Anna Tuschling: The Age of Affective Computing
The Age of Affective Computing
(S. 179 – 190)

Media Worlds and Affect

Anna Tuschling

The Age of Affective Computing

Übersetzt von Maya Vinokour

PDF, 12 Seiten

“Affective computing”1 is a fairly new field of research that aims at equipping machines with emotions. It utilizes findings in the psychology of emotion to design and implement interfaces allowing for an “emotional dialog” between man and machine. The goal is for computers to correctly “read” the affective state of their human users. This paper argues that “human emotion” as conceptualized by the emotion psychology and by researchers in the field of affective computing is not a range (or a set) of “natural” states of feeling but a product of scientific research and technological development. Accordingly, this paper examines the historical and media technological foundations of affective computing. It is not concerned with the nexus of affect and media in general which has been the subject of a detailed study.2 Instead, it focuses on a specific kind of affect – the encodable expressions of the human facial muscles – that is the object of influential psychological theories (notably Tomkins’s, Ekman’s, Friesen’s, and Izard’s theories of emotion, among others). In particular, my paper illustrates how this “affect” – which is really a complex construct of scientific research – is used to develop technologies of affective computing and how it is supposed to aid the operations of “affective machines”.

Recent advances in affective computing are of great significance because basic concepts borrowed from the human sciences (concepts of emotion, to be more precise) are now being employed to design and realize new kinds of man-machine interfaces. I will discuss a certain aspect of the relationship of affect and technology: a technological condition (to use a phrase popularized by media philosophers Friedrich Kittler and Erich Hörl)3 that has only become recognizable today in the guise of affective computing. I will try to bring into the debate on affect a method characteristic for a certain tradition of German media theory: what might be described as the strategic disclosure of the technological condition for the purpose of determining the medial conditionality.

My paper addresses the following points:

1. The goal of the investigation is to reveal the technological condition of the so-called affective turn using affective computing as the example.

2. What I will not do is give a critique of the standardization of affective states as it is done in the psychology of emotion. Accordingly, I will not deal with the question whether “natural” human emotions do in fact exist or not.

3. The subject of my investigation is a single – yet very significant – aspect of the technological condition of the affective turn: a scientific system devised to encode the expressions of human facial muscles and a system that has become the foundation for technological development.

4. From the perspective of media studies I will examine the interrelationship between the digital computer and certain optical media. Digital computing accomplishes a twofold purpose: i) It facilitates, indeed it is responsible for the standardization of emotional states and thereby makes it possible to construct “affect” as an object of science; ii) it necessitates the functionalization of said standardization in the form of affective and ubiquitous computing.

This functionalization, though, is possible only because (and this observation will be the starting point of my critical inquiry) the medial conditionality of affective states is not acknowlegded by the technological development, i.e., because “affect” can be incorporated in the development of computing machinery in the form in which it is conceptualized by the psychology of emotion: as a “natural”, “innate”, and “universal” state.

Affective Computing: A new trading zone

This paper investigates the recently formed “trading zone”4 between psychology and computer development, called “affective computing”. I will be arguing here that over the past few years, developments in affective computing have cast the “renaissance of affect”5 in a different light. Most importantly, I would like to suggest this renaissance of affect may be understood not only from the perspective of discourse history and science studies, but must also be regarded as part of contemporary media history and even media development. Feeling, affect, and emotion stand out against the background of the 20th-century linguistic paradigm not only for intra-discursive reasons, but also for reasons proper to the history of technology. Why is this?

Affect and technology assume a new relationship because interactions with intelligent objects in experimental settings of computer design are increasingly regulated affectively. Computers are apparently becoming, at least metaphorically speaking, “emotionally intelligent” and are ever more capable of “responding affectively.”6 The following paper, however, is only partly devoted to the media-technological situation — that is, to the cluster of historical and technical prerequisites — which are supposed to enable computers to simulate empathy. I focus, instead, on how psychology (and which psychology) has become a basis for the development of interfaces. Therefore, I will firstly make some remarks on the renewed significance of interfaces and then use an example of affective computing to further delve into the theme.

