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The presence of animated objects in Performing Arts

The presence of animated objects in Performing Arts

The use of artefacts has played an essential role in the evolution of the Performing Arts. Their original appearance in the field was associated with ceremonies and rituals carried out by ancient cultures. They were used as healing and prediction items but also as objects attributed with life. Totems, stones, ruins among others were considered to be wise creatures or ancestors that could advise and determine decisions for entire communities [1].This perception of liveliness in objects is an inevitable characteristic of the human Psyche and it is based on our most primarily instincts. Thus, it has undoubtedly been a key element in the evolution of instruments and robotics. Through time, machines have been designed to imitate, simplify and embody our human chores. Although at the beginning they only executed dynamic tasks, since the digital evolution, machines have started to perform rational processes that were related exclusively to humans [2]. We can argue that through time, human kind has steered the progression of machines to become instruments that could possess autonomous life.

In the progression of technology, artefacts have influenced directly the productivity of different industries such as the telecommunications or energy. But the industry of Showcase has also understood the aesthetic potential that instruments could have on stage. There exist several examples in the arena of the Performing Arts were objects have been employed as tools but also as entities with independent presence. Such is the example of the Cybernetic explorations that study instruments with lively conducts.The concept of animation is the central focus of this research and its origin comes from the analysis of a personal project founded in the Interactive Architecture Lab under the name of “Lumina”. Lumina is an interactive installation whose purpose is to generate a sense of presence in the user. Lumina builds an intangible space represented by a cylinder of light around the user. He can subsequently modify the intensity, colour and shape of the light as he extends his hands towards and retracts away from his maximum scope. (img.1)

Img. 1: Lumina’s general concept

Lumina had a series of presentations in which an unpredicted phenomenon occurred. The installation was originally designed to be understood as a lifeless object whose intention was to shape the environment of the individuals who visited it. Instead, Lumina was appreciated by the audience as an entity with individual personality. During their experience, the users focus their exploration on Lumina’s conversational abilities. They spend their time in the experience trying to decipher the language in which our instrument communicated. (img.2) This event made me think about how us human kind as a species, possess the instinct to try to understand our surroundings and made me question the irresistible arguments that guide us to endow with animation the objects that compose it.

This research arises with the questions, Why do we, humans, possess an inherent tendency to attribute with life the objects in our surrounding? Are there specific qualities in this objects that make us think of them as alive? How have designers used this cognitive process to influence the narrative of their performances? And which are the characteristics that could influence the evolution of Lumina in order to increase the perception that she is an autonomous performative entity?

Keywords: animation, artefacts, anthropomorphism, empathy, motion, intention, environment, morphology, conversation, interactive, reactive, feedback.

Img. 2: The interaction of Lumina with visitors
Photographer: C. Cortes

2. Anthropomorphism and empathy

Cognition is the field of modern psychology in charge of studying the mental mechanisms that help us to interact with the world around us. These operations can be classified into three categories depending of the function they execute in the process of information analysis. First, there exist the mechanisms in charge of receiving the data (sensation, perception and attention); secondly, we will find the systems related to the reactions towards the received information (motivation and emotion), and lastly, will be the structures in charge of storing and analysing it ( learning, rationalising, intelligence and language). [3] These mechanisms in turn, interrelate with each other and form complex sub-systems among which we can find anthropomorphism and empathy. Through the following chapter we will research over how these unconscious operations structure the way we relate to our habitat and how they contribute to the irresistible tendency that men have to gift animation to an object.

Anthropomorphism

 

From the greek anthrophos: human and morphé: form or appearance, derives the term Anthropomorphism. Its original connotation resided in the attribution of human characteristics to the ancient divinities. It has now evolved to be used not only to assign these qualities to deities but to any other kind of non human bodies, as a whole or to any of its parts [4].

G. Romanes, Charles Darwin’s disciple, founded the field of the “Comparative psychology’ to explain how animals and humans share mental and behavioural features. On it, we are able to find the intrinsic reasons to why us humans as a species, tend to anthropomorphise the entities in our surroundings. He explains that there exist two characteristics in the human behaviour which lead this conduct. To begin with, he declares that the desire to feel competent to interact effectively with the environment is an attribute built within the human nature. Our brains are designed to try to receive and understand the information from other human thoughts. Alongside to this, studies in Neurosciences have shown that the brain regions that activate when we try to understand the behaviour of other humans are similar to the ones that we use while we try to explain a nonhuman conduct. Moreover, they explain that the same set of mirror neurones trigger when we observe an action and when we perform an action [5]. These concepts demonstrate that our primarily approach to understanding an activity, does not consider the subject executing it. Initially it only focuses on the behaviour itself.

Romanes also recognises the Aristotelian foundation where humans are distinguished to be intrinsically social beings. He states that in a person, individuality is preceded by society as men possess the need to establish social links with beings of their same species. In consequence, he explains, that it is also this inclination which drives us to “create beings” of our own species to compensate their absence in specific circumstances [6].

Anthropomorphism has been understood and applied by designers to create subjects capable to look, walk, move, talk and think like humans. However, by itself, this mental function is not capable to generate an effective social communication between two individuals. It requires the abetment of a secondary mechanism which will transfer this process of connection to an emotional plane, empathy.

Empathy

“Anthropomorphising a nonhuman does not simply involve attributing superficial human characteristics such as a humanlike face, body or movement to it, but rather attributing essential human characteristics to the agent and it is feeling the fundamental one. [7]”

Waytz, Epley and Cacioppo,2000

During the 1990’s Guthrie defined and unwavering relationship between anthropomorphism and empathy and described it to be a “perceptual and involuntary strategy” that is dependent of situational contexts [8]. Empathy is defined as the ability to discern and share the feelings, emotions and conducts of others. It is established over the cognitive mechanism known as “The theory of the Mind” which is the basis of everyday human interaction and which we develop in early stages of our growth. This doctrine refers to the capability to infer the mental states of oneself and of others minds. Psychologists refer to it as a theory because it is based on the understanding that we can only perceive the existence of our own mind as we will never have access to others. With it is how humans are able to intuit and predict the desires, beliefs and intentions of someone else’s present, past and future behaviours [8].

