PHILOSOPHY OF ARTIFICIAL INTELLIGENCE

Anno accademico
2025/2026 Programmi anni precedenti
Titolo corso in inglese
PHILOSOPHY OF ARTIFICIAL INTELLIGENCE
Codice insegnamento
FM0652 (AF:581009 AR:326938)
Lingua di insegnamento
Inglese
Modalità
In presenza
Crediti formativi universitari
6
Livello laurea
Laurea magistrale (DM270)
Settore scientifico disciplinare
M-FIL/02
Periodo
2° Periodo
Anno corso
2
The course frames the rise of AI not merely as a technical achievement but as part of the long history of cultural techniques and philosophical paradigms. AI is illustrated as a problem of externalisation of mental models and internalisation of technical models within the mind, which are fundamental problems of philosophy and, in particular, epistemology. This dialectical relationship between cognition, language, and techniques, however, is not approached in the abstract. Instead, it is situated in the historical conflicts and tensions of each historical epoch (see, for example, the social definitions of intellectual abilities and disabilities). In this way the course bridges with the other department courses on political philosophy and political epistemology.
Students will be able to critically discuss the position of AI in the philosophical debate and in the present society, with a critical perspective on both its ideological dimensions and material applications. In this sense, students will study and comprehend the material causes of the historical development of AI, particularly its intrinsic logical form, that is how it actually works in mathematical terms. This aspect is often neglected in many introductory AI courses. Knowledge of AI’s technical foundations will be used to analyze and critique its reception in philosophy, on one hand, and its societal applications on the other—from labor automation and scientific research to cultural heritage analysis and generation of artefacts. Students will learn to assess the risks and opportunities of AI especially in the humanities.
Students must possess a good level of education. A strong technical and philosophical preparation is not a necessary.
01 The Material Tools of Algorithmic Thinking
02 Babbage and the Mechanisation of Mental Labour
03 The Machinery Question
04 Origins of Marx’s General Intellect
05 The Abstraction of Labour
06 The Self-Organisation of the Cybernetic Mind
07 The Automation of Pattern Recognition
08 Hayek and the Epistemology of Connectionism
09 The Invention of the Perceptron
10 The Automation of General Intelligence
Main texts:
- Gould, Stephen Jay. The Mismeasure of Man. New York: Norton & Company, 1981.
- Pasquinelli, Matteo. The Eye of the Master: A Social History of Artificial Intelligence. London: Verso Books, 2023.

Secondary texts:
- Renn, Jürgen. The Evolution of Knowledge: Rethinking Science for the Anthropocene. Princeton University Press, 2020.
- Bates, David. An Artificial History of Natural Intelligence: Thinking with Machines from Descartes to the Digital Age. University of Chicago Press, 2024.
- Liu, Lydia. The Freudian Robot: Digital Media and the Future of the Unconscious. University of Chicago Press, 2011.
- Hayles, N. Katherine. Unthought: The Power of the Cognitive Nonconscious. University of Chicago press, 2017.
Oral examination at the end of the course. Participation in class discussion or email exchange with the professor will be highly valorised.
orale
According to the department standards.
- Mostly frontal lectures, in which the professor will introduce students to the topics of the course and provide step-by-step explanations where necessary.
- Dialogic seminars, in which students will interact with their classmates and the professor on specific assigned texts.
- Students presentations in class (encouraged).
- Guest speakers from international universities.

Questo insegnamento tratta argomenti connessi alla macroarea "Capitale umano, salute, educazione" e concorre alla realizzazione dei relativi obiettivi ONU dell'Agenda 2030 per lo Sviluppo Sostenibile

Programma definitivo.
Data ultima modifica programma: 11/04/2025