Medial Worlds and Affect

The more we view the union of contemporary media not only as apparatuses, but as atmospheres7 and environments,8 the greater the weight given to affect as the interface and link between human and technical instrument. If observations on media and technology have long focused on the specific medium (e.g., book, film, television) or tool, media concepts in the technically based “network society”9 now demand a “radically environmental point of view,”10 which would seem suited not only to cases of electronic worlds. Investigations of cultural history within media studies supply, and have long supplied, an overwhelming amount of evidence that medial spaces are no modern innovation.11 Taking into account current conditions, in particular “ubiquitous computing,” Mark Hansen suggests we shelve the established conception of media as a set of inevitably historically contingent conditions of possibility for storage, broadcast, and processing and instead understand media as a “platform for immediate, action-facilitating connection to and feedback from the environment.”12 Yet this alternative definition of media has two flaws: firstly, it is subject to the same objection as any mention of new media as such, that is, it ignores the long prehistory of putatively new technologies; and secondly, Hansen indirectly aligns himself with the much criticized media-anthropological scheme that speculatively understands electrical networks as expansions and extensions of the human nervous system.13 In the age of the touch screen, the neuronal prosthesis and affective computing, it continues to be important to articulate, and emphatically, to question the boundaries between and intersections among the human body, fingers, sense organs, and brain, on the one hand, and intelligent machines, on the other.

Even when the overlaps, interfaces and intersections within the fundamental merging of people and media, and above all affect, are recognized for their exceptional significance, many theories of the “affective turn”14 have not yet elaborated in detail on the new interactions between human and machinic emotionality and affectivity in computer design. In short: Affective computing and advancements in robotics are not yet situated in these debates. Concepts of emotion and theories of affect have experienced, over the past 20 years, a great resurgence. With the turn away from language theory, whose winding way across disciplines – from philosophy (e.g., Wittgenstein), to psychoanalysis (e.g., Lacan) all the way to anthropology (e.g., Lévi-Strauss) – determined large swaths of 20th-century discourse history, the non-verbal and the pre-cognitive (the body, gestures, emotion and affect) should be emphasized once more.15

As a look at media history demonstrates, the reasons for this renaissance of the affective are far more diverse than the history of the discourses of language theory and postmodernism alone might lead us to believe. It is much more the case, I would suggest, that emotion and affect represent an increasingly important element in the development of technology, which relies upon a greater involvement of human actors in electronic settings than the more recent definitions of media let on.

I will now continue to investigate why affect becomes so important by considering a specific setting within affective computing. Affective computing, in this instance, seems once again to realize cybernetic utopias, with electronic media enabling a self-regulated and more joyous assimilation of content and learning.

An Example of Affective Computing

In the last few years the formation and direction of “intelligent interactions” and affective computers have attracted more and more attention because they illustrate the increasing intensity of the human-machine connection in a specific way.16 The affective computing projects currently investigating the relationships between emotion/affect and computers, while not unique, nevertheless provide highly typical and representative examples of the new direction technological applications to affect are taking. Affective computing thus deliberately seeks to place 20th-century humanities research on emotion in the service of developments in computing. In the wake of the emotional turn of 1990s neuroscience (above all Antonio Damasio), Rosalind Picard defines affective computing as “computing that relates to, arises from, or influences emotions.”17 Definitions of affect and emotion are thus not developed out of computer research itself, but rather carried over from brain research and psychology. Affective computing thus imports affect as formulated within the humanities into the domain of technological development, taking psychological theories of emotion – from Cal Izard’s studies of Ekman and Friesen’s Facial Action Coding System to Lazarus’ motivational theories of emotion – as a basis for those classification systems upon which the computer, with its “decoding” of emotion and correspondingly “emotionally intelligent” response, must rely.18 In current computer development, affects (meaning here the states of human users as these have been classified by the humanities in the research traditions named above) furnish no less, I suggest, than a semantics of human-machine interaction since, after all, the processor’s recognition of affect facilitates the evaluation of user reactions: “Classification of learner emotions is an essential step in building a tutoring system that is sensitive to the learner’s emotions.”19 If the whole problematics of humanities research into the emotions seems poised to engage in a hermeneutics of the states of the soul on the basis of physiological and especially optical data (from facial expressions), then the appeal to research into affect rests, at this stage of technological development, upon something at least as tentative, namely the semanticization and evaluation of computer-enabled interactions on the basis of taxonomies of emotion established in psychology and behavioral science. Rosalind Picard’s programmatic definition immediately reveals that the human-machine interaction is of paramount importance in affective computing, meaning that learning processes, along with navigation aids and games, represent one of its most significant areas of application. In this connection, Picard notes that learning is the quintessence of emotional experience.20 Electronic learning attains one of its (currently) most comprehensive forms through affective computing. The following observations on the interplay between affect and technology are based on the design of a learning system called AutoTutor,21 which belongs to the Intelligent Tutoring Systems (ITS) group. ITSs claim to be sensitive to the emotional and cognitive states of learning users.22 Regardless of the setting – whether it is learning, navigating, or any other interaction with intelligent objects – the computer system, by recognizing its interlocutor’s affect, should always be in a position to adapt its moves and offerings appropriately to his or her emotional state. In the case above, one hopes for a positive influence on the learning process, especially when intensive learning is attended not only by negative emotions like confusion, frustration, fear, and boredom, but also positive experiences like happiness, flow, and surprise.23

