Media Theory and Ai
A.Y. 2025/2026
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 cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
First semester
Course syllabus
Prophetic Media. Visualising the Future, Envisioning History
Devoting a special focus to the transformative impact of the ongoing algorithmic revolution, the course will examines how visual media and image-making techniques influence our ability to visualise, predict, and pre-empt reality, particularly in the context of global relations and conflicts.
Media theorist Friedrich Kittler argued that technologies are not merely neutral tools; rather, they define the material foundations and structural limits of human thought, shaping our perception of the world and determining our epistemic frameworks. By selecting, filtering and archiving data, media and technologies set the boundaries of what is visible, thinkable, speakable, and recordable in any given era, and therefore what can be transmitted to the future.
"What remains of people is what media can store and communicate": civilizations do not leave behind what they experienced, but rather what their technical supports were capable of recording and preserving. Within this framework of mutual dependence between technologies and regimes of vision and discourse, algorithmic media bring about a fundamental shift: by replacing archives with datasets and operating through probabilistic models, they not only shape how we are able to record the present and remember the past, but also perform a predictive role, constantly anticipating the time to come. The course will explore the emergence of this tendency by situating it within a broader framework of media as predictive technologies.
Devoting a special focus to the transformative impact of the ongoing algorithmic revolution, the course will examines how visual media and image-making techniques influence our ability to visualise, predict, and pre-empt reality, particularly in the context of global relations and conflicts.
Media theorist Friedrich Kittler argued that technologies are not merely neutral tools; rather, they define the material foundations and structural limits of human thought, shaping our perception of the world and determining our epistemic frameworks. By selecting, filtering and archiving data, media and technologies set the boundaries of what is visible, thinkable, speakable, and recordable in any given era, and therefore what can be transmitted to the future.
"What remains of people is what media can store and communicate": civilizations do not leave behind what they experienced, but rather what their technical supports were capable of recording and preserving. Within this framework of mutual dependence between technologies and regimes of vision and discourse, algorithmic media bring about a fundamental shift: by replacing archives with datasets and operating through probabilistic models, they not only shape how we are able to record the present and remember the past, but also perform a predictive role, constantly anticipating the time to come. The course will explore the emergence of this tendency by situating it within a broader framework of media as predictive technologies.
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, aesthetics and visual culture for critical analysis. 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
Attending students (6 CFU):
F. Kittler, Gramophone, Film, Typewriter, Stanford University Press, 1999 (passim).
R. Grusin, Premediation: Affect and Mediality after 9/11, Palgrave Macmillan, 2010 (to be read in full).
H. Farocki, Phantom Images. Public 29, 2004: 13-22.
T. Paglen, Operational Images. E-Flux 59 (2014).
R. Uliasz, Seeing like an algorithm: Operative images and emergent subjects. AI & Society, 36(4), 2021, 1233-1241.
K. Crawford, V. Joler, Anatomy of an AI system. The Amazon Echo as an anatomical map of human labor, data and planetary resources. (2018) https://anatomyof.ai/
K. Crawford, T. Paglen, Excavating AI. The politics of images in machine learning training sets. September 19 (2019). https://excavating.ai
K. Crawford, V. Joler, Calculating Empires. A Genealogy of Technology and Power Since 1500 (2023) https://calculatingempires.net/
L. Munn, Automation is a Myth. In Materializing Digital Futures: Touch, Movement, Sound and Vision, edited by Toija Cinque and Jordan Beth Vincent. Bloomsbury, 2022.
R. Meyer, 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.
M. Jablonowski, Beyond drone vision: the embodied telepresence of first-person-view drone flight, The Senses and Society, 15:3, 2020, 344-358.
A. Somaini, Algorithmic Images: Artificial Intelligence and Visual Culture. Grey Room 93, 2023: 74-115.
A. Somaini, On the Photographic Status of Images Produced by Generative Adversarial Networks (GANs). Philosophy of Photography 13, no. 1, 2022: 153-164.
One book of your choice from the following (to be read in full):
J. E. Dobson, The Birth of Computer Vision. University of Minnesota Press, 2023.
A. Bousquet, The Eye of War. Military Perception from the Telescope to the Drone, University Of Minnesota Press, 2018.
Non-attending students (6 CFU) must, in addition to all of the above, choose one book from the following (to be read in full):
E. Finn, What Algorithms Want: Imagination in the Age of Computing, MIT Press, 2017.
J. Zylinska, AI Art. Machine Visions and Warped Dreams. Open Humanities Press, 2020.
S. Natale, Deceitful Media: Artificial Intelligence and Social Life after the Turing Test. Oxford University Press, 2021.
F. Kittler, Gramophone, Film, Typewriter, Stanford University Press, 1999 (passim).
R. Grusin, Premediation: Affect and Mediality after 9/11, Palgrave Macmillan, 2010 (to be read in full).
H. Farocki, Phantom Images. Public 29, 2004: 13-22.
T. Paglen, Operational Images. E-Flux 59 (2014).
R. Uliasz, Seeing like an algorithm: Operative images and emergent subjects. AI & Society, 36(4), 2021, 1233-1241.
K. Crawford, V. Joler, Anatomy of an AI system. The Amazon Echo as an anatomical map of human labor, data and planetary resources. (2018) https://anatomyof.ai/
K. Crawford, T. Paglen, Excavating AI. The politics of images in machine learning training sets. September 19 (2019). https://excavating.ai
K. Crawford, V. Joler, Calculating Empires. A Genealogy of Technology and Power Since 1500 (2023) https://calculatingempires.net/
L. Munn, Automation is a Myth. In Materializing Digital Futures: Touch, Movement, Sound and Vision, edited by Toija Cinque and Jordan Beth Vincent. Bloomsbury, 2022.
R. Meyer, 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.
M. Jablonowski, Beyond drone vision: the embodied telepresence of first-person-view drone flight, The Senses and Society, 15:3, 2020, 344-358.
A. Somaini, Algorithmic Images: Artificial Intelligence and Visual Culture. Grey Room 93, 2023: 74-115.
A. Somaini, On the Photographic Status of Images Produced by Generative Adversarial Networks (GANs). Philosophy of Photography 13, no. 1, 2022: 153-164.
One book of your choice from the following (to be read in full):
J. E. Dobson, The Birth of Computer Vision. University of Minnesota Press, 2023.
A. Bousquet, The Eye of War. Military Perception from the Telescope to the Drone, University Of Minnesota Press, 2018.
Non-attending students (6 CFU) must, in addition to all of the above, choose one book from the following (to be read in full):
E. Finn, What Algorithms Want: Imagination in the Age of Computing, MIT Press, 2017.
J. Zylinska, AI Art. Machine Visions and Warped Dreams. Open Humanities Press, 2020.
S. Natale, 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.
For both attending and non attending students, the final oral exam consists of 20-minute oral discussion, designed to assess the students' understanding of the main concepts introduced during the course, their ability to explain with clarity and to link the different topics and issues addressed, their capacity to analyse case studies with appropriate theoretical tools and critical awareness.
For both attending and non attending students, the final oral exam consists of 20-minute oral discussion, designed to assess the students' understanding of the main concepts introduced during the course, their ability to explain with clarity and to link the different topics and issues addressed, their capacity to analyse case studies with appropriate theoretical tools and critical awareness.
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:
Thursday 4-6 p.m. Please contact me to schedule an appointment
Festa del Perdono campus or Microsoft Teams