New Dark Age: Technology and the End of the Future

by James Bridle

Over the last century, technological acceleration has transformed our planet, our societies, and ourselves, but it has failed to transform our understanding of these things. The reasons for this are complex, and the answers are complex too, not least because we ourselves are utterly enmeshed in technological systems, which shape in turn how we act and how we think. We cannot stand outside them; we cannot think without them.

Across the sciences and society, in politics and education, in warfare and commerce, new technologies do not merely augment our abilities, but actively shape and direct them, for better and for worse. It is increasingly necessary to be able to think new technologies in different ways, and to be critical of them, in order to meaningfully participate in that shaping and directing. If we do not understand how complex technologies function, how systems of technologies interconnect, and how systems of systems interact, then we are powerless within them, and their potential is more easily captured by selfish elites and inhuman corporations.

Precisely because these technologies interact with one another in unexpected and often-strange ways, and because we are completely entangled with them, this understanding cannot be limited to the practicalities of how things work: it must be extended to how things came to be, and how they continue to function in the world in ways that are often invisible and interwoven. What is required is not understanding, but literacy.

This is a good start, but learning to code is not enough, just as learning to plumb a sink is not enough to understand the complex interactions between water tables, political geography, ageing infrastructure, and social policy that define, shape and produce actual life support systems in society. A simply functional understanding of systems is insufficient; one needs to be able to think about histories and consequences too. Where did these systems come from, who designed them and what for, and which of these intentions still lurk within them today?

The second danger of a purely functional understanding of technology is what I call computational thinking. Computational thinking is an extension of what others have called solutionism: the belief that any given problem can be solved by the application of computation. Whatever the practical or social problem we face, there is an app for it. But solutionism is insufficient too; this is one of the things that our technology is trying to tell us. Beyond this error, computational thinking supposes – often at an unconscious level – that the world really is like the solutionists propose. It internalises solutionism to the degree that it is impossible to think or articulate the world in terms that are not computable.

If philosophy is that fraction of human thought dealing with that which cannot be explained by the sciences, then systemic literacy is the thinking that deals with a world that is not computable, while acknowledging that it is irrevocably shaped and informed by computation.

There is a concrete and causal relationship between the complexity of the systems we encounter every day; the opacity with which most of those systems are constructed or described; and fundamental, global issues of inequality, violence, populism and fundamentalism. All too often, new technologies are presented as inherently emancipatory. But this is itself an example of computational thinking, of which we are all guilty.

We don’t and cannot understand everything, but we are capable of thinking it. The ability to think without claiming, or even seeking, to fully understand is key to survival in a new dark age because, as we shall see, it is often impossible to understand. Technology is and can be a guide and helpmate in this thinking, providing we do not privilege its output: computers are not here to give us answers, but are tools for asking questions. As we will see recur throughout this book, understanding a technology deeply and systemically often allows us to remake its metaphors in the service of other ways of thinking.

Today the cloud is the central metaphor of the internet: a global system of great power and energy that nevertheless retains the aura of something noumenal and numinous, something almost impossible to grasp. We connect to the cloud; we work in it; we store and retrieve stuff from it; we think through it. We pay for it and only notice it when it breaks. It is something we experience all the time without really understanding what it is or how it works. It is something we are training ourselves to rely upon with only the haziest of notions about what is being entrusted, and what it is being entrusted to.

The cloud is a new kind of industry, and a hungry one. The cloud doesn’t just have a shadow; it has a footprint. Absorbed into the cloud are many of the previously weighty edifices of the civic sphere: the places where we shop, bank, socialise, borrow books, and vote. Thus obscured, they are rendered less visible and less amenable to critique, investigation, preservation and regulation.

There’s a reason global, supposedly post-colonial empires hold onto bits of disputed territory like Diego Garcia and Cyprus, and it’s because the cloud touches down in these places, and their ambiguous status can be exploited. The cloud shapes itself to geographies of power and influence, and it serves to reinforce them. The cloud is a power relationship, and most people are not on top of it.

In the fourteenth century, an unknown author of Christian mysticism wrote of ‘The Cloud of Unknowing’ that hangs between mankind and the Godhead: the embodiment of goodness, justice, and right action. This cloud cannot be pierced by thought, but by the letting-go of thought, and through the insistence upon the here and now – not the predicted, computed future – as the domain of agency. ‘Go after experience rather than knowledge,’ the author urges us. ‘On account of pride, knowledge may often deceive you, but this gentle, loving affection will not deceive you. Knowledge tends to breed conceit, but love builds. Knowledge is full of labor, but love, full of rest.’1 It is this cloud that we have sought to conquer with computation, but that is continually undone by the reality of what we are attempting. Cloudy thinking, the embrace of unknowing, might allow us to revert from computational thinking, and it is what the network itself urges upon us.

turn, the network gave expression to the basest and highest ideals, contained and exulted the most mundane and the most radical desires, almost none of it foreseen by its progenitors – who are all of us. There was and is no problem to solve, only collective enterprise: the emergent, unconscious generation of a tool for unconscious generation.

