Call for papers| RCL nº. 67 |"The Animation of Images: Technics, Perception and Algorithmic Generation"
Ascribing life to images has a long history. Cult figures, statues, effigies and paintings have, over time, been described or experienced as entities capable of seeing, moving or acting upon those who engage with them. As David Freedberg (1989) and W. J. T. Mitchell (2005) have shown, our relation to images is not confined to recognising their representational character; it also involves forms of response through which presence or a capacity for action is attributed to them.
The development of technical media altered the material and perceptual conditions under which such attributions may occur. From optical toys to cinema, video and digital technologies, different devices endowed images with properties such as movement and duration, as well as new effects of presence. Animation can thus be conceptualised through the articulation of technical operations and perceptual conditions that can give an image the appearance of vitality.
The recent proliferation of generative artificial intelligence systems recasts this problem. By allowing images to take shape and become visible through algorithmic processes, these systems link visual production to forms of automation that enable images to respond and transform according to commands, data or interactions (Manovich, 2019; Zylinska, 2020).
From a text prompt or a pre-existing image, new images can be created, existing ones altered, given duration and movement, or integrated into interfaces and interactive processes. Practices such as the generative animation of photographs, image-to-video, text-to-video, or the production of avatars and interactive figures reconfigure operations of manipulation, sequencing and interpolation associated with earlier techniques, while introducing specific modes of generation, mutation and interaction (Manovich & Arielli, 2024). The boundaries between automatism, responsiveness and animation consequently become increasingly porous.
This special issue seeks to situate these practices within a broader history of technologically mediated animation, while examining how algorithmic generation changes the terms through which animation can be thought and described, particularly in relation to its temporal, processual and relational qualities. In certain generative systems, images can remain continuously open to transformation over the course of an interaction, varying according to information received and integrated by the system. They may therefore appear responsive and adaptive, while their modes of response introduce degrees of indeterminacy and unpredictability. This shift from images that move according to predetermined sequences to figures that are visual manifestations of systems capable of processing data and responding in real time invites a reconsideration of the relationship between automatism and animation, particularly as many of these capabilities remain under development and the full breadth of their implications is not yet clear.
One such implication concerns the ways in which images are experienced and interpreted. Apparently spontaneous responses may intensify a sense of presence and encourage affective involvement, while the resemblance of synthetic figures to human modes of expression and behaviour may, under certain circumstances, prompt attributions of intention, sensitivity or agency.
The increasing verisimilitude of generative images adds an epistemological dimension to these questions. As synthetic figures, objects and scenarios become increasingly plausible in appearance and behaviour, the distinction between recording and synthesis may become less evident. At the same time, this appearance of reality may reinforce the perception of animation by bringing synthetic images closer to forms and behaviours ordinarily associated with living beings. Verisimilitude therefore bears both on the status attributed to the image and on the conditions under which it is perceived as animated.
We invite article submissions that address the animation of images as a technical, aesthetic and media-related problem, with particular attention to the questions raised by algorithmic generation. We also welcome studies of the material and technical characteristics of animated and generative images; of automation, responsiveness, interactivity and interfaces; of changing relations between still and moving images; and of emerging generative practices and their aesthetic, affective and epistemological implications. Historical or archaeological approaches that help contextualise these transformations are also welcome, as are studies examining how literature, cinema and other artistic practices have conceptualised and problematised the animation of images.
Possible topics include, but are not limited to:
- Archaeologies of technologically mediated animation and devices for the production of movement;
- Optical toys, chronophotography and pre-cinematic animation technologies;
- Cinematic animation and techniques for the artificial production of movement;
- Computer graphics, digital images and the automation of animation;
- Generative artificial intelligence and moving images;
- Text-to-video, image-to-video and video-to-video technologies;
- Algorithmic animation of photographs and visual archives;
- Generation, interpolation and algorithmic extension of movement;
- Camera movement and the algorithmic expansion of represented space;
- Synthetic bodies, faces and characters;
- Responsiveness, real-time interaction and adaptive image systems;
- Avatars, digital doubles and interactive interfaces;
- Animation, inference and algorithmic motion prediction;
- Continuities and ruptures between traditional, digital and generative animation;
- Authorship, control and automation in animation processes;
- Aesthetics, error, indeterminacy and unpredictability in generative images;
- Contemporary transformations of montage, continuity and duration;
- Presence, agency and the attribution of intentional or cognitive capacities to images;
- New relationships between photography, cinema and animation in a generative context;
- Anxieties, fears and critical imaginaries surrounding the apparent autonomy, responsiveness and capacity for transformation of synthetic images.
References
Beckman, Karen, ed. 2014. Animating film theory. Duke University Press.
Bouko, Catherine, and Nicolas Laba, eds. 2026. Six critical lenses on AI-generated images. CRC Press.
Buchan, Suzanne, ed. 2014. Pervasive Animation. Routledge.
Conte, Philippe, Anna Caterina Dalmasso, Massimo G. Dondero, and Antonio Pinotti, eds. 2026. Algomedia: The Image at the Time of Artificial Intelligence. Springer.
Freedberg, David. 1989. The power of images: Studies in the history and theory of response. University of Chicago Press.
Lee, K. B., Francesca Mazzarino, and M. de Dardel, eds. 2026. The future of reality. Diaphanes.
Manovich, Lev. 2019. AI aesthetics. Strelka Press.
Manovich, Lev, and Emanuele Arielli. 2024. Artificial aesthetics: Generative AI, art and visual media.
Mitchell, W. J. T. 2005. What do pictures want? The lives and loves of images. University of Chicago Press.
Zielinski, Siegfried. 2006. Deep time of the media: Toward an archaeology of hearing and seeing by technical means. MIT Press.
Zylinska, Joanna. 2020. AI art: Machine visions and warped dreams. Open Humanities Press.
Submission Details and deadlines
Full manuscript submission deadline: May 31, 2027
Review process: July to October 2027
Editors’ decision: October 2027
Expected publication date: November 2027
Articles can be written in English, French, Spanish or Portuguese and will be blind peer reviewed. Visual essays will also be accepted. Formatting must be in accordance with the journal’s submission guidelines, and the submission must be made via the OJS platform of the Revista de Comunicação e Linguagens (RCL).
At the time of submission, please indicate (in the comments section) the issue number of the journal to which you wish to submit your manuscript.
Editors
- Carlos Natálio (Universidade Católica Portuguesa, School of Arts, Research Center for Science and Technology of the Arts)
- Manuel Bogalheiro (CICANT, Lusófona University)
- Tiago Ramos (ICNOVA, NOVA University Lisbon)