In particular, this occurs in computer-based learning environments equipped with sensors capable of transmitting the learner’s physiological data. Generally speaking, the electronic teacher sensitive to affect might help close the gaps between the “highly emotional human” and the “emotionally challenged computer.”24 The program developers assume that shifting “positive” and “negative” emotions shape the learning process, the experience of what Czíkszentmihályi describes as “flow” being the ideal.25 During flow, we forget time, do not feel fatigue, and experience other “positive” emotions like joy or, more rarely, “aha-moments.”26 Affect and technology weave together systematically, on several levels: throughout the learning process, a human user’s electronic environment collects, through sensors such as the Body Posture Measurement System and Facial Feature Tracking via IBM BlueEyes, physiological data relating to the acting/thinking/being human users. These data are then reconciled with a database of similar ones and thus evaluated. Using a given set of affects, the processor identifies, for instance, a specific posture combined with a specific facial expression and conversational cues as affects relevant to the learning process, such as boredom, confusion, or frustration.27

On the basis of this classification, the electronic environment can continually adjust itself to the user. The learning environment consists in the following: the learner is in a conventional class setting, sitting on a comfortable chair in front of a screen and processor, tries to execute a learning program that aims to impart Newtonian physics, an increase in computer-related knowledge, or raise the level of critical thinking as such.28 The learner’s activity is accompanied by a digital teacher or avatar, who is designated by the label Embodied Pedagogical Agent (EPA) or, in other contexts, by Embodied Conversational Agent (ECA).29 The computer obtains the learner’s various bodily data via an office chair equipped with sensors and a system for tracking eye movement. These data collectively amount to information about the learner’s emotional state, since the computer reconciles the learner’s data with available data on affect. This in turn enables the processor as well as the Avatar Tutor to “respond” to the learner’s affective condition according to specific rules. At its base, the story of affective computing is a story of sensors,30 since it is their accuracy and functionality that enables the computer’s so-called “affect recognition.”31 The processor is able to parse users’ affects on the basis of data from sensors. Templates for affect that incorporate knowledge of facial expression accumulated across earlier centuries (especially Ekman and Friesen’s basic emotions) may be sensibly used in learning environments. Whenever the question of intelligent or affect-sensitive computers arises in the literature, the central issue is always the verbal bridging of specific technical processes. In this connection it is indeed important to note that the goal of the present contribution is not first and foremost to expose the concealed technicity within affective computing. My focus here is rather the whole medial order with its effects and the recently formed link between psychology and processor development.

Emotional Psychology as the Basis of Affective Computing

I would like to continue by discussing, in all its historicity, the paradigmatic contribution of psychology to the development of interfaces within affective computing. The postwar years saw a decline in cognitivism and the simultaneous emergence of a new psychological paradigm that completed the turn toward technically based studies of facial expressions, toward the image. On the basis of Silvan Tomkins’s work,32 a tradition of research into emotion and affect developed among both the military (sponsored from 1966 to 1970 by the Advanced Research Project Agency, ARPA, of the US Department of Defense) and university researchers. This paradigm isolates the facial and employs contemporary technical avenues to stylize the significant expressions of facial muscles as “facial affect.”33 The emphasis on Paul Ekman and his peers’ work on facial expressions may be justified by the fact that the Tomkins-Ekman paradigm can hardly be overestimated in terms of its influence on psychology and the affective neurosciences, an influence that remains strong even after its displacement by similar techniques. Moreover, the aesthetic of this research into expression is uniquely transferable to the world of advertising, acting aesthetics, and television culture.34 Thus, for instance, the TV show Lie To Me (2009–2011) took as its inspiration the Facial Action Coding System.

