PHILOSOPHY OF ARTIFICIAL INTELLIGENCE

The course frames the making of AI not merely as a technical achievement but as part of the long history of cultural techniques and philosophical paradigms. It covers the rise of algorithmic thinking from ancient mathematics to the early experiment in automated computation during the industrial age, and in particular it clarifies the different genealogies of AI in the 20th century. The course provides a precise framing of AI: it illustrates AI 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, body, language, and techniques, however, is not approached in the abstract. Instead, it is situated in the social dynamics and tensions of each historical epoch (see, for example, the 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 assess 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 AI actually works in technical and 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 in society and especially in the humanities.

Students must possess a good level of education. A technical and philosophical preparation is not 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:
- Pasquinelli, Matteo. The Eye of the Master: A Social History of Artificial Intelligence. London: Verso Books, 2023. Italian translation: Nell’occhio dell’algoritmo: Storia e critica dell’intelligenza artificiale.
Roma: Carocci, 2025.
- Gould, Stephen Jay. The Mismeasure of Man. New York: Norton & Company, 1981.

Optional 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.

Oral examination at the end of the course. The final exam will be divided in two parts: the first part assessing the knowledge of the course materials; the second part testing the capacity for critical and independent thinking.

orale

Il/la docente ha il dovere di vigilare affinché siano rispettate le regole di autenticità e originalità delle prove d'esame. Di conseguenza, nei casi in cui vi sia il sospetto di un comportamento irregolare, l'esame può prevedere un ulteriore approfondimento, contestuale alla prova d'esame, che potrà essere realizzato anche in modalità differente rispetto alle modalità sopra riportate.

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.
- 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 other national and 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