Media Theory and Ai
A.Y. 2024/2025
Learning objectives
The course will address the philosophical and biopolitical implications of the contemporary mediascape and in particular of AI-enabled technologies by combining the methodologies and conceptual frameworks of media theory, aesthetics, and visual culture. The course will provide students with a set of tools for examining the role of images and media technologies in shaping cultural hegemony, reframing subjective and intersubjective identities, and influencing public opinion on social and political issues, taking into account the complex set of discursive and bodily practices which underpin our relationship to images in the era of algorithmic media. Students will achieve the capacity to critically read contemporary phenomena as part of a broader history of images and media technologies and to identify the conflicts that, at different epochs, images and media have entailed.
Expected learning outcomes
By the end of the course, students will be able to master and discuss some of the fundamental notions of aesthetics and media theory as applied to digital technologies and to put them into practice for the critical analysis of media and visual documents, in order to single out emerging issues as well as social and political implications. Having developed the ability to understand the dynamics of power, the conflicts, and the resistance that images and media bear, they will be able to recognise and examine the multi-layered manifestations of social agency expressed in contemporary mediality. By leveraging the set of competencies acquired, they will be able to independently assess the complex impact of visual media, especially driven by AI technologies, on global dynamics and develop original interpretations.
Lesson period: First semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course can be attended as a single course.
Course syllabus and organization
Single session
Responsible
Lesson period
First semester
Course syllabus
Algorithmic Media and/as Global Conflicts
In the era of algorithmic media, technologies are not only instruments for human action, they have an agency of their own. Images are no longer representations that can convey absent realities, they are operational entities capable of producing them. Machines not only process information about the world but also realise content, interact with people, and come to inflect individual choices and collective decisions. But when did machines start to see for themselves? How did they gain the ability not just to select or archive, but to create? And how can their activity affect our understanding of and ways to approach the world, the others and ourselves?
AI-technologies are expected to bring about dramatic social and existential changes, especially with regard to work and human labour, and to play an unprecedented role in shaping cultural hegemony and eliciting processes of subjectivation. As much as these technologies are presented as transparent tools capable of overcoming many of the challenges of post-industrial societies, their increasing automation dissimulates a network of material and human infrastructures, that are deeply intertwined with geopolitical issues. In developing these questions, the course will focus on how AI technologies are not only capable of extending the range of human perception and action, but constitute themselves the ground of multi-layered global conflicts in our time.
In the era of algorithmic media, technologies are not only instruments for human action, they have an agency of their own. Images are no longer representations that can convey absent realities, they are operational entities capable of producing them. Machines not only process information about the world but also realise content, interact with people, and come to inflect individual choices and collective decisions. But when did machines start to see for themselves? How did they gain the ability not just to select or archive, but to create? And how can their activity affect our understanding of and ways to approach the world, the others and ourselves?
AI-technologies are expected to bring about dramatic social and existential changes, especially with regard to work and human labour, and to play an unprecedented role in shaping cultural hegemony and eliciting processes of subjectivation. As much as these technologies are presented as transparent tools capable of overcoming many of the challenges of post-industrial societies, their increasing automation dissimulates a network of material and human infrastructures, that are deeply intertwined with geopolitical issues. In developing these questions, the course will focus on how AI technologies are not only capable of extending the range of human perception and action, but constitute themselves the ground of multi-layered global conflicts in our time.
Prerequisites for admission
None
Teaching methods
The course aims to introduce, through lectures, case study presentations, and Q&A sessions, the theoretical framework and key tools of media theory and aesthetics for an operational analysis of digital and AI technologies. Students will be constantly encouraged to actively contribute and participate in the examination of materials and documents through collective discussion and cooperative interaction tools. The final part of the course will be devoted to practising the critical analysis of media phenomena as well as visual and audio-visual content, through individual and group work in which students will be able to put their acquired skills to the test.
Teaching Resources
Crawford, Kate. Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. Yale University Press, 2022.
Crawford, Kate, and Trevor Paglen. "Excavating AI: The Politics of Images in Machine Learning Training Sets." 2019. https://excavating.ai.
Pasquinelli, Matteo, and Vladan Joler. "The Nooscope Manifested: AI as Instrument of Knowledge Extractivism." Interface Critique 3 (2021): 37-68.
Benjamin, Walter. "The Work of Art in the Age of Its Technological Reproducibility [First Version]." Grey Room 39 (2010): 11-37. (passim) https://doi.org/10.1162/grey.2010.1.39.11.
Kittler, Friedrich A. "There is no Software." Stanford Literature Review 9, no. 1 (1992): 81-90.