The classic images of facial expression research are meant simply to encode eight innate, allegedly universally valid (that is, cross-culturally and globally valid) basic emotions: joy, fear, anger, sadness, disgust, surprise, anticipation, and trust. Their influence and function, however, extend far beyond this purpose; in various ways, they have been integrated into experimental classification systems in the neurosciences, as cultural theory and the history of scientific emotion studies show.35 Research into emotions oriented toward evolutionary theory seeks the roots of these images, as in Charles Darwin’s The Expressions of the Emotions in Man and Animals and Duchenne de Boulogne’s aesthetically experimental photography in Mécanisme de la physionomie humaine (both containing appropriate forewords and commentary by Paul Ekman).36 Through his correspondence and by questioning traveling salesmen and missionaries especially, Darwin had already attempted to establish cross-cultural comparisons of emotional expression. But it is Ekman and Friesen’s research that first takes on the challenge of broadly discussing, and “graphically revealing”, the global validity of emotional expression. Lee Hough, former director of ARPA, provided strong support to such scientific investigations of gestures and expressions as studies of visually isolated tribes in New Guinea (the South Fore People).37 Surprisingly, cultural studies as well as psychology have so far disregarded Ekman and Friesen’s earlier relationship with the US Department of Defense. Ekman’s much-discussed participation in post-9/11 US security policy (Ekman was an advisor in the Bush Administration and the founder of a surveillance-technology company) is, in itself, nothing new and continues earlier relationships.38 It is only by recognizing these relationships’ indivisibility from their ARPA context that we may fully appreciate the comprehensive media-historical background of studies of emotion, affect and facial expression. Firstly, it is no coincidence that the technologies of facial coding made meaningful forward strides in immediate proximity to the first networked computers; secondly, the Facial Action Coding System project (FACS) may thus be understood as an analogy to Noam Chomsky’s universal grammar, which was similarly developed as part of ARPA’s behavioral-scientific research.

The theoretical validity of a global affective language means to cancel out any translation difficulties in the spoken word. The tendency toward the globalization of the affect code compiled thus far is manifested as much in image atlases and catalogs of affect as in universal grammar and the language of popular images, since this code is precisely intended to be valid irrespective of space and time and thus also attain global reach in the service of a better understanding of facial expressions. If we assume that the above mentioned facial expressions may be traced to innate basic emotions, this neither forecloses the possibility that feelings may be simulated, nor implies that all humans are equally capable of recognizing emotions. Ekman certainly takes into account the potential contained in optical media such as television, which he treats as a training ground for facial recognition and which, therefore, may present a methodological challenge to intercultural studies: “Perhaps everyone learned their ‘universal’ expressions from watching Sesame Street on television!”39

In any case, global entertainment media are not the only ones standardizing facial expressions; psychology, with its own work, further contributes a bank of images of worldwide ubiquity. Ekman and Friesen’s attempts at coding created both a much-used and comparatively long-lasting research tool while also establishing an aesthetic of facial affect. If the coding of Facial Action focuses, first and foremost, on the configuration of eyes, nose, and mouth to be recognized, or on the surrounding patterns of movement, first mapped by Duchenne, manifested in a play of muscles on the skin’s surface (Facial Action can distinguish between static, slow, and fast facial signals) then we must recognize the pictorial tradition established by FACS as one important part of its scientific history. The particularly theatrical staging of the first photographic series has rightly been emphasized.40 Now this historical and technological development has taken a new turn. Psychology, theories of affect and emotion make “affect” available for computing machinery (translated into algorithms) and are one of the foundations of affective computing.


Psychological study of facial expressions as established by Ekman and Friesen along with Tomkins and Izard, in particular through the Facial Action Coding System, provides, along with other such studies, a significant basis for affective computing and for the development of emotionally intelligent objects.41 It is only after global standards for human interfaces – primarily of the face – have been established that it makes sense to trust digital technology with a (now also technically possible) mass evaluation of physiological data that aims to improve human-machine communication. Emotional psychology will then have done no less than provide media development with a semantics of standardized affective language implemented in human-machine interaction. Even Weigel’s description of the tendency to treat images of the human as objects of measurement rather than of hermeneutics still poses the question of technology too indistinctly. This question will become central in the Age of Affective Computing.

When seen from the perspective of media studies, timing plays a central role in affective computing. Not only does it designate the recurring theories and concepts that have been discussed under the label of affective computing. Rather, it concerns the a posteriori shift in meaning that concepts in the human sciences undergo when employed in interface design, affective or emotive computing or intelligent interactions.

The historic interplay of a particular branch of technology (networked computers) and the affective turn reveals an uncanny functional context: On the one hand, computers are the technological basis on which certain psychologies of emotion and affect (Tomkins’, Ekman’s and Friesen’s psychologies, most notably) were developed; through affective computing, on the other hand, computers now “receive” the scientific knowledge on emotion they made possible in the first place.