Empathy is primarily a social phenomenon and is the initial mental operation in which two co-specifics create an emotional connection. To a specific extent, it is the assumption in which we constitute another subject to be our own counterpart and it is through it how we are able to understand that there exist emotional similarities between each other. In their study “Empathy: Its ultimate and proximate bases.” Dr. Stephanie Preston and Dr. Frans B.M. de Wall proved that as the social links of two individuals increase, regardless of them being humans or non- humans, the levels of strangeness and indifference towards each other consequently decrease. They proposed a multilevel model in which the most basic and automatic mechanisms of emotional synchronicity evolve to what they call an “emotional shared experience”. With it they explained that as similarities between two individuals increase, the primary operations of empathy allow them to build a clear representation of the emotional state of each other, to the point in which they can actively respond to it [9]. We can argue that in a process where empathy leads towards anthropomorphism, the human like connections between and object and a man could not only refer to external physical features but to emotive ties too. This can be consciously used by creators as a design tool to determine the level of engagement between an object and its visitors.

 

Chapter II

1. Evolution of Lively objects

In order to understand life itself, Humankind has dedicated its research to develop techniques able to imitate the shapes and behaviours of the world that he lives in. “What I cannot create, I cannot understand” [10], a quote attributed to the American physicist Richard Feynman, reflects the work of generations of physicist, engineers, chemists, geneticists and others who devoted their careers to test theories and mechanisms that mimic and reproduce life in order to understand it. Dr. Minsoo Kang states while describing René Descartes theory of the creation of the world, that humans possess the inevitable tendency to create understandable models even to analyse the origin of their own existence. [11]

The earliest exercises of life mimicry date back to the ancient Greece. Automaton, arose as machines that performed an established range of complex functions according to a predetermined set of instructions, and that simulated to act by their own will [12]. They were originally used to demonstrate basic scientific principles and were driven by hydraulic and pneumatic systems. During the enlightenment period, automaton evolved and began to be used as performative prototypes. Although these examples were merely considered in their time to be comical entertainment prototypes due to the reason that they emulated basic living processes of eating, drinking, digesting and moving, we know now that they were fundamental to the definition of the history of machine technology [13]. Such is the case of “The Writer” designed by Pierre Jaquet Droz, a mechanical simulation of a boy that could write individual letters with real ink and paper and that was considered to be the predecessors of what we know today as a programmable memory (img.3). Since then, machines suffered alterations according to the discoveries that the Industrial Revolution brought along with it. The internal systems of the machines transformed to electromechanical systems that with the foundation of Cybernetics explored in a different level the recreation of lifelike bodies.

Img. 3: The Writer.

Norbert Wiener, considered to be the father of this field of study, defined Cybernetics as the research field of the communication and control of the messages given between men and machines; machines and men; and machines and machines. He believed that for inventors to possess an effective control over their machines a message should be emitted back by the artefacts in order to know that a instruction has been understood and in consequence obeyed. [14] The principles of cybernetics originate from the understanding of how the nervous system of a human being operates. Men perceive the world through a series of sense organs. This information is then processed by the brain and the nervous system which through the practice of selection, collation and storage produce an action through their effector organs. This combination of received and transmitted information is what differentiates a cybernetic system from the automata’s mechanism. By storing the information received, the current actions of a machine influence the future actions of it. Whereas in an automata, the actions performed by it have a beginning and an end.

Thus the evolution of machines began to resemble not only the external structures of life but also its internal systems. In 1948 the Psychiatrist William Ross Ashby presented his machine “Homeostat”. It consisted of four units that possessed a pivoted magnet on the top. (img. 4)These units communicated by transferring an electrical output that was proportional to the deviation of the magnet from its centre. (img. 5) This electrical current was then received by the system and by the rest of the units which will in turn decide to transfer it or not according to their inner states. By measuring the intensity of the stimuli received by each of its parts the “Homeostat” was able to adapt its behaviour and learn through a method of punishment and reward (img. 6) [15]. This project was described by Time magazine as “the closest thing to a synthetic brain man had made so far” [16].

Img. 4: Homeostat

Img. 5: Pivoted magnet of the Homeostat

Img. 6: The electrical system of The Homeostat

René Descartes in his “Discourse of he Method”, established two means to categorise machines from men. According to his doctrine the ability of speech and the flexibility in a behaviour were the characteristics that regardless the resemblance between our bodies, will always differentiate us from them [17]. Although we must consider that during his time a machine was embodied by a clockwork automata, we can argue that since the appearance of Cybernetics the imitation of life, faded the limit between the differences of humans and apparatus.

 

“Lively Artefacts” as Dr. Ruairi Glynn describe them to be, appear with more frequency in the different fields of Art. The compendium Robots and Art: Exploring an Unlikely Symbiosis sates: “The Art is not in the machine, the machine is the art” [13]. The aesthetic potential of attributing liveliness to an object is a growing tool that designers use now a days in the development of their narratives. Therefore, it is important to understand which are the characteristics, both material and intellectual that transform an object into a subject. And how as a result they can reconfigure the levels of engagement in an audience.

 

2. Animation in the physical Nature of the Object

There are many biological characteristics that would discern a living organism from an inert object. Over the years, scientists have established that reproduction, growth and homeostasis are properties of life that can be used as differentiators of animated entities. However, there exist in us intrinsic and automatic processes that have helped us identify life since the moment we were born. These are cognitive mechanisms built in the primitive structure of our intellect that we share with the rest of the animal kingdom. [18]

 

Dr. V. Zogza and Dr. Papamicahel have researched over the similarities between the innate processes of humans and animals in order to identify the mechanisms that guide our intelligence before we even develop a Theory of Mind. Humans, as any other species rely on these mechanisms to survive and identify critical actions that will allow us to discern between predators, mates or preys. This suggests that the way in which we interact with animated beings does not only occur through reasoned acts of perception such as anthropomorphism and empathy, but also through automatic instinctive mechanisms that exist in our psyche. Throughout their studies they have identified different characteristics that our intuition uses to determine life in an entity. And they refer that it is motion the primary stimuli that help us determine the animation in a subject within seconds.

Motion

Motion is disclosed by our perception when our brain identifies a change in the pattern of light being received by the retinal image. Motion perception serves a vast array of essential functions in our every day life such as segmenting the background from the foreground, identifying the distance between us and an object, estimating the direction of a moving element or defining our trajectories in order to avoid collision. Furthermore, it is also the fastest biological stimuli to identify as it only takes around 200 millisecond for Human to recognise [19].

Jean Piaget determined in his study “The four Stages of Cognitive Development” that children begin to construct a rational mental process around a subject, by distinguishing an object with movement from one without it. This shows that the process of appointing an animated subject as such, begins by determining its ability of motion [20].

Researchers on the field of visual motion perception have established that our brains analyse not only movement itself but also the reasons to why an object moves and where does it do it. Our mind uses these characteristics to identify the animation in subjects. Swedish psychologist Gunnar Johansson with his experiment “Point light experiments” (img. 7) demonstrated that perception of biological motion can be determined with the most limited stimulations and that depending on its context the information received could be enough to identify qualities of the subject beyond its movement such as its gender or intentions [13].