Our great failing in thinking the network up to now was to presume that its actions were inherent and inevitable. By inherent, I mean the notion that they emerged, ex nihilo, from the things we created rather than involving our own actions as part of that co-creation. By inevitable, I mean a belief in a direct line of technological and historical progress that we are powerless to resist. Such a belief has been repeatedly attacked by thinkers in the social sciences and philosophy for decades, yet it has not been defeated. Rather, it has been reified into technology itself: into machines that are supposed to carry out their own embedded desires. Thus we have abdicated our objections to linear progress, falling into the chasm of computational thinking.

And so we find ourselves today connected to vast repositories of knowledge, and yet we have not learned to think. In fact, the opposite is true: that which was intended to enlighten the world in practice darkens it. The abundance of information and the plurality of worldviews now accessible to us through the internet are not producing a coherent consensus reality, but one riven by fundamentalist insistence on simplistic narratives, conspiracy theories, and post-factual politics. It is on this contradiction that the idea of a new dark age turns: an age in which the value we have placed upon knowledge is destroyed by the abundance of that profitable commodity, and in which we look about ourselves in search of new ways to understand the world.

represent an absence or occlusion of knowledge, as the popular idea of a dark age holds. It is not an expression of nihilism or hopelessness. Rather, it refers to both the nature and the opportunity of the present crisis: an apparent inability to see clearly what is in front of us, and to act meaningfully, with agency and justice, in the world – and, through acknowledging this darkness, to seek new ways of seeing by another light.

Nothing here is an argument against technology: to do so would be to argue against ourselves. Rather, it is an argument for a more thoughtful engagement with technology, coupled with a radically different understanding of what it is possible to think and know about the world. Computational systems, as tools, emphasise one of the most powerful aspects of humanity: our ability to act effectively in the world and shape it to our desires. But uncovering and articulating those desires, and ensuring that they do not degrade, overrule, efface, or erase the desires of others, remains our prerogative.

Technology is not mere tool making and tool use: it is the making of metaphors. In making a tool, we instantiate a certain understanding of the world that, thus reified, is capable of achieving certain effects in that world. It thus becomes another moving part of our understanding of the world – if, often, unconsciously.

The argument set out in this book is that, like climate change, the effects of technology are widespread across the globe and are already affecting every area of our lives. These effects are potentially catastrophic, and result from an inability to comprehend the turbulent and networked outputs of our own inventions.

Thinking through machines predates the machines themselves. The existence of calculus proves that some problems may be tractable before it is possible to solve them practically. History, viewed as such a problem, might thus be transformed into a mathematical equation that, when solved, would produce the future. This was the belief of the early computational thinkers of the twentieth century, and its persistence, largely unquestioned and even unconscious, into our own time is the subject of this book. Personified today as a digital cloud, the story of computational thinking begins with the weather.

In October 1945, von Neumann wrote to Zworykin, stating, ‘I agree with you completely.’ The proposal was totally in line with what von Neumann had learned from the extensive research programme of the Manhattan Project, which relied on complex simulations of physical processes to predict real-world outcomes. In what could be taken as the founding statement of computational thought, he wrote: ‘All stable processes we shall predict. All unstable processes we shall control.’

Programming Hippo took almost a year, and when it was ready it was run continuously on the SSEC, twenty-four hours a day, seven days a week, for several months. The result of the calculations was at least three full simulations of a hydrogen bomb explosion: calculations carried out in full view of the public, in a shopfront in New York City, without anyone on the street being even slightly aware of what was going on.

As we shall see, technology’s increasing inability to predict the future – whether that’s the fluctuating markets of digital stock exchanges, the outcomes and applications of scientific research, or the accelerating instability of the global climate – stems directly from these misapprehensions about the neutrality and comprehensibility of computation.

All contemporary computation stems from this nexus: military attempts to predict and control the weather, and thus to control the future.

We have been conditioned to believe that computers render the world clearer and more efficient, that they reduce complexity and facilitate better solutions to the problems that beset us, and that they expand our agency to address an ever-widening domain of experience. But what if this is not true at all? A close reading of computer history reveals an ever-increasing opacity allied to a concentration of power, and the retreat of that power into ever more narrow domains of experience. By reifying the concerns of the present in unquestionable architectures, computation freezes the problems of the immediate moment into abstract, intractable dilemmas; obsessing over the inherent limitations of a small class of mathematical and material conundrums rather than the broader questions of a truly democratic and egalitarian society.

By conflating approximation with simulation, the high priests of computational thinking replace the world with flawed models of itself; and in doing so, as the modellers, they assume control of the world.