Affective computing thus is based on a temporality of complex, discontinuous and subsequently shifting relations between science and technology. The case of affective computing illustrates how the human sciences, relying on technology and experiment, directly serve the development of media. Neither affective computing nor psychology take their own historicity and media-technological condition into account.

1 Rosalind W. Picard, “Affective Computing,” M.I.T. Media Laboratory Perceptual Computing Section Technical Report (1995); idem, Affective Computing (Cambridge, Mass.: MIT Press, 2000). See also: IEEE Transactions on Affective Computing (New York, NY: IEEE, 2010).

2 Marie-Luise Angerer, Vom Begehren nach dem Affekt, (Zurich/Berlin: Diaphanes, 2007). English translation Desire After Affect (London: Rowman & Littlefield International, 2014).

3 Friedrich A. Kittler, Die Wahrheit der technischen Welt. Essays zur Genealogie der Gegenwart (Berlin: Suhrkamp, 2013); Erich Hörl, ed., Die technologische Bedingung. Beiträge zur Beschreibung der technischen Welt (Berlin: Suhrkamp, 2011).

4 Peter Galison, Image & Logic: A Material Culture of Microphysics (Chicago: The University of Chicago Press 1997).

5 Sigrid Weigel, “Phantombilder zwischen Messen und Deuten. Bilder von Hirn und Gesicht in den Instrumentarien empirischer Forschung von Psychologie und Neurowissenschaft,” in: Bettina Jago and Florian Steger, eds., Repräsentationen. Medizin und Ethik in Literatur und Kunst der Moderne (Heidelberg: Universitätsverlag C. Winter, 2004), p.159–198, here p. 159.

6 See: S. K. D’Mello et al., “AutoTutor Detects and Responds to Learners Affective and Cognitive States,” Workshop on Emotional and Cognitive issues in ITS, held in conjunction with the Ninth International Conference on Intelligent Tutoring Systems (Conference Proceedings 2008); S. K. D’Mello & A.C. Graesser, “AutoTutor and Affective AutoTutor: Learning by Talking with Cognitively and Emotionally Intelligent Computers that Talk Back,” ACM Transactions on Interactive Intelligent Systems, 2/4 (2012): p. 2–39.

7 Mark B. N. Hansen, “Medien des 21. Jahrhunderts, technisches Empfinden und unsere originäre Umweltbedingung,” in: Hörl, Die technologische Bedingung, p. 365–409; idem, “Ubiquitous Sensibility,” in: Jeremy Packer and Stephen B. Crofts Wiley, eds., Communication Matters. Materialist Approaches to Media, Mobility and Networks (London/New York: Routledge, 2012), p. 53–65.

8 Hörl, Die technologische Bedingung.

9 Sebastian Giessmann, Netze und Netzwerke. Archäologie einer Kulturtechnik, 1740–1840 (Bielefeld: Transcript, 2006); Alexander R. Galloway and Eugene Thacker, The Exploit: A Theory of Networks (Minneapolis: University of Minnesota Press, 2007).

10 Hansen, “Medien des 21. Jahrhunderts,” p. 366 (trans. Anna Tuschling and Maya Vinokour).

11 See also: Friedrich Kittler and Ana Ofak, eds., Medien vor den Medien (Munich: Wilhelm Fink, 2007); Bernhard Siegert and Joseph Vogl, eds., Europa: Kultur der Sekretäre (Zurich: Diaphanes, 2003).

12 Hansen, “Medien des 21. Jahrhunderts,” p. 371.

13 Marshall McLuhan, Understanding Media. The Extensions of Man (New York: McGraw Hill, 1964); Ernst Kapp, Grundlinien einer Philosophie der Technik (Braunschweig: George Westermann, 1877).

14 Angerer, Vom Begehren; Michaela Ott, Affizierung. Zu einer ästhetisch-epistemischen Figur (Munich: Edition Text + Kritik, 2010); Melissa Gregg and Gregory Seigworth, eds., The Affect Theory Reader (Durham/London: Duke University Press, 2010); Patricia T. Clough and Jean Halley, eds., The Affective Turn: Theorizing the Social (Durham, NC: Duke University Press, 2007).

15 Angerer, Vom Begehren.

16 See also: Lectures at the international conferences on “Affective Computing and Intelligent Interaction,” (September 2–5, 2013, Geneva, Switzerland), (retrieved February 26, 2014).

