρασμα είναι ότι η συναίνεση στην επιστημονική βιβλιογραφία υπερβαίνει το 99%.
   https://doi.org/10.1088/1748-9326/ac2966

Artificial Intelligence: Digital Utopia or Dystopian Nightmare (Addendum 2026)

In late 2023, when large language models had just begun to seize the public imagination, I wrote a short essay to think through where AI might be taking us, and three years on it seems worth revisiting those original premises in light of how quickly the technology, and the debate around it, have evolved.

I think the broad thrust of the original article still seems right.

The first and most obvious change is that large language models are no longer merely text generators that sometimes say clever things, sometimes hallucinate and generate images with 100 fingers. They have become increasingly multimodal, better at coding, better at using tools, and better at handling long structured tasks. The old chatbot has become a much more useful tool.

That does not mean the core reliability problem has disappeared. These systems still make things up, miss context and require verification, especially in technical or scientific settings. But it is no longer serious to dismiss them as glorified autocomplete. They have crossed the threshold from novelty to utility, and in some fields from utility to genuine leverage.

In 2023, I wrote that it is experts who can truly push these systems to their limits, and that remains largely true. What has changed is that the floor has risen. Non-experts can now get genuinely useful work out of these systems far more easily than they could in 2023. The moat has narrowed.

The likely disruption then is more subtle, and perhaps more alarming for that reason. As AI lowers the cost of first drafts and routine cognitive work, smaller teams can now do work that previously required larger ones. Less experienced workers can produce passable results for longer, which makes substitution easier in some contexts. Experts will still be needed, increasingly to validate, debug and judge, because someone still has to understand the system well enough to know when the machine is wrong. Employers can ask more from fewer people. What then happens to apprenticeships?

Even where jobs are not eliminated outright, parts of jobs are being hollowed out or repriced. The social effects can arrive long before the dramatic headline event of "mass unemployment". Fewer junior positions, weaker bargaining power, and the gradual decoupling of output from payroll can reshape society without anyone ever being able to point to a single clean moment when the machine took over.

On creativity, AI really is lowering barriers to entry in writing, illustration, music and design. That is liberating for many people. But we are also getting much more sludge. Production is cheaper. Attention is scattered. Distinctive style matters more.

In 2023 it was already obvious that creators would object to having their work vacuumed into training data without consent or compensation. Since then, the European Union's AI Act has begun to apply in stages, and the copyright and licensing disputes around training data have moved into the legal domain. The conversation continues. Napster changed the music industry. This too shall be settled.

Schools and universities can no longer pretend that students will not use AI or that the old assessment structure can be defended by raised eyebrows. If a machine can routinely solve standard exercises, draft essays and explain intermediate steps, then education has to lean more heavily into interpretation, judgment and oral defence. In other words, it must place more value on the distinctly human parts of thought. Frankly, it should have been moving in that direction anyway.

I now regularly ask my students to present their work orally and we discuss both the problems and their different approaches. I tell them to think about the problem themselves first and try to solve it with their group. If they want to use AI, I tell them to use it creatively: ask for hints when stuck, explore unconventional approaches, and clarify confusing concepts. They still need to understand the problem well when they present their solutions in front of the class.

I ended the 2023 essay saying that some sort of UBI will be unavoidable, and I still think that. A full UBI remains politically difficult and fiscally contentious. But a broader search has begun for ways to decouple a meaningful part of economic security from traditional wage labour. Whether that becomes UBI or something similar is still unclear.

That, to me, is the key point. It is not that AI will abolish all work, but that it can reorganise labour markets and income distribution quickly enough that the old social settlement begins to crack. If productivity rises while the gains accrue mainly to those who own the models, chips, data and capital, then societies will eventually face a blunt question: how exactly are ordinary citizens supposed to share in prosperity?

The discussion has already started. It revolves around guaranteed income, public wealth funds, and other ways of giving people a firmer economic floor in a world where wages may no longer distribute prosperity reliably enough.

