Computational Culture

a journal of software studies

Editorial information

    Nicolas Salazar Sutil

    Fellow in Digital Performance University of Leeds

    Publication Date
    28th November 2017

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Section Editorial: Human Movement as Critical Creativity: Basic Questions for Movement Computing


This text poses a number of basic questions to the Computational Culture reader, and beyond, concerning the computation of human movement. The formulation of these basic questions (and broad problems) hinges on the need to better understand the nature of creativity, which according to this author, may be a key driver in the emergent field of research known as Movement Computing. These “basic questions” all gravitate around a prime concern, which is to critique the way in which machine computers affect movement-based creativity, and movement-based thinking. In addition to providing a general picture of critical literature orbiting this largely practice-driven field, and as well as introducing the reader to the two other essays and commentary section included in this issue of Computational Culture, this essay argues that Movement Computing is a mode of computation that embraces messy and open-ended work, and that it can be adopted as a framework for transdisciplinary research across a number of embodied and computer-based practices (beyond Dance and Computer Science). In this broadening context, the essay seeks to give more definition and priority to the critical and ethical perspectives, which according to this author are sometimes ignored in the Movement Computing research community.


How is movement?

Human movement is a medium of great complexity. Movement mediates a great number of interactional processes, including human and machine communication, transmission and knowledge formation. At the same time, movement can be an embodied medium involved with the expression and processing of thought. Before I move any further, the obvious question is: what field of research is addressing the complexity of movement as a creative medium? Is it necessary to stage an emergent field for this purpose, and if so, what kind of field might that be? Unlike Software Studies, which boasts an established academic apparatus, those working on the creative and artistic potential of computable movement have not yet staged their own field through specialized journals and publications, but have proceeded in a pre-eminently practice-based manner. Emergent theory around movement technology suggests that yet another new field is crystallizing across academic, arts and creative sectors. But what field does that practice and that theory of movement belong to, if any? That is the question that prompts the opening section of this essay.

What exactly is Movement Computing? One of several possible definitions of Movement Computing (I will attempt others) is this: an emergent or not-yet defined field that integrates embodied computing and tacit knowledge performed by the moving body with automated computation. This integration opens up interesting lines of research (for instance in the ambit of HCI, Machine-learning, Cognition, Psychology, Neuroscience), and scores of research questions and problems for this yet-to-be field. Where do I start?

There are numerous related fields that will boast an understanding of computable human movement on par with Movement Computing, for instance Performance Analysis (within the remit of Sports Science) and Morphological Computation (largely within the remit of Robotics and Prosthetics). This essay seeks to distil some of the unique characteristics that might point toward Movement Computing as a distinct emerging field of transdisciplinary research. Although I am not the first to suggest Movement Computing could be a field in its own right (Bleeker, 2017), the articulation of the motivations and ethos behind this potentially emergent field are yet to be spelled out. Hence, the timely appearance of this issue of Computational Culture.

Whilst Movement Computing is aligned with specialized communities such as the International Movement and Computing Workshops, or MOCO for short, there have not been many instances for collective publication where the effort has been to map and historicize the field, not to mention the need to probe and problematize the field at the critical level.1 This publication hopefully starts to address that dearth. This issue of Computational Culture emerged, in effect, as a result of a dialogue held in and around the MOCO 2016 workshops between Scott deLahunta and I. Others who made notable contributions to the discussion earlier on deserve an acknowledgement if only in passing, especially Marco Gilles, Kim Vincs, John McCormick and Sita Popat.

My objectives for this essay are threefold: first, to introduce the reader to the four texts included in this issue, and at once to provide an overview of these works; secondly, to contextualize some of the key ideas discussed in these pieces within the broader critical literature emerging from within movement theory more broadly. Thirdly, I would like to make a provocation in the manner of questions and problems which, in the spirit of mess and open-endedness, seek to push the envelope of Movement Computing, particularly in terms of advancing critical perspectives within this potential field.


Why question and why problematize?

Evidently, I am not posing questions and problems to Movement Computing in the spirit of mathematical problem-solving. Problems will be posed and questions will be asked over the course of this essay not because I intend to outsmart them. The problems alluded to won’t be solved. I am drawing attention to another notion of computation here which, under the auspices of creative research, is not practised in order to obtain answers, solutions, results and proof. The premise of my argument is that Movement Computation is a form of augmented creativity (more on this anon).

If the focus of this potential field is not the narrow understanding of movement as a biomechanical or motor control process, then what? Is the focus of Movement Computing not the creative affordances of movement as an ultimately transdisciplinary medium? If so, I cannot situate my argument in a discipline-specific context (for instance, dance, choreography, music or composition). The reason why I will not provide a disciplinary context here is because Movement Computing promotes creative collaboration across and beyond discipline. Not only does collaboration happen between different artistic disciplines, but also, and more typically, across sci-art contexts, and across design and engineering frameworks. Movement Computing is not an artistic field, nor indeed a scientific field. It is a field for the advancement of technologically enhanced creativity.

With this premise in mind, Movement Computing could be said to facilitate at least two inventive (as opposed to empirical) processes, applicable across a number of areas of artistic and scientific creativity. One process has to do with what deLahunta and Koch call (in this collection), “messy practices”2 (more on this anon). Secondly—and this is the very opposite of result-driven computation— Movement Computing facilitates open-endedness, a term popularized in the field by the bespoke practice of Paul Kaiser, Shelley Eshkar, and Marc Downie (The OpenEnded Group). In sum, the mode of computation I am questioning and problematizing here can be understood as an embodied technology for messy and open-ended creativity. The underlying question of this Corporeal Computing section of Computational Culture is not why we need mess and open-endedness, but how we need it. How is movement a form of creativity? I am not asking “for what purpose?”, “to what effect?”, or “in order to achieve what?” I am not arguing for the instrumentalization of creativity (and the channelling of creativity for gain or profit). Instead, I am focusing on the ongoing nature of a creative processes. My initial question is how movement becomes a modality of thinking, and by extension, a form of creativity. By creativity I mean an elusive human and non-human faculty to make up or bring into existence that which did not exist before. Movement, I will argue, is a prime force that can ultimately mediate a process of self-emergent poiesis (more on this to come).

The key point I will stress in this essay is this: Movement Computing is not only a framework for bodily and machine integration, aimed at enhancing artistic or aesthetic creativity. Movement Computing is also a critical form of creativity. One of the intentions behind Movement Computing, arguably, is not to approach computation in purely abstract terms, nor indeed in dualistic terms (hardware versus software; machine versus programme; corporeal movement versus incorporeal language). Movement Computing embraces human movement as a form of corporeal computation independent of machine computation, where software and hardware can be one and the same thing: the moving body. Movement Computing can provide a framework for synthesis, whilst offering a unique critical perspective—critical, that is, of cerebral, abstract, and disembodied models of computation.

The reason I raise critical questions and problems is thus twofold: to better understand the nature of this creativity that is defining of Movement Computing as an emergent field, and to better understand the criticality that movement-based creativity can mobilize. Critical creativity. That is the key rubric for Movement Computing, which perhaps crosses over to Software Studies. The possibility of a crossover has prompted us to put this issue together.


Is Movement Computing a field?

