This is a revised version of a talk I gave at the 20th conference of the Society for Philosophy and Technology in Darmstadt, Germany, on June 16, 2017.
When museums started to exhibit historically significant computing machines in the late 1970s, two major problems became immediately apparent: the problem of preservation and the problem of display. The problem of preservation asks: how can we preserve computing machines so their historical significance can be experienced by future generations? The problem of display asks: how can we structure this experience visually and spatially? While both the problem of preservation and the problem of display are first and foremost practical problems, they have latent philosophical implications. With Philip Agre, I propose that an investigation of these implications can not only enrich the philosophical discourse but also inform a critical technical practice1 which in this case is also a critical curatorial practice.
The pragmatic solution to the problem of preservation, for most institutions collecting and exhibiting computing machines, are software-based strategies like portation and emulation. While these strategies come with their own set of problems, they are commonly perceived as the best possible compromise between authenticity and viability.
The pragmatic solution to the problem of display, on the other hand, seems less agreeable. Most institutions still arrange computing machines in a simple chronological fashion, disconnected from the electrical grid, silent, and confined in dimly lit glass cabinets, creating what is essentially a white cube full of black boxes framed by a narrative that does not even require the presence of the exhibited machines themselves. This practice prevails even in the omnipresence of machines of unprecedented complexity, particularly from the domain of artificial intelligence, whose role a critical curatorial practice needs to address.
I argue that one reason for this neglect of the problem of display is the ontological constitution of the exhibited machines themselves, or, more precisely, a lack of critical vocabulary suited to describe a machine’s relation to another machine, a thing’s relation to another thing. Hence, recent philosophical frameworks addressing this inaccessibility could be said to indirectly address the problem of display as well. More specifically, I claim that object oriented ontologies, if we take them seriously and literally (and with a grain of salt), can serve as a speculative principle for exhibition design, notably for the design of exhibitions of computing machines.
This is of course not an entirely novel idea: the visual arts discovered object oriented ontologies early. As one article half-ironically states: “For cutting-edge artists looking to lend their work some conceptual heft, Object-Oriented Ontology has become the faddish successor to such previous intellectual trends as structuralism and postmodern theory.”2 This summarizes the problem well: as a theoretical framework for the visual arts, object oriented ontologies remain secondary and descriptive (and always a little pretentious), rather than informing any initial curatorial decisions.
A brief disclaimer: I use the term object oriented ontologies as an umbrella term here to conveniently address a variety of really very different theoretical frameworks that nevertheless have the one common goal of re-investigating the object-object relation. Furthermore, I embrace much of the criticism brought forward against object oriented ontologies as a somewhat over-hyped academic trend, “the thing that happened after poststructuralism”3, as Alexander Galloway writes.
Specifically, I tend to side with Andrew Cole in arguing that the rejection of “correlationism”4 in many object-oriented ontologies relies on a selective and/or narrow reading of Kant. As Cole writes: “Kant’s entire Critique of Judgment […] is nothing if not an exercise in extending the possibilities of thinking noumena of various kinds: positive, causal, worldly, natural, human, and divine. He tells us that to think these noumenal realities, no matter how mundane or sublime, you have to make up your own concepts and, in short, use whatever imaginative means you have at your disposal.”5 Also, I strongly believe that the marriage of materialism and vitalism is a mesalliance in the best case, and an oxymoron in the worst. The computer is not a living thing, and nothing (ethically or otherwise) is gained from treating it like one, no matter how much “energy” is “pulsing”6 in its circuits.
So, why bother then? Why not be pragmatic? Do we really need the constraints of an academic philosophical framework to address the problem of display? More specifically: even if we do, what is left of object oriented ontologies if we disagree with one of their most basic premises, the premise that there even is a philosophical problem that needs to be addressed? What I suggest is to look at methods rather than objectives, at phenomenology rather than ontology.