We are still, I think, a long way from the end of this story. But we are no longer in the opening scene either.

The problem with satellite swarms

The Vera C. Rubin Observatory will soon begin a rapid, long wide-field survey called the Legacy Survey of Space and Time (LSST). The survey itself is simple enough to describe: take many deep snapshots of the entire night sky, night after night, do this for about a decade, and carefully track anything that changes or moves. The list of things that change or move will include potentially hazardous asteroids, exploding stars, a bunch of other known astrophysical phenomena and a lot of “what the hell is this thing” discoveries. It will also help us better understand the nature of dark matter and dark energy.

All this is very cool and we astronomers are very excited about it. However, there’s a potential complication that can harm this project (as well as other already existing observatories). SpaceX and other (commercial as well as state) actors are discussing and planning very large new satellite fleets, including proposals described publicly as orbiting “data center” infrastructure that could scale to hundreds of thousands of satellite spacecraft. FCC filings reported in the press suggest the intention is far beyond today’s already huge constellations of satellites. At that scale, satellites become frequent very bright streaks through telescope images, especially around twilight, and they can also add a diffuse, harder-to-remove glow to the background sky as sunlight scatters off many of these objects.

Ok, so why is that a problem for me, you may ask. I just want a better signal for my phone. Well, this is not only about pretty astronomical pictures. It is about disrupting an early-warning system for potential asteroid threats, changing the shared night sky in ways that are extremely difficult to reverse (your kids and their kids will never get to experience the night sky like you did), and about degrading a very important, high quality scientific dataset that taxpayers already paid for, that is meant to be openly available to everyone for many decades to come. As Andy Lawrence argues in his book “Losing the Sky”, the night sky is a shared environment. If we treat it like an unregulated dumping ground, we lose something that is hard to replace, scientifically and culturally.

The good news is that dealing with this does not require a ban on satellites. But it does require setting standards and demanding accountability. It means designing satellites to be much darker in practice, choosing appropriate orbits that reduce how long they stay sunlit over major observatories, sharing precise orbit predictions so telescope operators can plan around crossings, and doing honest cumulative environmental and safety reviews before scaling up. It requires close coordination between the satellite developers and the affected parties. It also means treating orbital crowding and debris risk as a real public-interest constraint, not an afterthought. It is entirely possible to keep the benefits of space services and at the same time maintain access to the night sky, but only if “move fast and launch everything, because of competition and market share capture” stops being the default.

What can you do as an individual? You can (1) raise awareness: read about, support and share work by groups like the International Dark-Sky Association, (2) ask your elected representatives and regulators to require brightness standards, transparent orbit data, and cumulative impact assessments for mega-constellations, (3) support companies that adopt meaningful darkening and operational mitigations, and (4) talk about this as a solvable engineering and governance problem, not a culture war. Increasing public pressure is often what turns “nice-to-have” in theory into practical requirements.

The Unspoken Cost of Knowledge: How Academic Publishing Profits from Free Labor

When most people think of publishing, they imagine a writer being paid for their work, an editor polishing it, and a reader buying the final product. This transactional loop, however imperfect, makes a certain kind of economic sense.

Academic publishing, however, doesn’t follow this pattern. In fact, it inverts it.

In academic publishing, it is not the publishers that pay those who work to generate the content, it is the other way round. Then there are also the reviewers, experts in their particular fields, who are called upon to assess and review the content submitted by the authors before publication, a process that can take months with a lot of back and forth. They also work pro bono. Meanwhile, the publishers profit by charging either the readers through subscriptions or, more recently, the authors themselves through article processing charges (APCs). The result is a system where the people who create and validate knowledge are volunteering their time, while the organizations that distribute it turn a handsome profit.

This would be strange enough if it were a quirky side effect of bureaucracy. But it’s not. It’s the system. And it’s wildly profitable.