Even though it is in and around computer-assisted choreographic dance where the application of Movement Computing has proven perhaps most fruitful, it would be a mistake, in my opinion, to think that the field is a subset of Dance Studies in association with Computer Science. Movement Computing has a following also within the fields of Music (mostly in regards to Composition and Sound Technology), within Human-Computer Interaction (HCI), within the Digital Arts, and increasingly within Digital Performance (i.e. in respect to multimedia theatre, computer-assisted dramaturgy, electronic forms of performance art, and digital body art). Movement Computing can be characterized as a transdisciplinary effort, rather than an interdisciplinary interaction, as stated in the MOCO website (see note 2). In other words, this is not a case of putting a dancer and a computer scientist in the same room in order to provoke new knowledge in the stitches. Furthermore, Movement Computing understands the medium of “movement” as something eminently slippery. As a creative (and virtual) material, movement can take the form of image, action, sound, or even thought. This trans-media condition at the heart of movement creativity facilitates knowledge formation well outside the remit of any single artistic or scientific discipline.

Besides, the dancer and the scientist in the room need not be two different people. They can be the same person. Splitting the role of artist and scientist, creator and engineer, is a questionable act of knowledge divisionism. What guides Movement Computing, I would contend, is not interaction between one discipline and another necessarily, but the blurring of disciplinary distinction for the sake of creative synthesis. This is not to say that Movement Computing research cannot be framed in a discipline-specific way, or a conventional interdisciplinary way, as the MOCO statement suggests. Of course, it can.

To help disentangle kinetic creativity from a specific artistic discipline, I have elsewhere referred to movement-based creativity as kinetopoiesis.3 Kinetopoiesis is the making of things out of and through movement, and not just the making of literary, dance or musical pieces. Poiesis is the act of bringing forth, in a more general sense. At least in the philosophical literature, poiesis is the business of bringing something into being that did not exist before. To make things in and through movement, is perhaps the essence of the kinetopoietic act more specifically. There are countless different kinetopoietic crafts—the dancer’s, the choreographer’s, the musician’s, the composer’s, the architect’s. These are examples of professional roles devoted to creating or making things, where one of the materials of choice is typically movement. My point is that there is a creativity and a criticality in the kinetopoietic act that blurs the distinction posed by discipline, opening up the spaces for transdisciplinarity. This idea will, I hope, become clearer in the next few paragraphs.

Back in the days of the historical avant-garde, and whilst resident at the Weimar Bauhaus, Wassily Kandinsky created a series of abstract drawings from the movement phrases of dancer Gret Palucca, and claimed to have created an unprecedented type of abstract art.4 Movement researcher Rudolf Laban, who trained as an architect and a draughtsman before turning his attention to dance, famously described this very same transmedia procedure and dubbed it choreutics, arguing at around the same time as Kandinsky, that the invention of an architectural, plastic, pictorial and choreographic form is, in reality, a common “choreutic form”5. Whilst Kandinsky’s and Laban’s understanding of abstract art or choreutics was rather esoteric— both were directly inspired by Pythagorean and Platonic philosophy— kinetopoiesis is no such thing. Whatever transdisciplinarity is to be had in Movement Computing does not hinge upon a metaphysical sense of movement form, nor indeed an understanding of movement as an idea to be found in some higher plane or some Platonic sense of the real.

Several decades after Kandinsky’s and Laban’s pioneering research, American choreographer Trisha Brown elevated the art of choreographic drawing to a formal art practice, exhibiting sketches of her choreographies as gallery works. Likewise, the OpenEnded Group made visual art out of the movement phrases created by eminent choreographers, including Trisha Brown,6 which led to the subsequent computerization, the digital visualization, and the endowment of Artificial Intelligence to movement forms. Brown’s collaboration with OpenEnded Group is one specific case (out of many) where the computerization of movement forms can help exemplify a changing cultural understanding of movement as augmented creative medium. The intervention of computer technology in movement-based creativity, as exemplified by OpenEnded Group’s collaborations with a number of major choreographers, has perhaps helped demystify movement creativity, in the sense that rather than promoting an association of movement forms with esoteric philosophy, the kinetopoietic act is now a more transparent process that involves thinking across crafts, design pathways, and techniques. If kinetopoietic practices have become more transparent, it is because making movement forms, and using these to produce art pieces across different disciplines, does not necessarily hinge upon modernist visions of the unification of art, or the mystical elevation of art to a higher plane of creativity.

As Sha Xin Wei puts it, poiesis is simply dynamic thinking— “it is not so much a metaphysics but a style, a way of thinking and a making that is sensitive to ethico-aesthetic practice”.7 In a similar vein, Scott deLahunta, Wayne McGregor and Alan Blackwell speak of “transactables”, or the cross-fertilization of movement forms and notational elements from one design discipline to another. They add: “[what] facilitates this transfer of experience are structured taxonomies of the language of graphics, and patterns of experience in the way that notations either encourage or obstruct particular profiles of design activity.”8 The transactable character of kinetopoietic practice may well be transparent, and yet, perhaps for this very same reason, movement based creativity has become increasingly more complex.

In summary, kinetopoiesis is not an esoteric notion, but a way of saying that the creative process of working with movement as medium, and as material for creation, is shared. Movement creativity is a commons—it is a limitless reservoir that belongs to no-one or indeed anyone that reaches out across a number of different disciplines, practices, and technological media. As such, Movement Computing provides a framework for the exploration of the kinetopoietic act, as well as its applicability to specific artistic and scientific disciplines.


Is human movement a way of thinking?

It is useful to bring Stamatia Portanova’s notion of the “mov-objects” into this discussion.9 The mov-object is the thing itself, that which has been created out of movement. The mov-object may or may not be a work of art. The mov-object could be a tangible object like a kinetic sculpture, a drawing, an architectural space, or a mocap-based digital puppet. All these are examples of actual things— tangible and concrete works of art made out of the creative material that is movement. At the same time, the mov-object could be an intangible object, for example a choreography. The mov-object is thus virtual: it lies between tangible and intangible; between matter and thought.

To gain a better sense of how thought can be understood as a non-linguistic process involving the making of mov-objects, it is worth considering OpenEnded Group’s creative praxis once again. For these artists, the process of making objects out of movement (tangible or intangible, embodied or computerized) hinges on the attributes of movement as image. Movement is an image that is not optical, to be seen or eyed. The performance of embodied movements is a creative affair, in the sense that moving bodies typically leave invisible pathways, trajectories or wakes behind, typically known as “movement forms” (Salazar Sutil 2015). When movement forms reveal how bodies understand and make sense of their surrounding space and durational time, they can be described as “thinking images”. As Marc Downie of the OpenEnded Group puts it, “thinking images move between abstraction and figuration to be near a field with a concern for the virtual”10. Downie’s so-called “creatures” are mocap-based computer visualizations endowed with Artificial Intelligence, which feed on the creative imagination of a body, not the body itself. They also feed on an imaginary reality. In other words, the kinetopoietic act is not only a process of making art things—art objects—to put in galleries or on the stage. The kinetopoietic act is also a way of producing mov-objects of thought or “thinking images”. Making movement forms and computerizing them is a style of creative ideation, where the imagination provides a common ground, a transactable, across choreographic and computational thinking.

It is necessary to ask the question: What exactly is movement thinking? These “thinking images” that Kaiser and Downie refer to aren’t alphabetic forms of thinking, clearly not. You do not think with words, or mathematical symbols necessarily, at least not when producing these so-called “thinking images”, which are derived from moving bodies. And so, in what way can images derived from movement be characterised as “thoughts”? How does the body think in its own terms? For David Kirsch, a cognitive scientist, thinking with the body can be distilled in relation to the technique of “marking”. Marking refers to the activity of dancing a choreographic phrase in a sketchy or less than complete manner. In theatre acting, the technique is also knowing as “walking”. Both in theatre acting and choreographic dance, “marking” is a core technique used to help remember material that is intended for live performance (either in the form of choreographic movement, staged action, or text), and which, given the significance of that material to the overall piece, must be well memorized and well emphasised through the physicalized memory of the performer. Marking is an example of what Kirsch calls “physical thinking”, to the extent that this technique can be considered a gestural language for encoding aspects of a target movement; a way of priming neural systems involved in target movement; and a method for improving the precision of mentally projected aspects of the target.11 What characterizes physical thinking, I would argue, is not only germane to movements performed by dancers, and thus cannot be confined to the technique of marking alone. Physical thinking is also the embodied ability both to remember and to form expectation in a broader sense, akin to what Edmund Husserl famously called “retention” and “protension”.