Img. 7: Frames from the recorded research, Point Light experiment.

Designers have understood the potential qualities of motion and the human perception to seed the idea of presence in objects. They have explored different arrays of movement in order to reinforce specific intentions on their narratives. For the purpose of this thesis we will study them through four of the categories that Zogza and Papamicahel use to determine animation in living organisms which are, motion and its dependency to the environment, intention of a motion, motion dependant of its morphology and motion for life.

 

Motion dependent of the environment

Environment is understood to be as all of the elements in the context of a subject that could affect its individual state. Before all else, Paul Szego and Mel Rutherford determined that when analysing a movement our mind considers as originally factors of the environment, the physical conditionings in which an object performs. In a terrestrial reasoning the human brain automatically takes into consideration facts such as gravity or atmospheric pressure to determine the state of animation in an object (img. 8). An example given by them is how we perceive an object that jumps to be more lively than an object which falls such as the movement of a frog against the falling motion of a leaf [21].

Img. 8: An object that defies gravity is more likely to be understood as lively.

Parallel to this, the ethologist Dr. Dugatkin states that in living organisms movement conditional to stimuli in lively entities can be classified depending on the receiving mechanisms that process the information. These can be physical or sensorial. On one hand, we will find the subjects that collect stimuli through its morphology in order to trigger motion. Such as a bird who uses its wings and the pressure of the wind to generate its movement. On the other hand, their exist the subjects which require the integration of neural processes to understand the received data and generate with it movement. For example, Dugatkin states that when an animal faces increasing body temperatures, the process of learning through observation and sensation in order to consequently move to shade would be consider as motion dependent of the environment as well [22].

 

Intention in a motion

On their paper “Visual Perception of Intentional Motion”, Dittrich, W and Lea, S, defined that if the motion of an artefact presumes to possess an intention, wether or not the goal is perceived, we will identify it to be more animated. The intention of a movement can be easily identified when while observing a scene a spectator is able to visualise the goal or the reason to why an object moves. The presence of a target or a secondary individual facilitates the understanding of an examined motion. Studies show that when an object avoids obstacles or expresses social encounter in their trajectories (img. 10), audiences are more likely to associate life to them [23]. But when a comprehensible figure that could explain the motive of a motion is absent, the essential components of movement, speed and direction, could be used by designers to illustrate it and reinforce the notion of liveliness.

 

Img. 10: Object with a target moving through obstacles

Referring back to their study, Dittrich and Lea stablished that when the speed of an object increases through time is considered by audiences to be more alive than an objet whose movement is constant or static (img. 11). This for the reason that in the psyche of a human, the perception of a motion is affected by learnt previous experiences that lead us to make assumptions. Such as that the object might be running from or to somewhere. Equivalent to it, this cognitive processes affect the understanding of the direction in a motion. Therefore, we find it to be more human like the situations that could reflect our previous experiences such as the assumption that an object can make independent decisions on its own trajectory if it suddenly changes direction without collision (img. 12).

 

Img. 11: An object moving with constant speed vs. an object which increases its acceleration.

Img. 12: An object that changes its course with no apparent reason, vs. one that does not.

During the “Colloquium on Performing Arts and Robotics” held by the Washington University of St. Louis in 2011. William Smart presented a movement piece to research over the capabilities for a machine to produce an understandable narrative over a stage performance. The movements of a robot was choreographed around its relationship with another human actor. The piece was designed to transmit a sense of persecution that was easy to recognise due to the presence of a secondary character (img. 13). This work was the beginning of his research in which he aimed to understand how performing objects can recreate understandable tales in Theatre [24].

 

Img. 13: Movement piece by William Smart

Motion dependent of its external morphology

External morphology, refers to the qualitative features that compose the body of an object. It involves every element that defines the anatomy of a subject such as material, shape, colour or texture. These elements can individually affect the characteristics of a movement or can model bigger structures that could in turn determine it completely. Designers have understood the potential of morphology and together with the application of classical mechanics have conceived artefacts with independent transition between rest states and movement.

The first Law of Newton expresses that a body at rest will stay at rest until a force, whether balanced or unbalanced, acts upon it. Because of this, motion dependent of morphology has been commonly been explored in conjunction with the dependence on the environment. From what we have previously studied, we can argue that as the levels of perceived independency in the movement of an object increase, so does the perception of liveliness. An artefact capable of creating the initial force of its movement would be considered to be more lively than an object that relies upon an external source to generate it [25]. Thus, creators have understood the potential of constituting structures that could take advantage of the available sources in their environment, particularly the invisible ones, to create the illusion of autonomous actions.

The “Walk Wind sculptures” of Theo Jansen display the aptitude of combining morphology and sources in the environment to pursue the gift of liveliness in an object. His research demonstrates a profound study of materials and geometry which he complements with the understanding of the physical advantages of the wind. As a result he obtains “new forms of life” capable of autonomous actions (img. 14) [26].

Img. 14: Strandbeest

Motion for life

Aristotle explained life to be as the sum of all of the objects that are material and subject to motion. He explained that movement in the ample sense, had two converse sides “gignésthai “ in progress or existent, and “corruptio” passing away [27]. As we stablished before, movement is an underlying characteristic of life and has the potential to be applied in objects in order to assign qualities of liveliness. However, the anthropologist Ray Birdwhistell founder of the social science known as “Kinesics”, explains that there is only a specific range of gestures which are able to transfer a complex intention such as it is the awakening of life. In his research, he studies how a body, mainly a human one, uses movement to communicate. He classifies it into four categories: emblems, illustrators, regulators and adaptors. Emblems are the only expressions capable to transfer a complete intention [28]. They are identified to be sharp and high in intensity and explains that in a man they are normally related to vigorous components of the anatomy of a body, such as it is the sudden aperture of a human eye (img. 15).

 

Img. 15: Emblems of body language.

Emblems have been adapted to express animation in lifeless artefacts in the performing arts. Satyajit Das presents a cloud of blossoming pixels on his project “Ensemble” (img. 16). These artefacts, activate as a visitor approaches them. A single movement of expansion is made instantly while the user is present and contracts back on its absence (img. 17). The motion is characteristic for its speed and simplicity and emulates a colony of lively objects that will only awake in the presence of life [28].