Munn, Luke. "Automation is a Myth." In Materializing Digital Futures: Touch, Movement, Sound and Vision, edited by Toija Cinque and Jordan Beth Vincent. Bloomsbury, 2022.
Farocki, Harun. "Phantom Images." Public 29 (2004): 13-22. https://public.journals.yorku.ca/index.php/public/article/download/30354/27882/31077.
Paglen, Trevor. "Operational Images." E-Flux 59 (2014). https://www.e-flux.com/journal/59/61130/operational-images/.
Ways of Machine Seeing, special issue of AI & Society 36 (2021) (selected articles).
Somaini, Antonio. "Algorithmic Images: Artificial Intelligence and Visual Culture." Grey Room 93 (2023): 74-115.
Somaini, Antonio. "On the Photographic Status of Images Produced by Generative Adversarial Networks (GANs)." Philosophy of Photography 13, no. 1 (2022): 153-164.
Meyer, Roland. "Operative Portraits. Or How Our Faces Became Big Data." In Reconfiguring the Portrait, edited by Abe Geil and Tomáš Jirsa, 21-42. Edinburgh: Edinburgh University Press, 2023.
Galdeano, Alexandre, et al. "Developmental Learning for Social Robots in Real-World Interactions." Paper presented at the First Workshop on Social Robots in the Wild, 13th Annual ACM/IEEE International Conference on Human-Robot Interaction (HRI 2018), Chicago, IL, March 2018.
Additional texts for non-attending students (6 CFU):
Natale, Simone. Deceitful Media: Artificial Intelligence and Social Life after the Turing Test. Oxford University Press, 2021.
Crawford, Kate, and Trevor Paglen. "Excavating AI: The Politics of Images in Machine Learning Training Sets." 2019. https://excavating.ai.
Pasquinelli, Matteo, and Vladan Joler. "The Nooscope Manifested: AI as Instrument of Knowledge Extractivism." Interface Critique 3 (2021): 37-68.
Benjamin, Walter. "The Work of Art in the Age of Its Technological Reproducibility [First Version]." Grey Room 39 (2010): 11-37. (passim) https://doi.org/10.1162/grey.2010.1.39.11.
Kittler, Friedrich A. "There is no Software." Stanford Literature Review 9, no. 1 (1992): 81-90.
Munn, Luke. "Automation is a Myth." In Materializing Digital Futures: Touch, Movement, Sound and Vision, edited by Toija Cinque and Jordan Beth Vincent. Bloomsbury, 2022.
Farocki, Harun. "Phantom Images." Public 29 (2004): 13-22. https://public.journals.yorku.ca/index.php/public/article/download/30354/27882/31077.
Paglen, Trevor. "Operational Images." E-Flux 59 (2014). https://www.e-flux.com/journal/59/61130/operational-images/.
Ways of Machine Seeing, special issue of AI & Society 36 (2021) (selected articles).
Somaini, Antonio. "Algorithmic Images: Artificial Intelligence and Visual Culture." Grey Room 93 (2023): 74-115.
Somaini, Antonio. "On the Photographic Status of Images Produced by Generative Adversarial Networks (GANs)." Philosophy of Photography 13, no. 1 (2022): 153-164.
Meyer, Roland. "Operative Portraits. Or How Our Faces Became Big Data." In Reconfiguring the Portrait, edited by Abe Geil and Tomáš Jirsa, 21-42. Edinburgh: Edinburgh University Press, 2023.
Galdeano, Alexandre, et al. "Developmental Learning for Social Robots in Real-World Interactions." Paper presented at the First Workshop on Social Robots in the Wild, 13th Annual ACM/IEEE International Conference on Human-Robot Interaction (HRI 2018), Chicago, IL, March 2018.
Additional texts for non-attending students (6 CFU):
Natale, Simone. Deceitful Media: Artificial Intelligence and Social Life after the Turing Test. Oxford University Press, 2021.
Assessment methods and Criteria
For attending students, the overall assessment of the theoretical and applied skills acquired will be based on: a final oral examination focusing on the bibliography and learning materials provided (50%), on the preparation of individual and collective work (30%), and on the active participation during classes (20%). Self-assessment tools will be provided to attending students during the course. For non-attending students, the knowledge and competences developed will be assessed by a final oral examination.
L-ART/06 - CINEMA, PHOTOGRAPHY AND TELEVISION - University credits: 3
M-FIL/04 - AESTHETICS - University credits: 3
M-FIL/04 - AESTHETICS - University credits: 3
Lessons: 48 hours
Professor:
Dalmasso Anna Caterina
Professor(s)
Reception:
Wednesday 2-4 p.m. Please contact me to schedule an appointment
Festa del Perdono campus or Microsoft Teams