One could reference Merleau-Ponty or Stiegler on the subject; however, I will refrain from doing so as I do not want to conceptualize movement. I do not wish to pursue a phenomenological conceptualization here (more on this issue anon). Consequently, I would like to consider bringing Husserl’s terms over from phenomenological philosophy to a more practical field of enquiry.

Bodies perform retention by keeping information or sensation over the course of an extended present. In other words, retention is the knowledge of where a movement comes from. You see a ball hitting a net, and a person standing before the goal in a particular bodily position, and you know, from that purely present moment, that the ball must have been kicked by the player. Physical movements come from different places, following specific trajectories. That precedence of a given movement, and the place where a given movement trajectory comes from, is knowable via the faculty of retention, or the knowledge of a movement stretched over an extended present. For instance, when performing a dance phrase, a progression is typically performed, sometimes linearly, over the course of which a physical effort is extended for the course of a duration. Choreographic retention is the capacity to understand where your dance movement or position comes from (that is, from what previous position, previous move, or previous bodily effort). You do not necessarily need to remember this precedence in a representational way, that is, via a mnemonic tool (a recording or a notation). Retention is not the same as memory, insofar as it lies in a perceptual and also physical plane of present experience. Retention is not a flashback of something that happened in the past, but an “appresentation”, as Husserl would call it, a means of bringing the present forth, a way of grasping an event from the immediate present and presence of the body. Thus, bodies literally re-member. Each body member (each part and organ) can contribute to the performance of retention, given the capacity of the whole body to grasp movement in an immediate way.

Bodies can also generate a sense of how movements might unfold following a given event. In sum, the body thinks in and through the processes of retention as well as through the anticipation of the next move. Even when a moment has yet to be perceived, the body can create an expectation, a sense of what will happen next. This sense of anticipation is what Husserl refers to as protension.

When a computer facilitates this process of retaining and anticipating motor action, what is being prosthetically enhanced is not the body itself. Rather, what is being prosthetically enhanced is movement. Movement Computing is a motion prosthetics (as opposed to a body prosthetics). Movement prosthetics function as autonomous forms, as thoughts that exist in their own terms. In other words, when a body performs protension and retention, and a thinking image is derived from that present movement, two bodies can mark the same movement and think the very same thought. Two different bodies can perform that movement-thought with two very different anatomies. Movement thinking becomes independent from the body that conceived it. A movement-thought can be re-embodied (rather than re-presented and referenced), time and time again, which precisely what happens when different dancers interpret a given choreographic structure. And because this movement thinking is independent, that is, it exists regardless of the body that conceived it, it can be “appresented” or given a present articulation not necessarily by a human body, but also (in theory at least) by an artificial one: a robotic body, an avatar, a computer-generated animation. That is the premise, arguably, of OpenEnded Group’s so-called “creatures”, which as I pointed out earlier, are movement phrases endowed with Artificial Intelligence.

Paul Kaiser asks: “why are artificial memory and anticipation so important?” And he attempts an answer: “As we observe any event, our perception of it derives not simply from the present moment, but rather how this present event stands in contrast to what we think led up to it, or where we suspect it might be headed.” Kaiser finishes off: “In a complex event, like that of a great performance, such memories and expectations are never fixed, but are set in constant play as we continually readjust our perceptions and understanding. That’s precisely what we want our imagery to do.”12 And that is precisely what thought is, in the Husserlian sense. Thought is a playful rhythm between retention and protension, between retaining and anticipating. Thought is what fills that gap, locking both the precedence and imminence of a movement to an immediate present.

Movement thinking also relates closely to an embodied form of diagrammatic imagination, where diagrams are “marked”, that is, where they are learned by physical means. An actor “walks” the scene, when he or she is simply marking locomotional movements to help memorize both the blocking and text of a given scene. Unlike the embodied diagrams of actors and dancers moving on stage, the diagrammatic imagination found in philosophy, mathematics and computing is abstract. The complexity and function of diagrammatic imagination varies extensively, but there is a common creative ground here, facilitated by the kinetopoietic act. This ground opens fruitful cross-disciplinary relationships that Movement Computing can exploit. In other words, although a computer cannot perform retention in a physical way—a computer cannot mark a series of steps in the way a dancer does— and although a machine cannot anticipate the next move by physical means, movement thinking can be formally described, categorized, and it can be ultimately given formal representation in languages of movement, being thus prone to automated forms of computation too.

And here is the rub. Because movement thinking is embedded in physical life, and other modalities of thinking tend not to be (particularly when thought is tied to symbolic language), movement thinking is also a framework for criticality. From movement thinking, you can adopt a critical perspective that problematizes the dominance of disembodied ways of thinking. It is possible to think critically from the moving body, to the extent that thinking in and through bodily movement is a welcome break – a crisis—from cerebral thought.

By the same token, movement thinking establishes a fundamental rupture from alphabetically or numerically written thought. Movement thinking has no widely accepted and lasting form of inscription, which is why the practice of choreography, according to James Leach at least, “demonstrates the possibilities for sustained critique”13. This is the case not only because choreography is an ever-varied and ever-changing possibility for the inscription of dance movement, but also because choreography involves the creative invention of systems of graphic expression for movement that can be critical of alphabetic writing. Choreographic writing challenges the idea that alphabetic writing is the sole or dominant medium for the scripting of thought. In summary, movement thinking and choreographic writing are inherently critical, to the extent that they pose alternative ways of thinking and writing thought.


Can you compute with your body?

Rolf Pfeifer and Josh Bongard have pointed out in their book How the Body Shapes the Way We Think (2006), that the fundamental need for categorization, which is so central to linguistics, mathematics, and computation, does not stem from brain activity alone, or from the abstracting process typical of formal languages. In other words, categorization does not stem from an intellectual capacity to distinguish abstract categories of language (be they linguistic, mathematical or computational). Categorization is also a system of differentiation performed by the physical body. As Lakoff and Johnson wrote, the embodied mind poses a critical challenge to Western epistemology, to the extent that embodied thinking is typified by the “inseparability of categories, concepts and experience.”14

Categorization happens as a matter of course in the sense that a human body is, anatomically speaking at least (and bearing in mind all the different modalities of human bodies), a structure that is parsed, sized and shaped in a species-specific way. In other words, categorization starts with the anatomical distinction of body parts and bodily movement. There are various different motor actions in the reservoir of human movement, all of which are categorically different one from the other. Walking is categorically different from running. You do not need to explain this difference in linguistic categories, that is, by writing down the words “walking” and “running”. You can just perform the difference. On the basis of this tacit differentiation of movement due to anatomical and kinematic conditions of motor activity, human movement can be later categorized in more formal ways. From the ground zero level of the moving body, one can start to make movement alphabets, movement words, movement phrases, movement languages, movements techniques for dance, as well as movement programs for machine computation. From non-formal categorization to formal categorization. Whether or not there is a continuous transition from one to the other is a critical question for Movement Computing. Unfortunately, this is not a question I can pose here without spilling beyond the rather limited scope of this essay, which is why it must be mentioned only in passing.15