Img. 16: Ensemble

Img. 17: Individual pixels of Ensemble

3. Perceived liveliness in the mind of the Object

Even the simplest form of living organisms presents complex intrinsic systems that allows it to understand and perceive its environment. Recent studies in the filed of Evolutionary Ecology suggest that plants responses are similar to the ones that animals have when confronted to behavioural experiments. In her book “Thus Spoke the Plant” , Dr. Monica Gagliano states that from the results on her research we could argue that plants possess intelligence, memory and the ability of learning. This interpretation would mean that the traditional structure of intelligence formed by a brain and a nervous systems would have to consider an alternative were intellect could stand in a body regardless of the absence of these organs [29]. As we studied before, through our evolution men have built their interpretation life in order to understand it better. Therefore, it was only logical that when performing our attempts to mimic it we had not only tried to resemble its mechanics but also its intellect.The first attempts in history that speak about emulating intellectual human processes date back to the beginning of the 19th century. Charles Babbage was a mathematician and economist working for the Astronomical Society in 1820. He supervised the production of star tables which included the revision of the calculations, compilation and printing of the astronomical discoveries given at the time. Babbage was unsatisfied with the inaccuracy and monotony of the process, and decided to use the principles of mass production- technology to create the “Difference Engine”, a machine able to compute different sets of numbers and print the results in the form of the required tables [30].

In 1941, Konrad Zuse faced similar obstacles to Babbage’s practice. As a civil engineer, Zuse recognised the potential of the “Difference Engine” to make calculations more efficient. Accordingly, he adapted its system to serve his own purpose of mechanising static estimations and also improved it by creating a new function able to store up to 64 words in its memory. He called this new machine the Z1 (img. 18) [31].

Img. 18: Z1

With the invention of these systems, in the 1950s scientist challenged the parameters of intelligence built within a machine. Can Machines Think? Was an enquire explored by theories such as the one proposed by Alan Turing “Computing machinery and intelligence”. On it he stated that our human intelligence relies in the ability to use the available information in our environments in order to make decisions a resolve paradigms through reason. Consequently, he mentions, that men should focus on assigning these mechanisms to machines if we want them to be able to think [32]. Nevertheless, these hypothesis were restricted to be proved, by the capability of computers at the time. Until this moment in History, apparatus lacked the ability to store ample sets instructions and were mainly focused on executing orders.

It was not until 1956, that the proof of concept emerged during the Dartmoth Summer Research Project on Artificial Intelligence. Allen Newell, Cliff Shaw and Herbet Simon presented their project called “The Logic Theorist”. It was a program able to simulate the problem solving ability of a human brain. They understood how through interaction, simple programmable units could develop complex operations. By manipulating symbols an artefact a machine could imitate processes such as decision making [33]. This event turned out to be a breaking point that would catalyse the research of the next twenty years on the field. The execution of theory was still uncertain but in this moment scientists agreed that the idea of Artificial Intelligence was possible.

Many approaches have raised since then with the objective to define what the intellect in a machine refers to. Nevertheless, in the History of Artificial Intelligence intelligence in a machine is appointed by the same people who designs them. But what happens when an object as such, performs in an environment where interaction is required such as in the field of the Performing Arts. How are we to measure when an instrument is considered to be intelligent in an unstable environment or when an audience challenges its ability.

Conversation

“When asked to define “obscenity”, Supreme Court Justice Potter Stewart famously demurred: “I know it when I see it.” (Stewart 1964) Maybe intelligence is like that, impossible to define, but you know it when you converse with it [34].”

M.H.A. Newman

On Descartes discussion “Discourse on Method” he argued that the most complicated task that would permanently segregate machines from men is the human ability to hold an intelligent conversation. The mathematician Alan Turing understood this concept and with it created a method known as the “Imitation Game”. This system would be able to identify the intellect of a machine through analysing the “indistinguishability” between the verbal behaviour of a man and a machine [35]. The game or test, is based on the cognitive mechanism known as comparative method (img. 19) which allow us to identify the similarities and differences between two objects or subjects [36]. It is through this process how we ordinarily assign characteristics to objects in our surroundings.

For example, when we want to know if the length of an object corresponds to a meter, we simply compare it with a different object that we have previously stablished to be a meter long.

Img. 19: Comparative method

The test is played with three characters. A machine known as “A” a human known as “B” and a human interrogator “C”. The interrogator is set in a room separated form A and B. The target of the game is for C, the interrogator, to determine which of the other two is a machine and which is a human. He determines X to be human and Y to be machine, therefore the results of the game could be as follow: X is A and Y is B or X is B and Y is A. Around the game the elements that could give away the answer are suppressed according to the circumstances of it, for example, in order for the tones of voice to not help the interrogator distinguish between the characters, the answers to questions given to both of them should be typewritten (img. 20).

Img. 20: The Imitation Game

Turing uses communication as a standard to determine the intelligence of a machine in view of the fact of what the cybernetician Gordon Pask stablished in his “Theory of Conversation”. On it he installs that communication has an epistemological foundation and through it a living organism or a machine can learn and increase the competency of its intellect [37]. He begins by explaining that the standard position of communication in the “Conversation Theory” is called a “strict conversation” and it refers to the principles encountered when any type of conversation takes place between participants. On a “strict conversation” the participants obey the rules of a preset language known as the “conversational language”. Which he explains does not necessarily restricts to the natural language but could also be built on any type of graphic or non verbal symbolic language.

Pask expounds that there exist two integral mechanism-postulates constituted in a mind, concepts and memories. A concept is a method that is able to reproduce the understood information related to specific topic; and a memory refers to the mechanisms able to reconstruct a concept. When a conversation between two agents is held, learning occurs through the existence or creation of the concepts associated in the memory of a subject. In this procedure of sharing, a participant provides its own stable concept and shares it with a participant oblivious to it. The process in which this new agent is able to understand it and execute it is known as behaviour (img. 21) [38]. Furthermore, he explains that in communication the participants are formed by two characters, a P-individual which refers to the mind of the participants and a M-individual which is represented by their body. These “personas” can take different roles in a conversation, for instance, in a discussion where four people agree and object over the same topic and nothing else, we will be able to found four M-individuals forming one single P-individuals (img. 22).

Img. 21: Pask’s “conversation theory”

Img. 22: Characters involved in Pask’s “conversation theory”

The conversation theory considers communication to be an essential aptitude of Human nature. Therefore, in order for a machine to be consider a living organism, it should be able to execute satisfactory models of conversation. According to Dr. Susan R. Beauchamp [39], there exist specific inherent qualities in the human communication models that speak of complex processes of rationalisation. Over the next chapter we will review the specificities of these characteristics and will research over their application in creation of lively objects in the Performing Arts.