The Economics of an Asymmetry

Producing a peer-reviewed paper is not a trivial affair. Researchers spend months, sometimes years, gathering and analyzing data, refining arguments, and engaging with an ever-growing thicket of academic literature. When they’re finally ready to publish, they often face hefty charges just to make their work publicly available. Article processing charges commonly range from $1,600 to $4,000, with high-prestige journals charging much more. Nature, for instance, now charges over $12,000 for its Gold Open Access option.

Even when authors manage to publish without paying upfront, usually in subscription-based journals, universities and libraries still foot enormous bills to access that content. This is what makes the economic structure so peculiar: the costs are real, but they are rarely borne by the publishers. Independent studies estimate that the actual cost of processing and publishing a paper lies somewhere between $200 and $700. The rest? Pure profit.

And profit they do. Elsevier reported a 38% operating margin in 2023, a number that surpasses even tech giants like Apple or Alphabet. Springer Nature and Taylor & Francis reported margins in the 28% range and 35% range respectively. These are not the returns of a struggling industry. They are the hallmarks of a rentier model built on monopolizing access to knowledge.

To add insult to injury, authors often surrender copyright to their own work. That means they can’t freely share, reuse, or even publicly post their own findings, at least not in the final, published form, without explicit permission from the publisher. The content is no longer theirs. It belongs to the distributor.

Open Access: A Solution That Isn't

But what about Open Access journals? At first glance, Open Access seems like the fix we’ve all been waiting for: make all research freely available to everyone, no subscriptions, no gatekeeping. Knowledge for the many, not the few. And indeed, perhaps that was the intention, to remove paywalls and democratize access to scientific findings. But Open Access has not solved the problem. It has simply moved it.

Instead of charging readers or libraries to access research, publishers now charge authors to publish it. These are the aforementioned Article Processing Charges, often thousands of dollars per article, paid by researchers, their institutions, or more often, indirectly by the public through government-funded grants. So the cost hasn’t disappeared. It’s just been shifted upstream. The reader no longer pays, the writer does. And the writer’s wallet is frequently taxpayer-funded.

Meanwhile, the underlying business model remains intact. Publishers are still extracting massive profits, just from a different node in the chain. Worse, this system often introduces new barriers: now, if you want to publish in a prestigious journal, you don’t just need good ideas. You need funding. Researchers at underfunded institutions, in the Global South, or in fields with limited grant support, are once again priced out, not from reading the science, but from contributing to it.

The paywall hasn’t been demolished. It’s just been relocated.

The Oubliette

The academic publishing system persists because of an unspoken compromise between compliance and necessity. Academics know it’s exploitative, but early-career researchers are under immense pressure to publish in prestigious journals. For academics, especially early on in their careers, tenure, funding, credibility, it all hinges on where you publish, not just what you publish. 

So even when researchers are aware of the flaws, they cannot afford to not participate. It’s not apathy. It’s survival. Change, under these conditions, is not just difficult. It can be professionally dangerous.

On Academic Duty

Defenders of the system sometimes argue that writing and peer review are part of the  academic job, already paid for by salaries, grants, or public funding. Why not then consider peer review as a kind of civic duty? The problem is that this narrative overlooks the broader structure. First, academic salaries are modest, often significantly lower than those offered to individuals with comparable skills in industry. Most academics work on precarious contracts, with limited institutional support. Second, publicly funded research should be accessible to the public, not hidden behind paywalls that restrict its reach and impact. Third, tax money intended to support the advancement of science should not be diverted to enrich private publishing companies, but should instead be reinvested into further research and education. Fourth, the time and effort dedicated to peer reviewing and revising articles comes at the expense of teaching, mentoring, and conducting new research, core activities that universities and the public explicitly value. 

Peer review is essential labor. Without it, the entire edifice of scholarly communication collapses. And yet it is invisible in tenure files, promotion cases, and annual evaluations. It is uncredited, unremunerated, and often thankless.

There are broader implications, too. High APCs and subscription costs deepen the divide between wealthy institutions and the rest of the world. Researchers in lower-income countries, or even underfunded departments, simply can’t afford to participate in this system, either as authors or readers. The result is a kind of epistemic inequality: knowledge flows downhill, access is tiered, and entire regions are locked out of the global scientific conversation.