17 Picard, Affective Computing, p. 321.

18 D’Mello et al., AutoTutor, p. 6f.

19 Ibid., p. 6.

20 Picard, Affective Computing, p. 3.

21 D’Mello et al., AutoTutor.

22 Ibid., p. 1.

23 Ibid., p. 2.

24 Ibid., p. 1.

25 Ibid., p. 2.

26 Ibid., p. 1.

27 Ibid., p. 3f. and p. 9.

28 Ibid., p. 2.

29 Christos N. Moridis and Anastasios A. Economides, “Affective Learning: Empathetic Agents with Emotional Facial and Tone of Voice Expressions,” IEEE Transactions on Affective Computing 3/3 (2012): p. 260–272.

30 Rosalind Picard, “Emotion Research by the People, for the People,” Emotion Review, 2 (July 2010).

31 D’Mello et al., AutoTutor, p. 3f.

32 For the renewal of Tomkins’ approach in recent cultural theory, see: Eve Kosofsky Sedgwick, Touching Feeling. Affect, Pedagogy, Performativity (Durham, NC: Duke University Press, 2003).

33 Paul Ekman and Wallace V. Friesen, Unmasking the Face: A Guide to Recognizing Emotions from Facial Clues (Englewood Cliffs, NJ: Prentice-Hall, 1975), p. XI.

34 Ruth Leys, “How Did Fear Become a Scientific Object and What Kind of Object Is It?,” Representations 110 (2010): p. 66 -104, here p. 88; Weigel, “Phantombilder zwischen Messen und Deuten,” p. 166; Tim Dalgleish, D. Dunn Barnaby und Dean Mobbs, “Affective Neuroscience: Past, Present, and Future,” Emotion Review 1 (2009): p. 355–368.

35 Ruth Leys, From Guilt to Shame: Auschwitz and after (Princeton, NJ: Princeton University Press 2007); Leys, “How Did Fear Become a Scientific Object”; Sigrid Weigel, “Phantom Images: Face and Feeling in the Age of Brain Imaging,” Zeitschrift für Kunst- und Kulturwissenschaften 40 (2012): p. 33–53; idem, “Phantombilder zwischen Messen und Deuten.”

36 Charles Darwin, The Expression of the Emotions in Man and Animals, ed. Francis Darwin. The Works of Charles Darwin 23, ed. Paul Howard Barrett and Richard Brooke Freeman (London: William Pickering, 1989); Guillaume-Benjamin Duchenne de Boulogne, Mécanisme de la Physionomie Humaine (Paris: Librairie J.-B. Bailliere et Fils, 1876), (retrieved February 18, 2014).

37 Ekman and Friesen, Unmasking the Face, p. XI; Paul Ekman, “Facial Expressions” in: Tim Dalgleish and Mick J. Power, eds., Handbook of Cognition and Emotion (New York: John Wiley & Sons, 1999), p. 301–320, here p. 308.

38 Leys, “How Did Fear Become a Scientific Object?”, p. 66.

39 Ekman, “Facial Expressions,” p. 308.

40 Weigel, “Phantombilder zwischen Messen und Deuten,” p. 171.

41 Picard, Affective Computing, p. 16.

  • Zeitlichkeit
  • Künstliche Intelligenz
  • Emotionen
  • Wahrnehmung
  • Körper
  • Affekte
  • Affective Computing
  • Epistemologie
  • Interface

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Anna Tuschling

ist Juniorprofessorin für Medien und anthropologisches Wissen am Institut für Medienwissenschaft an der Ruhr-Universität Bochum. In ihrer Forschung beschäftigt sie sich mit Medienanthropologie, Medien der Affektforschung, Münchhausenmaschine, und medialen Lernwelten.

Weitere Texte von Anna Tuschling bei DIAPHANES
Marie-Luise Angerer (Hg.), Bernd Bösel (Hg.), ...: Timing of Affect

Affect, or the process by which emotions come to be embodied, is a burgeoning area of interest in both the humanities and the sciences. For »Timing of Affect«, Marie-Luise Angerer, Bernd Bösel, and Michaela Ott have assembled leading scholars to explore the temporal aspects of affect through the perspectives of philosophy, music, film, media, and art, as well as technology and neurology. The contributions address possibilities for affect as a capacity of the body; as an anthropological inscription and a primary, ontological conjunctive and disjunctive process as an interruption of chains of stimulus and response; and as an arena within cultural history for political, media, and psychopharmacological interventions. Showing how these and other temporal aspects of affect are articulated both throughout history and in contemporary society, the editors then explore the implications for the current knowledge structures surrounding affect today.