It is a trivial observation that the computer is not your everyday object but comes with many additional “metaphysical subleties”. When we exhibit computers, these additional “metaphysical subleties” are amplified. Specifically, what is amplified is the fact that the computer is “a means for the mechanization of mental labor”7, as Frieder Nake has put it. Exhibiting computers thus means exhibiting materialized thinking. Even worse, it means exhibiting potential materialized thinking – after all, the computer itself does not equal its use for the computation of a specific algorithm or the implementation of a specific piece of software. Instead, it provides a universal (in the sense of Turing) framework for the materialization of thinking. Likewise, the goal of any exhibition is to materialize, visually and spatially, historic and systematic thinking about what is being exhibited. An exhibiton of computing machines thus has the difficult task to materialize thinking about objects that are themselves frameworks for the potential materialization of thinking.
So, what can we adopt from object-oriented ontologies that makes this easier to deal with? I think it is worthwile to consider the notion of an “alien phenomenology” that I take from Ian Bogost’s practice-oriented flavor of object-oriented ontology8, but which resonates implicitly throughout Graham Harman’s work as well9.
In addition to Harman, Bogost derives the concept of “alien phenomenology” from Thomas Nagel’s idea of an “objective phenomenology”, developed in his famous essay “What It’s Like To Be a Bat”10. The goal of an objective phenomenology, Nagel writes, would be to “describe, at least in part, the subjective character of experiences in a form comprehensible to beings incapable of having these experiences.”11. The only way to accomplish that, Bogost adds, is by means of analogy: “The bat is like a submarine.”
This is, of course, the easy way out. The analogy conveniently releases us from the burden to think the unthinkable by letting the trope do the heavy lifting. However, in many ways, the bat is not like submarine, and the analogy only works because it immediately falls back to the original problem. In other words: to say “the bat is like a submarine” only makes sense if we already know that the actual problem is the impossibility to think a thing’s perspective on the world. We are thus right back where we started, and reminded of the fact that, as Andrew Cole says, we might just as well “consult [our] local analytic philosopher, who will tell [us] that metaphysical mistakes are mistakes in natural languages”12.
I would like to argue, however, that the “analogical approach” simply does not go far enough. That it does have merit if we approach the concept of analogy from a more technical perspective, a perspective more appropriate for our object of interest, the computer. The goal would be an “alien phenomenology” which is alien in the Brechtian sense, a defamiliarized, technical perspective which nevertheless has something to say about both itself and the real world.
To do this, we will turn to a very specific field of computing, which nevertheless has broad implications for the problem at hand: machine learning, more specifically generative neural networks.
Neural networks were famously first proposed as a computational method by McCulloch and Pitts as early as 194313. Approximately seventy-five years later, with the advent of computers capable of processing very large data sets in parallel, they finally became practically viable as well, and have since spawned a multi-billion dollar industry and groundbreaking research in computer vision, natural language processing, and other disciplines.
Most neural networks are trained on a large dataset to solve classification problems. Through simple technical manipulation, however, they can be instructed to also generate perceptually meaningful new data from learned patterns – images, text, sound. In a generative adversarial network, for instance, two neural networks compete with each other: a generator and a discriminator. The discriminator tries to learn if an image was produced by the generator or if it is part of the original training set, thereby constantly “encouraging” the generator to produce better images.
Importantly though, the latent space sampled by such a generative adversarial network can be described as an analogical space where the produced literal images are also analogical “images” which, as a set, constitute an analogy of the machine’s perspective on the world. Unlike in the analogy “the bat is like a submarine”, instead of shifting all the complexity to the trope, a multitude of images empiricially approximates the machine’s perspective on the world.
