The New Dark  Age

15th December 2018 |

     

   …when you are “nowhere” physically, you are “everywhere” spiritually…Never mind if you cannot fathom this nothing, for I love it surely so much the better.

–The Cloud of Unknowing

              On the eve of a World War escalating and sweeping through Europe, Virginia Woolf jotted down in her private notebook that “the future is dark, which is the best thing the future can be, I think.” At first glance, the year of entry evokes grim and grotesque images of a continent awash in bloodshed, where the motor of mass industrialized carnage became revved up by the advent of aerial bombing and poisonous gas unleashed on the Western Front. Woolf, afflicted with her own personal demons, bouts of depression, and a suicide attempt, channeled a vulnerable and demurred spirit in that entry, yet a spirit willing to dive into the maelstrom of a dark and uncertain future. It is this future as dark, that Virginia Woolf scholar Rebecca Solnit contends effaces“distinctions and definitions…in which things merge, change, become enchanted, aroused, impregnated, possessed, released, renewed.” 1 A world in which things enchant and possess, bewitched another contemporary disciple across the Atlantic, H.P. Lovecraft, whose conjuring up of arcane and cryptic worlds spoke to an epoch where “we shall either go mad from the revelation or flee from the deadly light into the peace and safety of a “new dark age.” Respectively, it is the timely ruminations of both that inform artist James Bridle’s work The New Dark Age: Technology and the End of the Future

           Combating the notion of a Dark Age as merely characterizing our entrance into an age of bleak and paralyzing hopelessness, Bridle contends it is an age that opens us to a frontier to be chartered. It is a frontier that willingly embraces an apparent inability to see clearly what is in front of us and instead embraces a ‘Cloudy Thinking’ that attempts to decouple us from a world organized around the logic and protocol of the Cloud, a logic that shackles us to the belief that our problems are solvable through the application of computation. Combined with Cloudy Thinking, Bridle invites us to still consider the weight of ‘acting meaningfully’ and retaining belief in concepts of agency and justice in a world roiled by the onslaught of Artificial Intelligence, Climate Change, and economic turbulence.

        Bridle’s slew of works have gained notoriety for their engagement in the role of invisibility behind the operation of our networks and technologies that constitute our medium-saturated environments. One such work, Drone Shadow, transformed urban streets into life-sized contours of Drones to highlight for Bridle how “the drone is shorthand for the internet, for all of our technologically-mediated experiences, as well as being a compelling image of today’s endless, borderless wars.” 2 The role of the invisible is ever more pertinent with the prevailing metaphor of our Internet Age, ‘The Cloud’ which played a role in Bridle’s next work, entitled the ‘Cloud Index.’ Utilizing a Neural Network and a collection of 15,000 satellite images of weather patterns, Bridle’s experiment was designed to predict weather patterns and particular voting results that lead up to the UK’s 2016 EU referendum.

        Here,Bridle’s New Dark Age elaborates his focus further on the tantalizing and numinous keyword of ‘The Cloud’ that streams, buffers, and upload us to screen of the present. On one end, it is The Cloud’s vaporous and numinous aura that enshrouds and mystifies a physicality behind the crosshatch of phone lines, fiber optics cables, satellites, data centers and vast warehouses populated with computers to monitor global supply chains. On the other end, it is our entanglement with and through The Cloud that not only ‘condenses’ our world into space-time computerized environments, importantly it also ‘evaporates’ our sense of agency. Primarily, the ubiquity of the Cloud engenders critical considerations as to what defines agency in an age where we are ceaselessly tracked and our habits and social networks are recalibrated through algorithmic governance. Here, our sense of agency and selfhood become dubious and blurred, as our sense of self becomes wrapped up through scoreboards of likes that are measuring and configuring our experience with these networks as ways to simply increase connectivity and social capital. 3 Thus, these social platforms are means to consume our sense of selfhood in order to generate data sets that ultimately enable us to automate what we think or say. This automation of what we think or say amplifies the phenomenon of filtering bubbles that are found to run amok especially on the platforms of Facebook, Twitter and Youtube. Worryingly, it also these platforms that are increasingly shaping what is deemed appropriate in terms of discourse concerning what voices and content are posted, liked and debated. Thus, The Cloud and its vast ecosystem only become less conducive to critique, investigation and regulation by users, where left in the dark, a sense of powerlessness emerges.

   Ultimately, Bridle weaves a compelling narrative that explores the genesis of the Cloud, focusing on the intriguing symbioses between early computer design that calculated the yield of atomic bombs and weather-control. Through Bridle genealogy, we can follow the course of a tectonic shift in our mode of framing the world and thinking that swept throughout the 20thcentury to solidify itself as the dominant mode and logic of our contemporary age.

