Teaching code

4S012292

Teacher

Massimiliano Badino

Coordinator

Massimiliano Badino

Credits

6

Also offered in courses:

• Philosophy of Science of the course Master's degree in Linguistics
• Epistemology and Philosophy of Science of the course Master's degree in Philosophy

Language

Italian

Scientific Disciplinary Sector (SSD)

M-FIL/02 - LOGIC AND PHILOSOPHY OF SCIENCE

Period

Sem. 1B dal Nov 11, 2024 al Dec 21, 2024.

Courses Single

Authorized

Lessons timetable Moodle Seminars 0

Learning objectives

The course explores the relationships between the models of production, justification, and dissemination of knowledge and the development of artificial intelligence. From an educational perspective, the objective is twofold. On one hand, it will discuss how artificial intelligence represents the culmination of a computational representation of knowledge and cognition that has found in the modern digital computer a model of the human mind. On the other hand, it will show that artificial intelligence raises fundamental epistemological problems regarding the type of knowledge produced, the forms of its justification, and its impact on the social structure of scientific research. The course will be conducted using two main modalities: (1) traditional lectures and (2) seminar presentations. The lectures will be held in person and will not be streamed or recorded. Dedicated videos will be made available for: (1) explaining the examination procedures and grading, and (2) delving into specific parts of the course and important concepts. Although these videos are primarily intended as study support for non-attending students, attending students can also make use of them.

Prerequisites and basic notions

The course requires knowledge of the fundamental concepts of the philosophy of science and the philosophy of mind. No prior knowledge of computer science or artificial intelligence is required. To facilitate the learning of the more conceptually challenging parts, in-depth videos will be provided.

Program

The course aims to explore some the assumptions and philosophical consequences of artificial intelligence for the production of knowledge and the social and political application of technology.
The course program is divided into three parts.
The first part introduces some philosophical preliminaries to the understanding of artificial intelligence: the concept of probability, the problem of induction, the notion of cognition and the problem of statistical inference.
The second part will deal with the epistemological problems of machine learning and data science: the concept of data, the inferential notion of learning, statistical learning theory, logical approach vs. connectionism.
The third part will deal with the social, cultural and political consequences of artificial intelligence, with special reference to generative artificial intelligence.

Bibliography

Didactic methods

The course will be conducted using two main modalities: (1) traditional lectures and (2) seminar presentations. The lectures will be held in person and recorded. Dedicated videos will be made available for: (1) explaining the examination procedures and grading, and (2) delving into specific parts of the course and important concepts. Although these videos are primarily intended as study support for non-attending students, attending students can also make use of them.

Learning assessment procedures

The final evaluation aims to determine not only the possession of knowledge but also the candidates' ability to argue correctly, to appropriately use the concepts and tools of the philosophy of science, and their creativity. The grade is obtained based on active participation in the seminar part, a paper (2000-5000 words) on a relevant topic related to the course, to be agreed upon with the instructor, and an oral examination according to the following proportions:
- 35% Oral examination
- 40% Paper (2000-5000 words)
- 25% In-class presentation
The in-class presentation on a topic to be agreed upon with the instructor can also be done in a small group (maximum 3 people).

Evaluation criteria

The main assessment criteria are: (1) conceptual competence and (2) linguistic competence. Students will also find an evalutation rubric to help them compose the assignments.

Criteria for the composition of the final grade

- 35% Oral examination
- 40% Essay (2000-5000 words)
- 25% In-class presentation

Exam language

Italian and English