Morphological Computing, and the same could be said of Movement Computing, raises a critical point particularly in terms of understanding the narrow computational sense of software. A Morphological Computing expert might argue that human bodies are already “soft”. So-called soft bodies are programmed not by a language or code agent, but by the body’s anatomical morphology, intelligently programmed by evolution, or indeed human engineering. As Hauser et al have pointed out, “the body is not a device, which is deemed to merely drag the brain around, but rather it is highly involved in computational tasks.”16 There is no software/hardware split here; no soft/hard dualism. As Pfeifer and Bongard have argued, Morphological Computing highlights “the intrinsic dynamics of the physical embodied agent, which in themselves, provide a memory function: behavioural sequences need not be stored internally but they simply take their course.”17

In other words, the body does not need a rationalizing brain to compute—indeed, you do not need a brain at all to think. Vegetal intelligence proves this. Plants are smart at the morphological level, inasmuch as they can perform tasks that can be defined as “computational” (in the extended sense of the word). Plant smartness hinges on the simple fact that evolution has determined a plant’s anatomical shape in order to solve problems posed by its environment. A fascinating juncture in our human early chordate ancestry, at least according to neuroscientist Rodolfo Llinás,18 is the tunicate or sea squirt (Ascidiaceae), a marine creature that lives its adult life as a sessile, filter-feeding tube. The adult sea squirt lives rooted to the floor by its pedicle (like a plant). The larval form of this creature, however, is free-swimming. In fact, it is equipped with a brainlike ganglion as well as a primitive nervous system, which it then absorbs (or eats up), after it buries its head and reattaches itself to a base once again. At this point, the tunicate becomes plant-like once more. An evolutionary juncture between sessile and motile, tunicates display two very different modes of movement— brainy and brainless. The plant-like adult does not move in the same way the larvae do, but it grows directionally. Such is the tropism or movement of plants (not to be confused with growth). I wonder why the tunicate has evolved in such a way. Why has it not discarded either one intelligence or the other in its evolutionary journey?

The human body is smart in its own morphological way. Human body parts typically come in ones, twos and fives (although not always). My body has one brain and one nervous system to centrally control motion, volition and individuation. It has two hands, two arms, two legs, two feet, two eyes, two ears, two nasal orifices, consolidating an intelligent symmetry that predisposes my body for life in stereo space. In other words, the manner in which my body resolves problems or performs tasks posed by three-dimensional space (in time) are typically resolved by anatomical bipedalism, bimanualism, biopticalism. My body has five fingers. Pentadigitism predisposes my hand for prehension (and apprehension), akin to what Juhani Pallasmaa calls the “thinking hand.”19 From a morphological computing point of view, the hand could be said to “think” given the way it is anatomically determined, not because it is controlled by a brain, nor because it is capable of communicating signs and writing symbols. The hand is multifunctional, and has evolved to be emancipated from locomotor functions, that is, from crawling. The hand was liberated, if you like, so as to be able to perform communicational functions. And yet, the hand is digital before you learn the abstract notion that is “number”. Fingers solve problems posed by objects in stereo-space— they perform morphologically, which is why the smartness of the hand is embedded in the anatomy, and in the affordances of embodied motor action. The hand has digits before you start using these to count from 1 to 10— before fingers are used as devices for “digital” calculation and computation in a mathematical sense. Before automated technology intervenes, the hand is already a pentadigital smart tool. This morphological modality of computation is at the heart of smart and pliable body design, and not only in robotics or prosthetics, but also in the field of Movement Computing.

A critique of software languages is being pried open here. It is necessary, I argue, to continue challenging the conventional idea that Software with capital ‘S’ is a language-based agent separate from the lived-in body. There is no Software with capital ‘S’ and in the singular, only software in the plural. There are many modalities of software, some found in language form, some found in the soft body. It is true that well-known dance software such as LifeForms, Isadora, LabanWriter (and also Field, which is not strictly speaking used for dance) are automated tools, external to the body. However, these software tools have been conceived, arguably, as prosthetic extensions of movement thinking. The assumption here is that dance software is expanding an intelligence already found in the articulate human body, and in articulate human movement. Dance software typically augments, enhances, modulates, represents, or helps teach and learn the tacit skills, the embodied skills, of a dancer or choreographer. Even before the machine computer intervenes, the dancer’s body is already a human kinetic computer, a retention and anticipation machine. The question is: can kinetic intelligence ever be externalised and automated? Or is the machine computer only providing an external rationalization of the embodied thinking of a dancing body? The body has its own capacity for protension and retention, drawing again on Husserl, which allows the body in movement to think space, in time. What are the effects of having the dancer or choreographer’s thought removed from the somatic body?

In order to memorise a choreography, all you need to do is dance, or mark the movements, at least. And repeat. You do not need to observe the movement on a computer screen; you do not need to talk and verbalize necessarily. Choreographed movement is saved in the flesh by the technique of marking (see Kirsch, above). Why is it useful to video record or computerize the movement, then? Is the integration of soft and hard within the compliant body not being unduly fragmented by the mediation of video recorded and computerized dance creativity? If some portion of that integration is definitely lost, the question is: what is gained by technology that outweighs the loss? In other words, what is so irresistible and powerful about the machine computer? What is being gained?


In order to gain what?

Heidegger, who never shied away from inventing new terms, wrote about ‘makability’. Makability is the human capacity to make things of a technological nature. My question also concerns the making of technologized movement, which orbits around what this author calls ‘technicity’, that is, the making of subjectivity itself through technique-based and technology-dependent makability.20 The question at hand is not prompting me toward the phenomenological approach to movement theory associated with authors like Don Idhe and Susan Kozel (amongst others); in fact, I would argue that the phenomenological stance tends to conceptualize categories such as body or experience, making them opaque. Phenomenologists of movement are typically interested in the epistemological value to be gained from intellectualisation, for the advancement of an academic philosophy. The reference to Heidegger is intended as a rather ironic move away from the once dominant school of phenomenological thinking within Movement Studies.

In addition to (post)-phenomenological perspectives, movement theory has been recently inflated by a poststructuralist approach. Contributing to an intellectual conceptualization of movement, particularly under the auspices of Deleuzian, Bergsonian and Whiteheadian philosophy, are a number of authors including Erin Manning, Brian Massumi, Derek McCormack, Stamatia Portanova, and many others. One of these authors (Stamatia Portanova) is also featured in this issue. Recent book collections such as Transmission in Motion edited by Maaike Bleeker (2017), and Digital Movement (2015), edited by Sita Popat and Nicolas Salazar Sutil, have also sought to link the philosophical approach to movement studies with performance theory, thus contributing to an interdisciplinary debate advanced over several decades by performance technology scholars such as Johannes Birringer, Sally Jane Norman, and Sarah Whatley (to mention but a few). These names only offer an incomplete and impartial mapping of the area that is Movement Computing and Movement Technology more broadly. These names are in no way representative of the field as a whole—indeed, a plethora of other scholarly and practical influences would have to be mapped out to make sense of Movement Technology as field in non-English-speaking research contexts. The delineation of that map is not within the remit of this contribution.