Decision making in conversation

 

Beauchamp defines two models of communication, a linear and an interactional. The linear model of communication is carried out by two participants. A sender, who encodes a concept according to a pre-established language and subsequently transmits it; and a receiver who interprets the translated idea. The concepts are perceived by sense organs built in the anatomy of the subjects and it is through an intellectual capability how the receiver determines if the acquired information is valuable enough to influence him. This ability to decode and discern the information received in order to decide its relevance is one of the primarily characteristics of a rational conversation [40]. Decision making is a behaviour consequence of the changes in the algorithms that communicate directly with a subject. When viewed in the context of a goal, a linear model of communication can derive into two possible results. In a first scenario, the sender transfers non-relevant information to a receiver, who consequently does not modify his state. And a second scheme where even though the collected information is relevant enough to alter the state of the receiver, the input produced by him does not influence the sender in any event (img. 23).

Img. 23: Models of Human linear communication.

This last concept is also know as a reactive mechanism and even though it does not translate into a continuous transference of information it can possess complex capacities. The choreographer Blanca Li, understood the potential of these method to develop her piece “Robot!”. This choreography is performed by professional dancers who lead the movements of the NAO robots that share the stage with them (img. 24). During her presentation at the Barbican Center, she explained that in order to generate a convincing piece that demonstrated robots’ abilities to dance as humans, she needed to understand the limitations in its movements [41]. This piece exemplifies a machinery able to demonstrate complex gestures of life regardless of its linear communication model.

Img. 24: Robot!

Adequate response in conversation

An interactional model of communication occurs through the same concepts of the linear model and includes the notion of feedback. Norbert Weiner established the definition of this concept to be the necessary information in order to enact equilibrium in a system. Feedback can be understood as the process of generating an appropriate response in consequence of the difference between the input and a predetermined goal [42]. This interchangeable operation constantly exchanges the rolls between receiver and sender, and it relies in the understanding that both individuals are capable of transforming the data into understandable and logical responses (img. 25).

 

Img. 25: Model of Human interactional communication.

“…whereas reason is a universal instrument which can be used in all kinds of situations, these organs need some particular disposition for each particular action; hence it is for all practical purposes impossible for a machine to have enough different organs to make it act in all the contingencies of life in the way in which our reason makes us act [43].”

René Descartes

 

The developments of artificial intelligence have radically evolved throughout the last decades. Nevertheless, the existence of a machine capable to accurately reply to every attainable inquisition has not yet been fabricated. Therefore, we can argue that for our existing time, the relationship between a machine intelligence and its accuracy in response towards a specific set of acknowledged information is still demarcated by the existence of a context or the definition of a goal.In an interactive communication, feedback composes a bilateral learning structure between individuals, either machine or man. Dr. Ruairi Glynn defines that wether they are fed by humans or other entities into the system, an interactive conduct is more likely to be understood as purposeful and individual [13] and they bring as a consequence longer perceptions of animation in the objects. On his piece “Performative Ecologies”, Glynn generates a conversational habitat between his robotic sculptures and the visitors. These creatures use a genetic algorithm to measure the attention levels that their behaviours produce in an audience (img. 26). As the objects learn from their failure and success a shared dancing ecosystem is constructed by the reciprocal gestures between the people and the robots [44].

 

Img. 26: Performative Ecologies

Emotional state in conversation

Human beings are as much emotional creatures as they are rational. Thus, human communication models consider the emotional state of a conversation to be an intrinsic part of their structure [45]. Through several approaches designers have simulated emotional states in the conversations realised by an artefact. The application of colour psychology and the study of specific gestures of motion are a few of the tools used by them that could evoke perceived sentiment in an object (img. 27).

 

Img. 27: Theory of colour according to emotions

Hysterical Machines is the name of the creatures who perform in the installation presented by Vill Born at the STRP festival of 2006. The morphology of these creatures was inspired by the anatomy of arachnids (img. 28).The robots react with an erratic behaviour to the presence of a body which increases as the number of observers in the installation augments (img. 29). The research of Born focuses on the human empathy responses towards the aesthetics of an artificial behaviour. He describes how through the creation of an environment with specific colours, sounds and motions his machines transfer a hectic emotional estate to the audience (img. 30) [46].

Img. 28: Hysterical Machines

Img. 29: Erratic behaviour in Hysterical Machines

Img. 30: Environment of the Hysterical Machines

However, if it is true that artificial intelligence is not yet able to possess an inherent emotional state of its own, the latests advances in machine technology have refined mechanisms that allow an artefact to recognise a vast array of emotional expressions and with them intuit the internal state of a human conversation. The researcher, Javier Hernandez from the Affective Computing Group at the MIT Media Lab, explains that emotion AI works by analysing a broad amount of data that is after filtered in order to select subtle but constant micro-expressions on humans interactions (img. 31) [47]. For him, this field of study is understood to be a tool that facilitates a more natural conversations between machines and humans.

Hey Hexx is a responsive puppet theatre developed by the Interactive Architecture Lab at The Bartlett School of Architecture in 2018. Hexx is a puppet controlled by a robotic arm who was built with the objective to translate the messages in social media of the audience who interacts with him into expressive cues of motion (img. 32). Hexx together with all of the elements on his stage perform in real live specific behaviours that gives to the observers the experience of transferring their emotions to a secondary subject (img. 33) [48].

Img. 31: Human micro-expressions.

Img. 32: Hey Hexx on its set

Img. 33: Hey Hexx translating emotions

Chapter III

1. A Turing test for Liveliness

Alan Turing designed the “Imitation Game” or “Turing test”, to define the capability of intellect in a machine based not in the systems built within the artefact but in the judgement of an audience. The author of the book “The Art of Presenting the Performing Arts”, Naomi Rhodes states that, as in the Turing Test, the acknowledgement of the content that an audience possess towards any type of Performing art is the most relevant strategy to determine its engagement [49]. With this we can argue that the model of measuring the intelligence of a machine based on the relevance of an external subject that the imitation game uses, coincides with the perspective of this research.

I propose for the forthcoming evaluation of Lumina to create a “Turing test of Liveliness” based on the qualities of motion and communication that we have formerly determined to be potential cues of animation. We will perform the test according to the steps that exist in the experiential journey of the installation.

It is important to recognise that during his research Turing defined specific qualities that a machine could have in order to “pass the test” [50]. And that his aspiration was, that mechanisms would achieve this goal with more frequency and ease as our History develops. As the Turing test, during the next chapter, we will make use of this research to analyse Lumina’s current behaviour and speculate over the possible subsequent transformations that she could suffer in order to more frequently be perceived as a lively object.

2. Lumina under the Turing test for Liveliness

 

Q: Why do I think that you are alive?