Reform and Solutions

Given these inequities, it is clear that reform is needed. One promising model is exemplified by platforms like the Open Journal of Astrophysics, which uses the arXiv preprint server as its submission system. Here, articles are submitted openly and peer reviewers are assigned to evaluate the work transparently. This system minimizes costs, maximizes accessibility, and keeps ownership with the researchers. This model could be expanded. Universities and consortia could collaborate to host decentralized, nonprofit journals. These would restore control to the scholarly community and reduce dependence on commercial platforms.

Alternatively, the publishing industry could introduce a model where both authors and reviewers are remunerated for their contributions. Reviewers could receive base compensation for their evaluations, with opportunities to earn higher rates for thorough, well-argued, and respectfully conducted reviews. Outstanding reviewers could be recognized through formal credentials and higher pay rates, encouraging a culture of constructive and diligent peer review. Authors could also be provided with modest stipends to offset the hidden costs of article preparation and revisions. Such a system would not only reward academic labor fairly but also improve the overall quality, rigor, and civility of scholarly communication.

Such reforms wouldn’t just create fairer conditions. They’d likely improve the quality, speed, and rigor of scholarly communication as a whole.

Reclaiming the Commons

Researchers themselves also have a role to play in driving change. Before achieving tenure, they can carefully balance the need to publish in high-impact journals with efforts to also submit work to reputable, low-cost open-access venues whenever possible. They can advocate for transparency in peer review and promote discussions about reform within their institutions. After achieving tenure, researchers are in a stronger position to challenge the status quo more openly: by prioritizing low-cost open-access journals, participating in or founding new publishing initiatives, mentoring young researchers about their publishing choices, and pressuring academic societies and funding agencies to support open science principles.

And for those outside academia: this affects you too. As taxpayers, your tax money funds most of this research. You have a right to access it. You have a right to ask why the products of public investment are being locked away for private profit. You can support open-access legislation, pressure politicians to pressure funding agencies and universities to rethink publishing priorities, and back projects that are trying to do things differently. Journalists, educators, and policymakers can help raise awareness of the inequities in academic publishing. Ultimately, by demanding that publicly funded research remain publicly accessible, we can all help shift the system toward one that serves science and society, rather than private profit.

Knowledge as a public good

Academic publishing has become a system where the creators of new knowledge must pay to give it away, while the public, who funded the creation of this new knowledge, must pay again to read it. The costs are high, the profits concentrated, and the labor largely invisible.

If we believe that knowledge is a public good and not a luxury commodity, then we need to work towards a system that reflects that belief. That means rewarding the work that sustains it, reducing barriers to entry, and making the outputs of scholarship freely available to all.

The current structure is outdated. The incentives are misaligned. But the alternatives are no longer hypothetical. They’re real, viable, and already in motion.

All that remains is the will to choose them.

References:
Cost of publication in Nature https://www.nature.com/nature/for-authors/publishing-options

How publishers profit from article charges: https://direct.mit.edu/qss/article-pdf/4/4/778/2339495/qss_a_00272.pdf

How bad is it and how did we get here? https://www.theguardian.com/science/2017/jun/27/profitable-business-scientific-publishing-bad-for-science

How academic publishers profit from the publish-or-perish culture

https://www.ft.com/content/575f72a8-4eb2-4538-87a8-7652d67d499e

Academic publishers reap huge profits as libraries go broke

https://www.cbc.ca/news/science/academic-publishers-reap-huge-profits-as-libraries-go-broke-1.3111535

The political economy of academic publishing: On the commodification of a public good

https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0253226

Elsevier parent company reports 10% rise in profit, to £3.2bn

https://www.researchprofessionalnews.com/rr-news-world-2025-2-elsevier-parent-company-reports-10-rise-in-profit-to-3-2bn

Taylor & Francis revenues up 4.3% in 'strong trading performance'

https://www.thebookseller.com/news/taylor--francis-revenues-up-43-in-strong-trading-performance