Besides, and as many writers have recently insinuated, computation is far too significant and ubiquitous a process, not least given the dependence of political and cultural systems on computer technology, to be dealt with in strictly academic terms. According to Matthew Fuller, computer skills need to be acquired in practice to empower and engage people within an increasingly high-tech world. Fuller’s effort to combine practice-based understandings of computation with critical thinking sheds light on the political and cultural ramifications of digital media and computing. “The questions posed” write Fuller and Harwood (and this can be extrapolated to the problems posed in this essay), “become less allied with philosophical concerns and the emphasis on epistemology… [and more] with social and urban forms [that] become places of computational inter-operation and experiment.”21

Through technologized movement, contemporary subjectivities are being recast. The technologization of human movement is an issue that has real-world ramifications. The big issue needs to be discussed in terms that are not exclusive to academic philosophers, but open to society at large, as human bodily movement is being roboticized, avatarized, digitally animated and computationally puppeteered in everyday life. The creativity that is being augmented by technological means ultimately needs to be a critical form of creativity, not just an aesthetic creativity. According to Fuller and Harwood, the media-as-matter approach to computation can shed light on the materiality of computation, or the manner in which computation achieves concrete expression in material life, “divulging a number of aspects of [computation’s] material practice that are often rendered conceptually and procedurally invisible.”22 In other words, the materialist approach can provide yet another branch of criticality, one less concerned by epistemology, and more with the hands-on, practical and material consequences of motion technologization at the cultural, social and even political level. As Mark Hansen would have it: “critics stand united against traditional philosophy of science and the sanitizing privilege it grants the theoretical”. And he adds, echoing deLahunta and Koch’s messy practice: it has become necessary to “assert the primacy of the practical, to probe the messy extraphilosophical logic of scientific and technological change— and its constitutive embeddedness within a thick cultural context.”23 Embedding computing within that thickness, that messiness, that practicality, is perhaps an ethos Movement Computing can strive for.

Meanwhile, the effort to conceptualize movement and render it procedurally invisible is perhaps one of the reasons why movement practitioners need to intervene critically in their own terms, through creative movement and creative coding. The problem, following from the above, is that reflexive thinking within the ambit of Movement Computing has been insufficiently critical. Movement Computing has been too concerned by aesthetic movement, by the beautification of movement by dancers and choreographers for the sake of staging it, and by technical questions concerning the technologies and languages used to augment movement-based creativity. The critical knowledge amassed in the field of computer-assisted choreography, however, ought to be divulged within a broader critical circle concerning the cultural, social and even political effects of technologized movement.

While academic philosophers are busy carving fields and wrangling about concepts that are rooted in one epistemology or another, the technologization of movement continues to materialize through practical experimentation. The question is, in very broad terms, what kind of choreographic thinking is emerging from the latest experiments, and what kind of critical creative experiments are being carried out in the name of Movement Computing more specifically? What is being gained? No doubt Scott deLahunta is in a privileged position to answer that question; indeed, his commentary (in this issue) is very much a companion to this introductory piece. For deLahunta, it seems, one of the critical questions (and problems) derived from Movement Computing is the process he and Koch call “becoming data”.

According to deLahunta and Koch (this issue), after a few decades of computer experimentation by a number of renowned choreographers using a plethora of software tools and coding practices, one of the problems faced by the research community concerns the vast amounts of existing data. Not only is this a problem concerning the diversity and idiosyncrasy of different choreographic thinkers that have used computer technology (e.g. Merce Cunningham, Trisha Brown, William Forsythe, Wayne McGregor, Emio Greco, Deborah Hay, to mention but a few). This is not just a question of how to store or retrieve the data. The problem, as I understand it, is the independence of that data. Data is running amuck.

On the one hand, there is the question of what to do with the amounts of data amassed in data-intensive projects such as Motion Bank (see deLahunta and Koch, this issue). On the other hand, there is the more critical question concerning the manner in which this data changes the very nature of the kinetopoietic imagination. In other words, whilst Motion Bank started out as a project of The Forsythe Company for research into choreographic practice (particularly the visualization of movement data), the project has grown to include the signature choreographic practices of a number of other artists, expanding the research remit, whilst also prompting interest in teaching and learning. The problem that deLahunta and Koch pose is how to deal with the complexity of data, as independent and often self-generative process. The material collected by Motion Bank researchers take on a life of their own, as movement data transitions from live choreographic knowledge, to archived material, to purely computable data, to metadata, and so on. This is not a linear becoming, by the way, but a radial one, spiralling in lots of directions at once. The question seems to be: what can be done? What are we gaining from such incalculable amounts of information and knowledge? Where is all this data going? What are the implications of ‘becoming data’? As knowledge becomes datarized, it changes fast. How can human knowledge keep abreast? Whether in Practice as Research or critical theory, how do you keep up with data?

As Mark Coniglio puts it, the human subject and its technological frame may well be having a conversation in computer-assisted performance, but “the subject and the frame are like two great actors who carry with them an equally great dose of ego.” And he adds: “when the push and pull between [human and technology] is carefully and precisely balanced – we are rewarded with a truly great work… The thing is, imbalance is nearly unavoidable,” and Coniglio finishes off by recalling the words of his long-time collaborator Dawn Stoppiello: “When you add technology to a piece, you have no choice but to spell it with a capital T.”24 The effects of machine computation on human movement, going back to Fuller’s critique, are far too significant and they are having far too transformational a role on the arts and creativity at large to be considered in opaque terms, in only academic or philosophical terms. Machines are not only performing antics to upstage the human actor. Computers are inflating and exploding human creativity to a point that is hard to comprehend, and hard to critique, not least given the amounts of information, of data, that a technological machine can churn.

William Forsythe and his company showed just how complex movement forms can get. Forsythe showed this in his Improvisation Technologies: A Tool for the Analytical Dance Eye (1999), and later in Synchronous Objects (for One Flat Thing, reproduced) (2000) exposing in both cases, and in equally neat visual manner, just how complex the human capacity to make choreographic information can be. It is not that the human capacity for kinetopoiesis is being dreamed up now in a more intelligent way by computers, or that computer-assisted choreography is producing better works, or better practitioners. The question has to do with the degree of complexity that we can now visualize mercy of video technology and computer technology, and the effects that this complex way of seeing and knowing movement is having on creative practices and critical thinking.

Even at the outset of movement computation as a creative discipline, when Merce Cunningham first incorporated machine computers and software in his choreographic practice, the writing was on the wall. Cunningham had this to say about LifeForms (software): “it is not revolutionizing dance but expanding it, because you see movement in a way that was always there— but wasn’t visible to the naked eye.”25 In response to her collaboration with Cunningham, and also in response to a CNN report about LifeForms whose headline read: “finally technology is coming to the rescue of choreographers,” Thecla Schiphorst argued: “I never imagined technology rescuing choreographers. It’s really the opposite: the nonlinguistic knowledge inherent in physical training is a richly technical world that can inform technological development. One reason LifeForms operates so well is that our bodies work so well.”26 Since the tool trusts the smart body, LifeForms works well, at least for practitioners that accept working with simulations of the anatomical body. Personally, I prefer the more abstract stimulation of movement ideas favored by OpenEnded Group, whose Field tool offers a non-representational and non-photorealistic framework. My point is that both LifeForms and Field work, depending on user preference, by trusting the well-functioning computing embedded in the body.

Maybe what is gained by computerized movement is a sense of an impossibly long expansion, a creative mess so messy and so open-ended, we no longer understand it in one-size-fits-all theoretical blankets. It is not only that we do not fully understand the creativity exploding mercy of data-churning computers—some of us no longer care to fully understand. That is, conceivably, the biggest gain. Perhaps we no longer care to rationalize all this data, all this information, and all this knowledge. Technologization of movement might well be driving not only the demystification of movement creativity, driving us away from the esotericism of Kandinsky and Laban, whilst kindling in some of us a very real and material sense of awe. We are becoming post-rational, at the mercy of the same machine that was supposedly invented for utmost control.