But our growing reliance on the system masks the fact that it can still be manipulated by those in control of its signals, including the United States government, which retains the ability to selectively deny positioning signals to any region it chooses.26 In the summer of 2017, a series of reports from the Black Sea showed deliberate interference with GPS occurring across a wide area, with ships’ navigation systems showing them tens of kilometres off their actual position. Many were relocated onshore, finding themselves virtually marooned in a Russian airbase – the suspected source of the spoofing effort.27 The Kremlin is surrounded by a similar field, as first discovered by players of Pokémon GO, who found their in-game characters teleported blocks away while trying to play the location-based game in the centre of Moscow.

That which computation sets out to map and model it eventually takes over. Google set out to index all human knowledge and became the source and arbiter of that knowledge: it became what people actually think. Facebook set out to map the connections between people – the social graph – and became the platform for those connections, irrevocably reshaping societal relationships. Like an air control system mistaking a flock of birds for a fleet of bombers, software is unable to distinguish between its model of the world and reality – and, once conditioned, neither are we.

This phenomenon is known as automation bias, and it has been observed in every computational domain from spell-checking software to autopilots, and in every type of person. Automation bias ensures that we value automated information more highly than our own experiences, even when it conflicts with other observations – particularly when those observations are ambiguous.

Just as global telecommunications have collapsed time and space, computation conflates past and future. That which is gathered as data is modelled as the way things are, and then projected forward – with the implicit assumption that things will not radically change or diverge from previous experiences. In this way, computation does not merely govern our actions in the present, but constructs a future that best fits its parameters. That which is possible becomes that which is computable. That which is hard to quantify and difficult to model, that which has not been seen before or which does not map onto established patterns, that which is uncertain or ambiguous, is excluded from the field of possible futures. Computation projects a future that is like the past – which makes it, in turn, incapable of dealing with the reality of the present, which is never stable.

Computational thinking insists on the easy answer, which requires the least amount of cognitive effort to arrive at. Moreover, it insists that there is an answer – one, inviolable answer that can be arrived at – at all.

Computational thinking has triumphed because it has first seduced us with its power, then befuddled us with its complexity, and finally settled into our cortexes as self-evident.

In the margins of his revision copy of Numerical Prediction, Lewis Fry Richardson wrote, Einstein has somewhere remarked that he was guided towards his discoveries by the notion that the important laws of physics were really simple. R.H. Fowler has been heard to remark that, of two formulae, the more elegant is the more likely to be true. Dirac sought an explanation alternative to that of spin in the electron because he felt that Nature could not have arranged it in so complicated a way. These mathematicians have been brilliantly successful in dealing with mass-points and point-charges. If they would condescend to attend to meteorology the subject might be greatly enriched. But I suspect they would have to abandon the idea that the truth is really simple.40

Coastlines were even worse, leading to the realisation that it is in fact impossible to give a completely accurate account of the length of a nation’s borders. This ‘coastline paradox’ came to be known as the Richardson effect, and formed the basis for Benoît Mandelbrot’s work on fractals. It demonstrates, with radical clarity, the counterintuitive premise of the new dark age: the more obsessively we attempt to compute the world, the more unknowably complex it appears.

Climate change is already occurring, and its effects are as visible and urgent in the landscapes of geopolitics as of geography. The Syrian conflict, which forced the ICARDA scientists to flee to Beirut and call on the Seed Vault for assistance, is itself partly attributable to changes in the environment.10 Between 2006 and 2011, more than half of the Syrian countryside suffered its worst drought on record. More intense and longer lasting than could be explained by natural variations in weather, this drought has been linked to accelerating climate change, and over a few years nearly 85 per cent of rural livestock died, as crops withered. President Bashar al-Assad redistributed traditional water rights to political allies, forcing farmers to dig illegal wells, while those who protested faced imprisonment, torture, and death.

Media reports and activists have called the Syrian conflict the first large-scale climate war of the twenty-first century, connecting climate directly to the vast numbers of refugees arriving in Europe. Scientists are more circumspect about making explicit connections between conflict and climate – but not about the changing climate itself. Even if Syria recovers politically in the next few years, it stands to lose nearly 50 per cent of its agricultural capacity by 2050. There is no going back from here.

But the opposite is occurring: our sources of data are slipping away, and with them the structures by which we have structured the world. The melting of the permafrost is both danger sign and metaphor: an accelerating collapse of both our environmental and our cognitive infrastructure. The certainties of the present are founded on the assumption of ever-increasing, ever-crystallising geologies of knowledge; it is reassuring to imagine a cooling earth, coming into shape, manifesting in distinct and solid forms. But, as in Siberia, the sponging of the Greenlandic landscape reiterates a return to the fluid: the marshy and boggy, the undifferentiated and gaseous. A new dark age will demand more liquid forms of knowing than can be derived from the libraries of the past alone.