The environment of Lumina is an isolated black space that does not possess any other source of light apart from the one she emits. The enclosure of Lumina in an empty room is an intentional design decision, that comes from the understanding of Romanes’ theory of anthropomorphism and empathy referred in the previous chapters of this thesis. On it he establishes that in the absence of another human our social brain is more susceptible to the creation of “beings of our own species”.In the presence of an unknown environment, a human is driven by his instinct of trying to feel competent to understand his surroundings. This intrinsic mechanism pushes men to analyse through cognition the elements that form our context. As we have reviewed before the cognitive processes built in our mind begin they function by the acquiring information through our senses and it is motion perception the fastest biological stimuli that our brain is able to identify. Consequently, as Lumina is the only element with activity in this specific space, she is also the first object to capture their attention (img. 34).

Q: Why do I think that you move as though you are alive ?

The motion of Lumina needs to be understood as two different sub systems. The first one refers to its actual movement abilities and the second one assigns to how this movements affect the motion of the light reflected through her. In simpler terms Lumina possess her own movements that in turn influence the motion of her light reflections (img. 35). She possesses two original movements that are produced by the parabolic mirrors in her anatomy. The first one is an up and down movement that due to the physical behaviour of light brings as a result the contraction and expansion of the diameter in the beam that she emits (img. 36). And the second one refers to a tilting mechanism that in consequence concentrates the reflections in order to transform the light into a directional spot (img. 37).

Img. 35: Lumina’s systems and sub-systems of motion.

Img. 36: Lumina’s up and down movement.

Img. 37: Lumina’s tilting mechanism.

Lumina develops in a terrestrial environment and even though her mechanisms need to be electrically triggered by an external source, the audience who interact with her, begin their experience with a Lumina in motion. Her initial movements defy the limitations of gravity and avoid a rest state. This according to Szego’s theory of “motion dependent on the environment”, begins to position the behaviour of Lumina as animated.

Q: Why do I think that you have an intention?

Lumina possess what we have assigned to be a passive behaviour. On it, the mirrors in her structure perform a sine movement. This action adjusts the reflections of the light and transforms them into a concentrated beam that emulates “the search of someone” (img. 38). The sine movement of Lumina constantly changes course and modifies its acceleration (img. 39). These cues of motion were designed based on the previously mentioned theory of “Visual Perception of Intentional Motion” which delineates that in the absence of contextual elements that explain the intention of motion in an subject, we can make use of specific cues in the speed and direction of it to generate hints of liveliness. Our intention with this initial conduct, is to generate sufficient intrigue in the audience that provokes them to approximate her. Nevertheless, we have experienced that this mechanical action occasionally is not enough to transfer a precise message.

Professor Carola Zwick, director of the eLab at the Kunsthochschule in Berlin, determined that for a successful collaboration between robots and humans, machines should be able to overcome the limited perception of a human brain when exposed to an increased amount of simultaneous signals. On his project “Body Language of Machines” he uses media animation techniques to study the human gestures that could be possibly be adapted into objects [51]. This analysis opens an argument for exploration in the upcoming development of Lumina. Gestures for greeting, variate depending on the cultural background that a person possess. Could Lumina or any artefact be programmed in order to adapt gestures and use human body language theories to address a more comprehensible discourse?

Img. 38: Lumina’s passive behaviour.

Img. 39: Lumina constantly changes speed and direction.

Q: Why do I think that you are aware of us?

The next step inside the interaction occurs when the proximity between Lumina and a visitor is enough to be read by an infrared sensor. This sends a signal to her running software and makes the decision to change the conditions of her state due to the presence of a subject. With this, an interactional model of communication begins as Lumina awaits for the second message that could or could not alter her state (img. 40).

An “emblem” defines this second cue of motion. With a fast and sharp movement Lumina points all of her light towards the found entity (img. 41). According to the interviews realised to the users who met her during the Ars Electronica Festival 2019, [52] it was this instant of the experience which determined the birth of Lumina as a lively object.

Img. 40: Lumina in a interactional model of communication

Img. 41: Lumina’s emblem.

Q: Why do I think that you are trying to respond to us?

The experience of the audience with Lumina transitions from a state of awakening into a an interactive conversation. The emblems in Lumina help the user understand that his action of approaching her triggers a secondary conduct. With this occurrence, the visitor becomes aware that through movement he can build a conversational language with Lumina.

In order to decode the symbolic meanings of this new language, the visitors tend to explore the possible changes in their postures that could cause a modification in position of Lumina’’s body. With this method of trial and error, Lumina and the visitor constantly interchange roles as senders and receivers and create an intermittent exchange of information (img. 42).

According to Glynn’s studies on Lively Artefacts an interactive conduct is more likely to be understood as animated. Nevertheless, it is the process of learning through feedback the one which defines a high degree of complexity in living organisms. In the case of the interchangeable loop of information that we are studying here, the user is the only subject capable to learn through experience as Lumina does not possess a system that allows her to learn and expand her programmed behaviours.

Img. 42: Lumina’s visitor trying to understand her language.

Q: Why do I think that you can make a decision?

She is programmed to identify specific gestures in the motion of a person. The sensors in Lumina distinguish between the limbs of a person and ranks their priority. She considers the position of the arms of a person as the principle parameter of measurement. This relationship affects the diameter of the reflected light. As the user contracts and expands his arms, he is able to increase and decrease the size of the beam accordingly. (img. 43) Lumina possess a secondary goal- directed action that is stablished by the location of the feet of a person. She performs a tilting motion when she distinguishes a foot to have more activity compared to the other. This action brings as a consequence the distortion of her reflections which form a spot light directed towards the position of this part of the body (img. 44).

Referring back to Dugatkin’s studies, the intellectual capability that an individual has to not only receive information but to determine its relevance to modify or not his inner state is essential to determine the complexity of a living organism. Lumina’s ability to respond adequately to a specific cues of motion helps her to be recognised as a lively object. Nevertheless, through observation we have realised that the bounded range of her replies interrupt the progress of a continuous conversation between her and the visitor. Unlike a human, Lumina can not be programmed with all the necessary information to distinguish every possible human cue of motion.

Img. 44: Lumina considers the arm to be the most important parameters.

Img. 45:Lumina considers the feet as a secondary parameter.

This research opens the question to the possibility of developing in Lumina a system that will allow her to extend her conversational parameters. In Turing’s words we should develop a system which uses the orders given, to generate unanticipated and interesting results [28].

Q: Why do I think that you have emotions?