Perhaps this juncture between embodied and automated computation is affording not only an augmented critical creativity, as I have suggested here, but something deeper still, something akin to what Colombian mathematician and philosopher Fernando Zalamea calls “expanded reason”. Expanded reason is no longer reduced to language. “Reason reduced to language” writes Zalamea, “has limited the spectrum of human understanding […] Complexity opens an extended space (topos) where a pendular swing from language and imagery, [is] attentive as much to their transits as to their obstructions, [and this] permits us to better point to the diversity of reason.”27 Reasoning is already found in the morphological body, in the thinking hands and the smart legs, in the articulate motion of living bodies, in the swinging dancer.

In sum, if the body is one source of mess (the mess left by sensation, inner intention, intuition, empathy, effort), the computer adds a mess of its own. The computer’s mess has something to do with the volumes, speed, and complexity of computer-generated data, not to mention the mess of computer languages, code, and manufacturer systems. Then there are those “messy practices” that deLahunta and Koch (in this issue) refer to, which concern the practical relations between human and machine. Two messy worlds mate, and it is up to someone to make sense of the offspring. The problem for Movement Computing, it seems, is that the level of mess is such, there is no time to stop, and possibly, if necessary, resist. Again, the question of ethics looms large. At the end of the day, real-life never presents problems in well-formulated academic structures. Indeed, real-world problems are more like messy situations. If so, the mess and open-endedness that characterizes Movement Computing practice is perhaps a tell-tale sign of real-life.


Who is asking the questions? (a note on the contributions)

We have included two unique scholarly perspectives in this issue: Stamatia Portanova’s essay is philosophical and theoretical in its approach, offering a conceptualisation of movement as a means to develop critical understanding. John Stell’s contribution draws on mathematical thinking and reasoning, to explicate a non-numerical form of categorisation and computation of movement.

The two perspectives were chosen not because they are representative of two main strands of research within the field of Movement Computing. We chose these out of several works submitted, for two reasons: the complexity of the field can readily descend to vagueness, something our own call for papers, posted in early 2016, was guilty of. This is why we have decided to focus the attention on the only two papers that draw on a more or less coherent framework (that is, the mathematical and philosophical works of Alfred North Whitehead). It is not for the sake of elevating Whitehead’s work within the field that we offer these papers, but for the sake of coherence. More importantly, we chose only two contributions, as we believe there is enough here to open up more questions and problems than we can possibly handle, even as, I have already pointed out, Movement Computing often hinges on the premise that problems and questions are intended to mess computation up.

Going back to the first essay in our list, Portanova’s big problem for Movement Computing is how to compute human bodies and capture enough of the human, so that it may be exported to a CGI animation. Her question concerns the mocap data used to animate the dancing penguins in the Oscar-winning film Happy Feet. Portanova’s problem is how to compute living bodies using a technology such as marker-based Motion Capture, where kinematic data is derived from a limited number of markers attached to reference points in the actor’s body. What is needed ahead of software computation, in this case, is a spatial reference that is point-based, so that the computer may interpret and process the marker as point, that is, as a geometrical or numerical category (a coordinate value in 3D space). The basis for computerization of the body is, in this case, point-based geometrization and numericalization, which sets off a process of abstraction removing movement from physical embodiment.

Portanova’s critique is also aimed at a Cartesian sense of “corporeal nature”. For Descartes, corporeal nature is understood as any one thing that exists in the realm of the extension.

In Cartesian philosophy, the principal attribute of a body is extension (in length, breadth, and depth), which is why corporeality (or the reality of bodies) is finite by definition. And since the prime attribute of bodies is to extend in three dimensions of space, bodies can be geometrically represented. Bodies are not continuous in the Cartesian sense. Portanova’s work problematizes this version of a corporeal nature, arguing that what is real about a body is not its extension in 3D coordinate space (or in point-based geometrical space more generally), but on the contrary, it is flesh, materiality, and its messy heterogeneity. The Cartesian gambit argues that bodies are defined by divisibility, as opposed to mind, which is supposedly indivisible. For Portanova it is the other way around. The flesh is continuous, it is indivisible, whilst the intellect is the agent that breaks, fragments, rationalizes, divides and ultimately claims pure mental computation.

Echoing Bergson’s critique of the cinematographic movement image, Portanova argues that even the most sophisticated software remains inevitably trapped in the same infinitesimals, without ever reaching the ultimate goal of a totally continuous or “real” motion. This is a problem as old as Zeno. Because motion capture technology hinges on an arbitrary categorization of geometrical points referencing body markers, the less computable issue of race, which is an altogether different starting point for movement quality, is entirely effaced. Portanova’s real-world problem is this: once the movements of Afro-American dancer Savion Glover (the real-world body behind the dancing penguin of Happy Feet) is motion captured, geometrization starts a process that forgets the body’s race. One could add here that it is not only the race of a body that geometrization of movement obliterates, but its gender, its age, its life rhythms (its season, its time of day or night, its pulses). Who is asking the ethical questions that leap out as a result of this obliteration? There is no somatic and material body left, only a Cartesian corporeality known to us numerically and geometrically in a world of abstract coordinates.

If Portanova’s critique of Happy Feet is generalizable, so is the problem posed by John Stell, also in this issue. Stell’s essay gives a different nuance on the same general problem. Stell is concerned by the shortcomings of point-based geometry and topology when it comes to establishing a foundation from where to start the process of movement formalization and abstraction. Here is a problem as old as Hilbert (at the very least!). For Stell, there is a third way, which is neither rooted in geometry nor general topology. Stell’s problem is that one cannot account for experience in computational models of living bodies.

Jean Petitot has likewise argued that it is possible to bypass representation (number) when trying to formalize the phenomenological character of sensible schemata.28 Petitot thus put forward “morphological eidetics” as a philosophical framework to help solve this problem, anticipating by several decades the emergence of Morphological Computing. Petitot has argued that ideation is already expressed in morphological dynamics: in structures, patterns and shapes, that is, for instance, in the anatomical shaping of the human body, which is smart in its evolved morphology. The question, going back to Stell, is how to formalize a phenomenological account of movement, for machine computable purposes. Whilst Stell wonders how to naturalize phenomenology, how to give it a natural language, it is not the morphological approach that he opts for. Stell is impatient with point-set topological models of bodily movement, where representation of human movement does not account for a lived-in sense of space. In other words, general and point-set topology treat bodies in the same way they would treat any other real entity (as point or set). Mathematics (and mathematical computation by default) indiscriminately abstracts every aspect of a corporeal entity in terms of fundamentally re-moved categories.

In summary, although mathematical concepts such as continuity, compactness, and connectedness are represented in continuous functions, and can be understood quite intuitively if one takes nearby points to nearby points, a topological model will be as problematic as Cartesian coordinates. Insofar as topology starts from the basis of an already abstract category, Stell adds: “The topological model provides an elaborate and sophisticated language allowing us to talk about points and to distinguish open and closed sets. To use this language, however, via some computational representation— to calculate with the body— means a considerable overhead in translating back from the topological language to the body as experienced” (in this issue). The use of the term “phenomenology” here is problematic, and it may be argued that the ambition for Stell, arguably for Petitot too, is not to formalize a concept found in the branch of philosophy known as phenomenology, but to draw knowledge from real-world bodies. Philosophical phenomenology only conceptualizes the lived-in world, whereas the lived-in world is devoid of concepts. In other words, philosophical phenomenology can stand in the way, as a layer of unnecessary conceptual and philosophical mediation.