        

        Bridle traces the ‘Cloud’ and its evolution from conception to realization through the origin and wedding of the fledgling fields of computation and meteorology. We follow how meteorology itself become a major catalyst for the computational revolution to unfold, a revolution that interestingly enough begins with one of many figures such as Quaker Lewis Fry Richardson. Experimenting with weather forecasting on The Western Front in 1913, he paved the way for the basis of modern day forecasting that is largely employed today. Richardson developed the idea of computationally modeling the weather using hydrodynamical equations that would be augmented and continually feedback from real-time weather data through studying changes in air pressure, temperature, density, humidity and wind velocity. Richardson’s vision entailed a painstaking process of creating numerical weather forecasts by hand that generated a gridded map of a forecast area, taking up to six weeks to produce for one location. Even though Richardson’s results were significantly off the mark, the employment of his method and slicing up of the world into a series of grids was crucial in laying down the basis for a cross-fertility of computation and meteorology. Richardson’s vision extended beyond the mere two-dimensional sheets of calculations and eventually ballooned into his idea of a ‘forecast factory’. His factory would be an enormous domelike theatre hall with a global map bedecked on its walls, and an estimated 64,000 ‘computers’ or a team of mathematicians focused on one small part of the globe tasked with calculating weather forecasts in real time.

              Richardson’s vision and ambition diminished after the course of the war only to be galvanized once again through World War II and the war machine that unleashed another explosion in computational power and interest in meteorology.

      Carrying on the legacy of Lewis Fry Richardson, the extraordinaries, John Von Neumann and Vladimir Zworykin became equally intrigued by the prospects of prediction and control in relation to Meteorology.  Von Neumann’s fascination translated into what we can assert became the paradigmatic motto of Modernity, as his bold proclamation that “All stable processes we shall predict,” and “All unstable processes we shall control” became a formative ethos that has shaped our contemporary landscape. The large volumes of Big Data collection, compounded by Algorithmic Surveillance and tools such as Neural Networks have revolutionized novel modalities of control, prediction and importantly intervention in our everyday lives.

        However, these modalities are also riven by an aspect of uncontrollability and uncertainty as we can observe in the renaissance of Machinic Intelligence that is leaving their engineers in the dark about the internal process of decision-making. One such example is Deep Learning, arguably crucial for today’s explosion of AI, which has trickled into the fields of medicine, finance, manufacturing. It  steadily gained its reputation through Image Recognition and Object Recognition competitions such as “ImageNet” that took place in the early 2010s, and garnered spotlight with Google’s AlphaGo triumph over Lee Sedol in 2016. Yet, we are confronted with models that simply aren’t a matter of opening the box and seeing its internal functions. Rather, we are handling networks that are calculations of serpentine mathematical functions and variables, and comprised of billion or trillions of simulated neuronal connections. They are delegated with the task and the ability to extract, teach and transform themselves in identifying patterns from the data sets they can access. 

 

Even with the developments and advances in Machine Learning, it still compels a critical question as to what is a distinctive feature that distinguishes machinic and human intelligence? The former here becomes increasingly autonomous and inaccessible in its decision-making operation while the latter evolved through suite of trust networks, emotional cues, and a cognition hinged on a unique form of sapien cooperation. 

      Nonetheless, Bridle draws focus on the prospect of ‘cooperation’ between algorithm and sapien, underscoring what he points to with the recently created Optometrist Algorithm. The project is A collaboration between Google and Tri AlphaEnergy that is designed to assist scientists in generating hotter plasma to achieve greater efficiently for nuclear fusion experiments. The Optometrist Algorithm’s design is to facilitate the selection of various parameters for an experiment, to winnow out experiments that could be dangerous or useless. Complementing the Optometrist Algorithm cooperative capacities lies also in the field of gaming, where Advanced Chess operates by exploring the possible move space that a human player can undertake against another pair of human-machine players.

         These elements of unpredictability and discovery also display another disquieting dimension, where the swapping of unpredictability becomes exchanged for a different form of predictability and control, one where the perpetuation of socio-cultural circuits of biases, discrimination and inequalities are still at large. We find Machine Learning used to reinforce human biases as exemplified by the infamous 2016 paper from Chinese researchers Xiaolin Wu and Xi Zhang. The researchers trained a neural network to construct inferences about ‘criminality’, based on over thousands of facial images. They trained a neural network on images of 1,126 ‘non-criminals’ culled from official Chinese ID photos found on the web, and another 730 ID photos of convicted criminals supplied by courts and police departments. 4

     

       The study triggered a torrent of accusations, leveling the concern the study was an update to school of criminal physiognomy in the 19th century that correlated shapes of jaw, foreheads, size of eyes as indicators of a subject’s primitive criminal characteristics.

          This worrying trend of increased integration of neural networks has been adopted by several police departments in the United States warrants further vigilance. ‘Predictive Policing’ is already employed by half of Police Departments in the U.S. Systems through software packages such as PredPol, that uses boats its usage of ‘high-level mathematics, machine learning, and proven theories of crime behavior.’ 5 Bridle points how this employment of Machine Learning continues a long thread of technology operating as a vehicle for perpetuating racial, ethical and gender inequalities, hearkening Benjamin’s infamous observation every document of civilization, is also a document of barbarism.