Currently, Lumina has not been designed to interpret human emotions. But the research from the Affective Computing Group at the MIT Media Lab have shown us that the existence of emotional states in a machine could facilitate a more natural conversation between us and them. Could we thereupon argue that Lumina could express internal emotional states such as confusion, anger or happiness in order to help the audience understand the parameters behind her behaviours.

Q: Why do I think your life can end?

Bioethicist Ronald Dworkin mentions that death should be always considered part of the dominion of life. He states that “Although any living creature anytime can lose its life, no creature can lose its death. This is why death is safe and secure in all living things” [53]. Ephemerality is constant in all forms of life. Therefore, I question the potential to use the characteristics of mortality in order to associate life to an object. Can Lumina or machines die in order to be considered lively? “Active dying” is an example of the fields of study that shows that liveliness can be understood through fatality. Dr. James Carey specialist on this field, categorise models of physical and functional qualities of a failing systems in a body [54].

3. Conclusions

Human perception, includes an irresistible tendency that men have to perceive life in the objects that conform his habitat. We have recognise that there exist human cognitive processes built in our brains which lead us to study the animation in an object before we are even able to create a rational judgement around them. Anthropomorphism and Empathy are perceptual functions that arise from instinctive mechanisms that men develop on early stages of their growth. These mental functions study the similarities between us and the individuals in our context in order to determine the liveliness in them.

Moreover, we have defined two primary capabilities that we, humans, detect to be associated with life. The capability of motion and conversation, drive our human analysis to define the complexity of a living form in a physical and intellectual manner. These are characteristics that through History, the development of machine technology has mimicked and constructed in the artefacts that conform it, with the objective to explain how our world works.

Visual motion perception is the most agile process that our Psyche employs to analyse the stimuli in a specific environment. We have determined through, Dr. Zogza’s theory of living organisms, four classes that study the quality of life in a movement. Motion dependent of the environment, motion triggered by an individual’s morphology, motion with intention and motion for life. These categories explain, that a movement presents individuality when its execution reflects a purpose. A motion with intention, even if it is simulated, is more likely to be understood as animated. This idea is reinforced when an artefact is capable of triggering its own movement by using its morphology and combining it with the sources available in its environment. Furthermore, there exist cues in the speed and direction of a motion that are more frequently associated with independent subjects. Alteration without collision in the direction of an action, and a changing acceleration are normally determined by our brain to be signals of a lively movement.The conversation theory of Gordon Pask, considers communication to be an essential aptitude of Human nature. He defines the existence of two available forms of conversation. A linear model of conversation refers to a review and scheme in which the information travels only in one direction. And a bi-directional model occurs when the participants in a conversation use the concept of feedback to create an interactive exchange of data. In order for an object to be consider a living organism, it should be able to execute satisfactory models of conversation. This involves the ability of decision making, selection of an adequate response and ownership of an emotional state.

Lumina is one of the examples in which the aesthetically potential of a lively object has been applied in the field of the Performing Arts. Nowadays, artefacts have transformed their role on the world of spectacle. They have transitioned from their previous function of tools to become characters with individuality. This research suggests the application of the abilities of motion and conversation, in order to conceal understandable cues of liveliness in objects. As the Turing Test, this research understands that the characteristics of these qualities will evolve together with the future development of machine technology. Consequently, it promotes the further study of cues of life that in the upcoming future will have the possibility to be transferred into machines.

Bibliography

1. Potts T. “Culture through Objects: ancient Near Eastern studies in honour of P.R.S. Moorey”. Griffith Institute. Oxford 2003.

2. Searle, J. “ Minds, Brains and Programs”. Behavioral and Brain Sciences. University of California. United States of America. 1980

3. Bogen, P. July 2019. “ How can we distinguish Perception from Cognition”. Accesses on: https://www.duo.uio.no/bitstream/handle/10852/58422/Sydhagen.pdf?sequence=1

4. Waytz, A. “The Mind in the Machine: Anthropomorphism Increases Trust in an Autonomous Vehicle”. Northwestern University. United States of America. 2001.

5. Povinelli, D. “Toward a Science of Other Minds: Escaping the Argument by Analogy. Cognitive Science” . Oxford University. United Kingdom. 2000.

6. Scotto, C. “ Empathy, Anthropomorphism and animal cognition”.Universidade Federal de Santa Catarina. Brazil. 2015.

7. Premack, D. “Does the chimpanzee have a theory of mind?”/ The Behavioral and Brain Sciences. United States of America. 1978.

8. Preston, S.; B.M de Waal, F. “Empathy: Its ultimate and proximate bases”. University of Iowa Hospital and Clinics. United States of America. 2002.

9. Ibíd.

10. California Institute of Technology. August 2019 “Feynman”. Accessed on: http://archives-dc. library.caltech.edu/islandora/object/ct1%3A483

11. Kang, M. June 2019 “The Mechanical Daughter of René Descartes”. Accessed on: https:// www.cambridge.org/core/journals/modern-intellectual-history/article/mechanical-daughter-of- rene-descartes-the-origin-and-history-of-an-intellectual-fable/14518C7D691F1B35B7504418 B935D8A1

12. IEEE computer society. July 2019 “Annual Symposium on Automata Theory”. Accessed on: https://ucl-new-primo.hosted.exlibrisgroup.com/primo-explore/fulldisplay?docid=UCL_LMS_ DS51247690290004761&context=L&vid=UCL_VU2&lang=en_US&search_scope=CSCOP_ UCL&adaptor=Local%20Search%20Engine&tab=local&query=any,contains,automata&offset=0

 

13. Ruairi, G. “The Iressistible Animacy of Lively Artefacts”. University College London. United Kingdom. 2018.

14. Wiener, N. August 2019. “Cybernetics in History”. Accessed on: http://neoscenes.net/teach/ cu/2012_2/atls2000_mit/pdfs/Wiener-1954-Cybernetics_in_History.pdf

15. Ibíd.

16. Anonymus. July 2019 “The Thinking Machine. Time Magazine 53” Accessed on: http:// content.time.com/time/magazine/article/0,9171,858601,00.html

17. Shieber, S.M. “The Turing Test: Verbal Behaviour as the Hallmark of Intelligence.” The MIT Press. London. United Kingdom. 2004

18. Zogza, V. “The Development of the concept of alive by preschoolers through a cognitive conflict teaching intervention”. European Journal of Psychology of Education. Greece. 2000

19. Johansson, G. July 2019. “Spatio-temporal differentiation and integration in visual motion perception.”. Psychological Research. Accessed on: https://link.springer.com/article/10.1007/ BF00309043

20. Derya, A. August 2019 “Investigation of intellectual Abilities of Students according to Piaget’s Stages of Cognitive Development”. Accessed on: https://doaj.org/article/ d9baeb3230744c0aaf4ce35851c7a491