Portanova’s effort to understand how continuity is represented after mocap, and Stell’s need to understand how bodily experience can be categorised mathematically and computationally in a manner that is not strictly geometrical or topological, sets these authors off in two divergent paths, where the problem of body computation is addressed either philosophically, as in Portanova’s contribution, or mathematically, as in the case of Stell’s contribution. These forking paths are representative of the kind of divergence in scholarship I mentioned earlier. But since the questions and problems touched upon may well be generalized across philosophical, mathematical and computer science registers, it would be useful to know what these two authors have in common, and where their contrasting terminologies and registers meet. The answer is: both authors have a penchant for mereotopology and Alfred North Whitehead. This makes perfect sense, since Whitehead’s work is quite conveniently poised between philosophy and mathematics, between speculation and formalisation.

The question for mereotopology is this: is it possible to think a point-free mathematics of space? Where does mathematical space start from, if not from points? To free the mathematical understandings of space from point means that a new foundation needs to be found. That alternative foundation is ‘region’. Since Whitehead did not express his theory of regions in formal language, but only in philosophical terms, it is not Whitehead’s mereotopology that concerns Stell per se, but the formal description of this philosophical idea. The formalisation of mereotopology in mathematical language is known as The Region Connection Calculus (RCC).29 RCC speaks of regions and relations between regions, such that computation does not require metrical values (numbers). Computation, in this case, is not digital at all. Points are discrete values, the same as number and digits. Instead, regions can be represented as statements. For instance, a statement may read: two bodies are or aren’t touching. Or: a body is externally connected to another. Or: two bodies are partially overlapping, and so on. Can a machine compute with a finite set of statements rather than discrete mathematical values (points, numbers, digits)? Based on a categorisation of statements, key information about entities in space (not least bodies) can be inferred. The turn away from ‘point’ (geometry), and the move toward ‘region’ (RCC) is not only a fundamental rethink of mathematical and computational thinking, but also a critical framework, going back to Portanova’s argument. Statement-based computation questions the supremacy of a Cartesian understanding of space, as well as the early modern topological paradigm of mathematical space grounded in continuous functions.

It is hard to find a way of reconciling the mathematical and philosophical arguments included in this issue of Computational Culture, however, since Portanova is demanding much more than a naturalization of phenomenological experience in the language of mathematical or computer logic. Stamatia Portanova’s contribution raises a number of areas of corporeality that elude even RCC. After all, how do you compute race? There is something about a black body, a black dancer, whether Savion Glover or Bill T. Jones, which the technologization of movement via motion capture eludes. There is something about Glover, a tap trained dancer, and Jones, a classical and modern trained dancer, which the machine fails to read. So, this is not just a question of capturing the race of a movement, but also the education of a movement, the social class, the gender, the sexual orientation, the emotional state, the mood, the messy real-world flavours that define a movement in the lived-in world. These and many other aspects of human motion are far too important to be missed out in the technologization of movement. Stell might argue that RCC cannot possibly do what the philosopher demands, but that RCC is nonetheless a pretty good place to start, and that yes, RCC avoids the pitfalls of point-based computation.

Finally, this issue contains two contributions by Scott deLahunta and Anton Koch. Their essay provides a partial map and history of Movement Computing as a field (although they do not name it as such), as well as a general sense of who is who in this community. Given his unique insights into a number of key practices that involve the technologization of dance, and given the long and impressive trajectory of his interdisciplinary research, deLahunta is in a unique position to provide a well-informed mapping of Movement Computing. The conversation between deLahunta and Koch (also included in this issue) touches on many of the key problems and questions raised in this essay. Their debate offers a practice-as-research approach, whereas this essay has mostly focused on theoretical issues.


Just why?

Even in statement-based computing, a computer will not process a vague and open-ended statement such as: “Why?” That is the point made by the main character of the 1960s cult TV series The Prisoner. The character of Number 6, played by Patrick McCoogan, asks an infamous Supercomputer called The General the one question that will cause the machine to self-destroy: “Why?” The question is non-computable. In this rather naïve scenario, The Prisoner shows that computers cannot do everything—all they can do is compute. You can expand human creativity, but you cannot replace it. Only a human can answer the question: Why?

Why? Why is there poverty in the world? Why does life exist? Why am I here? Humans are always asking why- questions. These are non-computable questions, non-mathematical questions and non-academic questions, but these are the kind of questions that only a creative human can entertain. You cannot blame a computer machine for failing to answer a question not even humans can fathom. Why do we create? Why do we move? There are questions and more questions, and the trail careers off into an existential sort of quandary. Evidently, these are not questions for machine computers. These are questions that feed creativity. Augmented creativity. Techno-creativity out of control.



Bleeker, Maaike (ed.) Transmission in Motion: The Technologizing of Dance. London and New York: Routledge, 2017.

Coniglio, Mark. ‘Reflections, Interventions and the Dramaturgy of Interactivity, in Nicolas Salazar Sutil and Sita Popat (eds.) Digital Movement: Essays in Motion Technology and Performance. London: Palgrave Macmillan, 2015.

deLahunta, Scott. Software for Dancers: Coding Forms. Available at Accessed October 3, 2017.

deLahunta, Scott, Wayne McGregor, and Alan Blackwell, “Transactables” in Performance Research 9:2 (2014), pp. 67-72.

Forsythe, W. Improvisation Technologies. A Tool for the Analytical Dance Eye,interactive CD-ROM and book developed in collaboration with V.Kuchelmeister. Karlsruhe: Zentrum für Kunst und Medientechnologie, 1999.

Forsythe, W., Palazzi, M. & Zuniga Shaw, N. (2000) One Flat Thing, reproduced. Available at: [Accessed 14 July 2014].

Fuller, Matthew. How to be a Geek: Essays on the Culture of Software. Cambridge: Polity, 2017.

Hansen, Mark. Embodying Technesis: Technology Beyond Writing, Ann Arbor: University of Michigan Press 2000.

Hauser, Helmut, Auke Ijspeert Rudolf M. Füchslin RM, Rolf Pfeifer, and Wolfgang Maass, “Towards a Theoretical Foundation for Morphological Computation with Compliant Bodies” in Biological Cybernetics 105: 355-370, 2012.

Heidegger, Martin. Mindfulness. Translated by Parvis Emad and Thomas Kalary. New York: Bloomsbury, 2016.

Ingold, Tim. Being Alive: Essays on Movement, Knowledge and Description, London: Routledge, 2001.

Kaiser, Paul, and Marc Downie. ‘Thinking Images: a conversation with Paul Kaiser and Marc Downie”, Available at: retrieved September 15, 2017.

Kirsch, David. Thinking with the Body, in (eds) S. Ohlsson R. Catrambone, Proceedings of the 32nd Annual Conference of the Cognitive Science Society, Austin, TX: Cognitive Science Society. 2010. Pp 2864-2869.

Lakoff, George and Mark Johnson. Philosophy in the Flesh: The Embodied Mind and Its Challenge to Western Thought. New York, NY: Basic Books, 1999.

Laban, Rudolf. Choreutics. London: MacDonald and Evans, 1966.

Leach, James. “Making Knowledge from Movement”, in Maaike Bleeker (ed.) Transmission in Motion: The Technologizing of Dance. London and New York: Routledge, 2017.

Llinás, Rodolfo. I of the Vortex: from Neurons to Self. Cambridge, MA.: MIT Press, 2001.

Norman, Sally Jane. “Dancing on Occam’s Razor: Expressive Movement in/And Place” in Carla Fernandes (ed.) Multimodality and Performance. Cambridge: Cambridge Scholars Publishing, 2016.