In the electromagnetic spectrum, the strength and efficacy of wireless transmission will be reduced as temperatures rise. The refractive index of the atmosphere is highly dependent on humidity and severely affects the curvature of electromagnetic waves, along with the rate at which they fade. Increased temperatures and rainfall will shift the beams of point-to-point data links – such as microwave transmissions – and attenuate broadcast signals. As the earth warms and becomes wetter, ever-greater densities of wireless masts will be required, and maintenance will become more difficult.

As digital culture becomes faster, higher bandwidth, and more image-based, it also becomes more costly and destructive – both literally and figuratively. It requires more input and energy, and affirms the supremacy of the image – the visual representation of data – as the representation of the world. But these images are no longer true, and none less so than our image of the future. As the past melts into the permafrost, so is the future rocked by the atmosphere. The changing climate shakes not merely our expectations, but our ability to predict any future at all.

Clear-air turbulence is so named because it comes literally out of the blue. It occurs when bodies of air moving at wildly different speeds meet: as the winds shear against each other, vortices and chaotic movements are produced. While much studied, particularly in the high troposphere where long-haul aircraft operate, it remains almost impossible to detect or to predict. For this reason, it is much more dangerous than the predictable forms of turbulence that occur on the edges of storms and large weather systems, because pilots are unable to prepare, or route around it. And incidences of clear-air turbulence are increasing every year.

The reason for the increase in turbulence is rising levels of carbon dioxide in the atmosphere.

The authors of the turbulence study emphasise once again the nature of feedback in this rise in turbulence: ‘Aviation is partly responsible for changing the climate, but our findings show for the first time how climate change could affect aviation.’

History – progress – does not always go up and to the right: it’s not all sunlit uplands. And this isn’t – cannot be – about nostalgia. Rather, it is about acknowledging a present that has come unhinged from linear temporality, that diverges in crucial yet confusing ways from the very idea of history itself. Nothing is clear anymore, nor can it be. What has changed is not the dimensionality of the future, but its predictability.

In a 2016 editorial for the New York Times, computational meteorologist and past president of the American Meteorological Society William B. Gail cited a number of patterns that humanity has studied for centuries, but that are disrupted by climate change: long-term weather trends, fish spawning and migration, plant pollination, monsoon and tide cycles, the occurrence of ‘extreme’ weather events. For most of recorded history, these cycles have been broadly predictable, and we have built up vast reserves of knowledge that we can tap into in order to better sustain our ever more entangled civilisation.

Gail foresees a time in which our grandchildren might conceivably know less about the world in which they live than we do today, with correspondingly catastrophic events for complex societies.32 Perhaps, he wonders, we have already passed through ‘peak knowledge’, just as we may have already passed peak oil. A new dark age looms.

The degradation of our cognitive abilities is mirrored at scale in the collapse of the transatlantic jet routes, the undermining of communication networks, the erasure of diversity, the melting away of historical knowledge reserves: these are signs and portents of a wider inability to think at the network level, to sustain civilisation-scale thought and action. The structures we have built to extend our own life systems, our cognitive and haptic interfaces with the world, are the only tools we have for sensing a world dominated by the emergence of hyperobjects. Just as we are beginning to perceive them, our ability to do so is slipping away.

Steam engines happen when it’s steam engine time: a process almost mystical, almost teleological, because it exists outside the scope of our framework for understanding historical progress. The set of things that had to come together for this particular invention to occur includes so many thoughts and events we could not think or know about that its appearance is like that of a new star: magical and previously unthinkable. But the history of science shows us that all invention is simultaneous and multiauthored.

Such histories give the lie to the heroic narrative of history – the lone genius toiling away to produce a unique insight. History is networked and atemporal: steam engine time is a multidimensional structure, invisible to a sensorium trapped in time, but not insensible to

The Web happened because of the history of microprocessors and telecommunications and wartime industry and commercial requirements, and a bunch of different discoveries and patents and corporate research funds and academic papers and TBL’s own family history; but it also happened because it was Web Time: for a brief moment, the dispositions of culture and technology converged on an invention that, in hindsight, was predicted by everything from ancient Chinese encyclopaedias to microfilm retrieval to the stories of Jorge Luis Borges. The Web was necessary, and so it appeared – in this timeline, at least.

But Moore’s law, despite the name by which it came to be known (one which Moore himself wouldn’t use for two decades), is not a law. Rather, it’s a projection – in both senses of the word. It’s an extrapolation from the data but also a phantasm created by the restricted dimensionality of our imagination. It’s a confusion in the same manner as the cognitive bias that feeds our preference for heroic histories, but in the opposite direction. Where one bias leads us to see the inevitable march of progress through historical events to our present moment, the other sees this progress continuing inevitably into the future. And, as such projections do, it has the capability both to shape that future and to influence, in fundamental ways, other projections – regardless of the stability of its original premise.