     Another important target for Bridle becomes the trend of ‘Big Data’ that has been blithely touted to inaugurate a paradigm leading to an “End of Theory.” 6 This particular position became enshrined in the 2008 article featured in Wired Magazine that espoused a belief that enormous amounts of data collection render the traditional scientific process obsolete. According to the article’s writer Chris Anderson, the agglomeration of data discards the need to build models of the world and test them against the sampled data; rather the colossal power of computing clusters would be able to process the data sets that would inevitably lend to the idea that numbers and data themselves would produce truth(s).

         One of the industries demonstrating the flawed promise of Big Data Solutonism is the pharmacological, where what is known as Eroom’s Law (The infamous Moore’s Law backwards)  underlines the paradox of advancements in research and development and technology. Eroom’s Law demonstrates that the cost of developing a new drug doubles approximately every nine years albeit, R&D costs of the pharmaceutical industry increased nearly 100 fold between 1950 and 2010. Even with the advance of a motley of techniques that reduced the difficulty in synthesizing and screening new chemicals, and an arsenal of computational tools that aided the design of new drugs, the silver lining in the global health fight isn’t found within advancing technology. 7

       Importantly, Bridle’s chapter on Climate weaves important considerations concerning the interplay of computation, complexity, and cognition. It is also here Bridle emphasizes the necessity of comprehending the need of preserving long held knowledge channels and banks that are increasingly becoming subjected to monoculture.

       Bridle identifies the significance of reserved diversities such as seed banks, most notably the Svalbard Global Seed Vault, a global biodiversity vault based on the Norwegian Island of Spitsbergen that is estimated to contain 968,000 seed samples from all over the world in the face of environmental degradation.8 The Seed Vault is a repository of knowledge, and ways of knowing that are preserved in the face of increasing monocultural. Thus,as Bridle underlines the climate crisis that confronts us is on a multiple fronts a“crisis of knowledge, and of understanding; it is a crisis of communication, and of knowing, in the past, the present, and the future.”  Beyond the Seed Vault we are also coming to grips with the imprints and traces of Climate Change that requires our understanding of it beyond a mere constellation of computational models, distributed systems of sensors, and exabytes of data.  Climate Change compels us to grasp  the concept of ‘network’ more profoundly than ever, where are modes of seeing and sensing are still not adequate to the task of a world driven by nonlocality and nonlinearity.  Importing Timothy Morton’s term ‘hyberobject’, Climate Change “is a phenomena or thing that surrounds us, envelops, and entangles us, yet is precisely what is literally too big to see in its entirety.” Yet, it is also the role of another hyperobject: The Internet that at one level maintains the seams of communication and connected lives distributed globally, and on the other level intensifies a crisis of understanding in the face of a climate crisis accelerated by energy consumption and a deluge of information.

       Even though,Bridle doesn’t spell out an explicit strategy or manifesto for action, he still renews and animates his push towards an ethos of ‘Guardianship’ as inherited from the 1970’s Atomic Culture. It is an ethos that still intends to mitigate our harm in the present and still conceive of a present responsibility for future generations. Even within the clasp of a looming uncertainty, it does still remain behoove of us of to speak and engage with what lies ahead. It is incumbent upon us to invest in our agency in the present and to remain wary of the design principles constitutive of our everyday gadgets, applications and systems. Ultimately, it entails reimagining possibilities that extend beyond the economy of screen and algorithm, beyond the binary deadlock of this world, and to immerse ourselves in the Cloudy formations of uncertainty. 


Works Cited

  1. Solnit, Rebecca. “Woolf’s Darkness: Embracing the Inexplicable.” The New Yorker, The New Yorker, 18 June 2017, www.newyorker.com/books/page-turner/woolfs-darkness-embracing-the-inexplicable
  2. Griffiths, Alyn. “Drone Shadows by James Bridle Evoke Unmanned Machines Overhead.” Dezeen, Dezeen, 29 Apr. 2014, www.dezeen.com/2014/04/29/drone-shadows-graphics-james-bridle-designs-of-the-year-2014/
  3. Horning, Rob. “Preemptive Personalization.” The New Inquiry, 8 June 2017, thenewinquiry.com/blog/preemptive-personalization/.
  4. Wu, Xiaolin, and Xi Zhang. “Automated Inference on Criminality Using Face Images – Semantic Scholar.” 2016, www.semanticscholar.org/paper/Automated-Inference-on-Criminality-using-Face-Wu-Zhang/1cd357b675a659413e8abf2eafad2a463272a85f
  5. Anderson, Chris. “The End of Theory: The Data Deluge Makes the Scientific Method Obsolete.” Wired, Conde Nast, 2008, www.wired.com/2008/06/pb-theory/
  6. Botz, Bálint. “Moore’s and Eroom’s Law in a Graph -Skyrocketing Pharma R&D Costs Despite Quantum Leaps in…” com, Medium, 13 Sept. 2016, medium.com/@BalintBotz/moores-law-and-eroom-s-law-in-a-graph-skyrocketing-pharma-r-d-costs-despite-quantum-leaps-in-5b6bd330484
  7. “What Is PredPol.” PredPol, 30 Nov. 2015, www.predpol.com/whatispredpol/
  8. Svalbard Global Seed Vault.” Crop Trust, www.croptrust.org/our-work/svalbard-global-seed-vault/

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