Pallasmaa, Juhani. The Thinking Hand: Existential and Embodied Wisdom in Architecture. Chichester: Wiley, 2009.

Petitot, Jean. “Morphological Eidetics for a Phenomenology of Perception” in Jean Petitot, Francisco Varela et al (eds.) Naturalizing Phenomenology: Issues in Contemporary Phenomenology and Cognitive Science. Stanford, CA.: Stanford University Press, 1999.

Pfeifer, Rolf and Josh Bongard. How the Body Shapes the Way We Think: a New View of Intelligence. Cambridge, MA: MIT Press, 2006.

Portanova, Stamatia. Moving Without a Body: Digital Philosophy and Choreographic Thoughts. Cambridge, MA: MIT Press, 2013.

Salazar Sutil, Nicolas. Motion and Representation: The Language of Human Movement. Cambridge, MA.: MIT Press, 2015.

—.       ‘Mathematics in Motion: a Comparative Analysis of the Stage Works of Schlemmer and Kandinsky at the Bauhaus’. In Dance Research, Edinburgh: Edinburgh University Press, 32.1, 2014.

Schiphorst, Thecla. Interview with by Evantheia Schibsted ‘LifeForm’ in Wired Magazine, 1996.

Xin Wei, Sha. Poiesis and Enchantment in Topological Matter. Cambridge, MA.: MIT Press, 2013.

Zalamea, Fernando. Razón de la frontera y fronteras de la razón. Bogota: Editorial Universidad de Colombia, 2010.




  1. MOCO aims to gather academics and practitioners interested in the computational study, modelling, representation, segmentation, recognition, classification, or generation of movement information. MOCO is positioned within emerging interdisciplinary domains between art and science. Proceedings of the various MOCO international workshops, and groups discussion, are available at the community’s website
  2. Tim Ingold has argued that technology has transformed the heuristics of technique into algorithms. The “messy, hand-on business of work” retreats into mind, according to this author, and the “notion of practice has been reconfigured as the application of rational principles whose specification has no regard for human experience and sensibility”. Ingold is drawing on an 1876 paradigm of movement technology (i.e. Franz Reuleaux’s The Kinematics of Machinery), so the argument is slightly passé. Delahunta’s point is that movement technology need not be a rationalization, intellectualization or technological recasting of technique into algorithm. Creative computing is, in itself, a messy practice, a hands-on business and critical work. See Tim Ingold, Being Alive: Essays on Movement, Knowledge and Description, London: Routledge, 2001, p. 61.
  3. See Nicolas Salazar Sutil, Motion and Representation: The Language of Human Movement, Cambridge, MA.: MIT Press, 2015.
  4. See Nicolas Salazar Sutil, ‘Mathematics in Motion: a Comparative Analysis of the Stage Works of Schlemmer and Kandinsky at the Bauhaus’. In Dance Research, Edinburgh: Edinburgh University Press, 32.1 (May, 2014): pp. 23-42.
  5. Rudolf Laban, Choreutics. London: MacDonald and Evans, 1966: p. 115.
  6. See How Long Does the Subject Linger on the Edge of the Volume (2005)
  7. Sha Xin Wei, Poiesis and Enchantment in Topological Matter. Cambridge, MA.: MIT Press, 2013, p. 269.
  8. Scott Delahunta, Wayne McGregor and Alan Blackwell, “Transactables” in Performance Research 9:2 (2014) p. 70.
  9. See Stamatia Portanova, Moving Without a Body: Digital Philosophy and Choreographic Thought. Cambridge, MA.: MIT Press, 2013.
  10. See “Thinking Images: a conversation with Paul Kaiser and Marc Downie”, available at:
  11. David Kirsch, Thinking with the Body, in (eds) S. Ohlsson R. Catrambone, Proceedings of the 32nd Annual Conference of the Cognitive Science Society, Austin, TX: Cognitive Science Society. 2010. Pp 2864-2869.
  12. Ibid. n/p
  13. James Leach, “Making Knowledge from Movement”, in Maaike Bleeker (ed.) Transmission in Motion: The Technologizing of Dance. London and New York: Routledge, 2017, p. 144.
  14. See George Lakoff and Mark Johnson, Philosophy in the Flesh: the Embodied Mind and Its Challenges to Western Thought. New York: Basic Books, p. 19.
  15. Sally Jane Norman, “Dancing on Occam’s Razor: Expressive Movement in/And Place” in Carla Fernandes (ed.) Multimodality and Performance. Cambridge: Cambridge Scholars Publishing, 2016.
  16.  Helmut Hauser, Auke Ijspeert Rudolf M. Füchslin RM, Rolf Pfeifer, and Wolfgang Maass, ‘Towards a theoretical foundation for morphological computation with compliant bodies’ in Biol Cybern 105(5):355–370, 2012.
  17. See Rolf Pfeifer and Josh Bongard, How the Body Shapes the Way We Think: a New View of Intelligence. Cambridge, MA: MIT Press, 2006, p. 303.
  18. See Rodolfo Llinás, I of the Vortex: from Neurons to Self. Cambridge, MA.: MIT Press p. 21-25
  19. See Juhani Pallasmaa, The Thinking Hand: Existential and Embodied Wisdom in Architecture, Chichester: Wiley, 2009.
  20. Martin Heidegger, Mindfulness. Translated by Parvis Emad and Thomas Kalary. New York: Bloomsbury, 2016.
  21. See Matthew Fuller and Graham Harwood, ‘Abstract Urbanism’ in Matthew Fuller, How to be a Geek: Essays in the Culture of Software, Cambridge: Polity Press, 2017.
  22. Ibid.
  23. Mark Hansen, Embodying Technesis: Technology Beyond Writing, Ann Arbor: University of Michigan Press 2000, p.1
  24. Mark Coniglio, ‘Reflections, Interventions and the Dramaturgy of Interactivity, in Nicolas Salazar Sutil and Sita Popat (eds.) Digital Movement: Essays in Motion technology and Performance. London: Palgrave Macmillan, 2015, p.274.
  25. Merce Cunningham quoted on Credo Interactive website, makers of 3D character animation software Life Forms. Accessed on 7 October 2017; available from
  26. Thecla Schiphorst interviewed by Evantheia Schibsted, ‘LifeForm”, in Wired Magazine, pp. 172-3, October 1996.
  27. Fernando Zalamea, “Borders and Creativity: Perspectives from an Expanded Reason” translated by Nathan Coombs. This is the final chapter of Zalamea’s, Razón de la frontera y fronteras de la razón (Bogota: Editorial Universidad de Colombia, 2010), pp. 107-122, a book in which Zalamea expores the nature of creativity with respect to the work of Peirce, Florenski, Marey, Lispector, Veira da Silva and Tarkovsky. The translated chapter is available at:
  28. Jean Petitot, “Morphological Eidetics for a Phenomenology of Perception” in Jean Petitot, Francisco Varela et al (eds.) Naturalizing Phenomenology: Issues in contemporary phenomenology and cognitive science. Stanford, CA.: Stanford University Press, 1999.
  29. Broadly speaking Region Connection Calculus is intended to serve for qualitative spatial representation and reasoning. RCC abstractly describes regions in Euclidean space, or in a topological space, by the possible relations between one region and another. RCC consists of eight basic relations that are possible between two regions, which can be represented diagrammatically or in statement form, for the purpose of computation and computer reasoning. Based on Whitehead’s mereotopology, RCC was developed in the early nineties by members of the Computing Department the University of Leeds (David A. Randell, Zhan Cui and Anthony G. Cohn).
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