21. Dittrich, W. H., and Lea, S. E. August 2019 “Visual perception of intentional motion”. Accessed on: https://journals-sagepub-com.libproxy.ucl.ac.uk/doi/abs/10.1068/p230253

22. Ibíd.

23. Ibíd.

24. Washington University in St. Louis. September 2019. “Colloquium on Performing Arts and Robotics”. Accessed on: https://www.youtube.com/watch?v=-FyK5tVuaKk

25. August 2019, “ Greek studies”. Accessed on: http://www5.csudh.edu/phenom_studies/ greekphil/greek13.htm

26. Jansen, Theo. July 2019. “Strandbeest” Accessed on: https://www.strandbeest.com/

27. Ibíd 23.

28. Architecture Social Club. September 2019. “Ensemble”. Accessed on: https://www. architecturesocialclub.co.uk/microsoft-ensemble
29. Gagliano, M. “Thus Spoke the Plant”. North Atlantic Books. USA. 2018.

30. Computer Hope. July 2019. “Firsts computers of its kind”. Accessed on: https://www. computerhope.com/issues/ch000984.htm

31. Martin, C-K. “Computer: A History of the Information Machine”. Perseus Books Group. United States of America. 2004.

32. Newman, M. Turing, A. “Can Automatic Calculating Machines Be Said to Think?”. MIT Press. USA. 1952

33. Anyhow, R. July 2019 “The History of Artificial Intelligence”. Accessed on: http://sitn.hms. harvard.edu/flash/2017/history-artificial-intelligence/

34. Dennett, Daniel. “ Can Machines think?”, Centre of cognitive Studies, Springler, Germany, 2004.

35. Damarus, M. July 2019 “Método comparativo de la psicologîa”. Accessed on: https://www. academia.edu/8890511/METODO_COMPARATIVO_DE_LA_PSICOLOGIA_diferencial

36. Newman, M. Turing, A. “Can Automatic Calculating Machines Be Said to Think?”. MIT Press. USA. 1952

37. Scott, B. “Gordon Pask’s Conversation Theory: A Domain Independent Constructivist Model of Human Knowing.”. Centre for Educational Technology and Development. Leicester. United Kingdom. 2001

38. Gordon, P. “Conversation Theory. Applications in Education and Epistemology.” Elsevier Scientific Publishing Company. Netherlands. 1976.

39. Beauchamp, S. “Introduction to Human Communication. Oxford University Press. United Kingdom. 2015.

40. Ibíd.

41. Li, B. September 2019. “Robot!”. Accessed on: https://www.blancali.com/es/event/99/ Robot

42. Morlidge Steve. August 2019 “Concepts on systems and cybernetics”. Accessed on: https:// onlinelibrary.wiley.com/doi/pdf/10.1002/9781119206613.app2

43. Turing, A. August 2019 “ Can Digital Computers think?”. Accessed on: https://aperiodical. com/wp-content/uploads/2018/01/Turing-Can-Computers-Think.pdf

44. 32. Glynn, R. September 2019. “ Performative Ecologies”. Accessed on: http://www. ruairiglynn.co.uk/portfolio/performative-ecologies/

 

45. Gugerty, L. “Newell and Simon’s Logic Theorists: Historical Background and Impact on Cognitive Modeling” Clemenson University

 

46. Vorn,B. September 2019. “Hysterical machines”. Accessed on: http://billvorn.concordia.ca/ robography/Hysterical.html

 

47. Horgan, T. “Connectionism and the Philosophy of psychology”. The MIT Press. United States of America. 1996.

 

48. Yamaguchi, S. September 2019. “Hey Hexx”. Accessed on: http://www.interactivearchitecture. org/lab-projects/heyhexx

 

49. Hadary, A. September 2019 “ Bibliography of Performing Arts in the East”. Accessed on: http://asia-perfo-arts.com/

 

50. Ibíd.

 

51. Robson, P. “Body Language’. Franklin Watts. London . United Kingdom. 1997

 

52. Ars Electronica. September 2019. “Six Movements”. Accessed on: https://ars.electronica. art/outofthebox/en/six-movements/

 

53. Carey, J. September 2019. “Biology of death”. Accessed on: https://evmedreview.com/ biology-of-death-2/

 

54. Ibíd.

Images
Image 3: “The Writer”. July 2019. Accessed on: https://www.watchtime.com/featured/do- androids-dream-of-horological-sheep-a-look-at-pierre-jaquet-droz-and-his-automata/
Images 4,5,6: “Homeostat”. June 2019. Accessed on: https://www.researchgate.net/figure/ The-homeostat-a-Four-interconnected-homeostats-b-Detail-of-the-top-of-a-homeostat_ fig3_250893458
Image 7: “Point light experiments”. August 2019. Accessed on: https://www.youtube.com/ watch?v=rEVB6kW9p6kautomata/
Image 13: “Colloquium on Performing Arts and Robotics”. August 2019. Accessed on: https:// www.youtube.com/watch?v=-FyK5tVuaKkjaquet-droz-and-his-automata/
Image 14: “Strandbeests”. June 2019. Accessed on: https://www.strandbeest.com/Image 16, 17: “Ensemble”. August 2019. Accessed on: https://www.architecturesocialclub. co.uk/microsoft-ensemble
Image 18: “Z1”. July 2019. Accessed on: https://xavo.com/holidays2018/2017/12/14/it-history- the-first-digital-computer-zuse-z1
Image 24: “Robot!”. September 2019. Accessed on: https://www.blancali.com/es/event/99/ Robot
Image 26: “Performative Ecologies”. September 2019. Accessed on: http://www.ruairiglynn. co.uk/portfolio/performative-ecologies
/Image 27: “Emotional Theory of colour”. September 2019. Accessed on: https:// everymomentcounts.org/view.php?nav_id=173
Image 28,29,30: “Hysterical Machines”. September 2019. Accessed on: http://billvorn. concordia.ca/robography/Hysterical.html
Image 31: “Micro-expressions”. September 2019. Accessed on: https://es.123rf.com/ photo_72308943_silueta-monocrom%C3%A1tica-con-la-ilustraci%C3%B3n-de-vector-de- ojo-de-mujer-de-gui%C3%B1o.html
Image 32,33: “HeyHexx”. September 2019. Accessed on: http://www.interactivearchitecture. org/lab-projects/heyhexxojo-de-mujer-de-gui%C3%B1o.html
Image 44: “Lumina”. August 2019. Performer: Tia Hockey.
Others: C. Cortes
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