What does this imply for the problem of display? If we, at least in part, are able to analogically approximate the machine’s perspective, as demonstrated for generative neural networks, this means there are more things to exhibit than just the computing machines themselves. In fact, there are almost unlimited supplementary objects which we could use to augment the exhibited machine and thus enable the experience of radical difference of experience that alien phenomenology proposes. Extending this idea into a general speculative principle for exhibition design then means: understanding the computer as a thing whose being is only sufficiently described as a producer of other things, as a means of production. Curatorially, this implies the task of identifying, even generating artifacts of computation which provide the same empirical lense into the machine’s perspective as the generated imagery for neural networks, and treating them as proper things. Not one artifact, not two, but as much as possible, hundreds, thousands, to show what it’s like to be a computer – an experience which can indeed only be approximated analogically, but approximated more closely the more artifacts the analogy encompasses. Philip E. Agre, “The Soul Gained and Lost. Artificial Intelligence as a Philosophical Project,” Stanford Humanities Review 4, no. 2 (1995): 1–19.↩ Dylan Kerr, “What Is Object-Oriented Ontology? A Quick-and-Dirty Guide to the Philosophical Movement Sweeping the Art World,” 2016, http://www.artspace.com/magazine/interviews_features/the_big_idea/a-guide-to-object-oriented-ontology-art-53690.↩ Alexander Galloway, “Assessing the Legacy of That Thing That Happened After Poststructuralism,” Blog, Alexander Galloway, (2015), http://cultureandcommunication.org/galloway/assessing-the-legacy-of-that-thing-that-happened-after-poststructuralism.↩ Quentin Meillassoux, After Finitude. An Essay on the Necessity of Contingency (Bloomsbury, 2010), 5.↩ Andrew Cole, “Those Obscure Objects of Desire,” Artforum, n.d., 318–23.↩ Jane Bennett, Vibrant Matter: A Political Ecology of Things (Durham, NC: Duke University Press, 2010).↩ Frieder Nake, Ästhetik Als Informationsverarbeitung. Grundlagen Und Anwendung Der Informatik Im Bereich ästhetischer Produktion Und Kritik (Springer, 1974).↩ Ian Bogost, Alien Phenomenology, or, What It’s Like to Be a Thing (University of Minnesota Press, 2012).↩ Graham Harman, The Quadruple Object (Winchester: Zero Books, 2011).↩ Thomas Nagel, “What Is It Like to Be a Bat?” The Philosophical Review 83, no. 4 (1974): 435–50.↩ Ibid., 449.↩ Cole, “Those Obscure Objects of Desire.”↩ Warren S. McCulloch and Walter Pitts, “A Logical Calculus of the Ideas Immanent in Nervous Activity,” The Bulletin of Mathematical Biophysics 5, no. 4 (1943): 115–33.↩
Philip E. Agre, “The Soul Gained and Lost. Artificial Intelligence as a Philosophical Project,” Stanford Humanities Review 4, no. 2 (1995): 1–19.↩
Dylan Kerr, “What Is Object-Oriented Ontology? A Quick-and-Dirty Guide to the Philosophical Movement Sweeping the Art World,” 2016, http://www.artspace.com/magazine/interviews_features/the_big_idea/a-guide-to-object-oriented-ontology-art-53690.↩
Alexander Galloway, “Assessing the Legacy of That Thing That Happened After Poststructuralism,” Blog, Alexander Galloway, (2015), http://cultureandcommunication.org/galloway/assessing-the-legacy-of-that-thing-that-happened-after-poststructuralism.↩
Quentin Meillassoux, After Finitude. An Essay on the Necessity of Contingency (Bloomsbury, 2010), 5.↩
Andrew Cole, “Those Obscure Objects of Desire,” Artforum, n.d., 318–23.↩
Jane Bennett, Vibrant Matter: A Political Ecology of Things (Durham, NC: Duke University Press, 2010).↩
Frieder Nake, Ästhetik Als Informationsverarbeitung. Grundlagen Und Anwendung Der Informatik Im Bereich ästhetischer Produktion Und Kritik (Springer, 1974).↩
Ian Bogost, Alien Phenomenology, or, What It’s Like to Be a Thing (University of Minnesota Press, 2012).↩
Graham Harman, The Quadruple Object (Winchester: Zero Books, 2011).↩
Thomas Nagel, “What Is It Like to Be a Bat?” The Philosophical Review 83, no. 4 (1974): 435–50.↩
Cole, “Those Obscure Objects of Desire.”↩
Warren S. McCulloch and Walter Pitts, “A Logical Calculus of the Ideas Immanent in Nervous Activity,” The Bulletin of Mathematical Biophysics 5, no. 4 (1943): 115–33.↩