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Oggetto:

ONC0263B Philosophy of Medicine and AI

Oggetto:

Philosophy of Medicine and AI

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Academic year 2024/2025

Course ID
ONC0263B
Teacher
Vincenzo Crupi (Lecturer)
Year
2nd year
Teaching period
First semester
Type
Distinctive
Credits/Recognition
5
Course disciplinary sector (SSD)
M-FIL/02 - logic and philosophy of science
Delivery
Formal authority
Language
English
Attendance
TBD
Type of examination
Written and oral
Type of learning unit
modulo
Modular course
The impact of Economics, Law and Humanities in a Data-Driven World (ONC0263)
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Sommario del corso

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Course objectives

The course aims at addressing foundational issues in the connection between medicine and artificial intelligence. It will draw on a strong interdisciplinary background including the philosophy of biology and medicine as branches of contemporary philosophy of science, insights from cognitive and behavioral sciences, and thriving research on philosophical and societal challenges for artificial intelligence and machine learning.

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Results of learning outcomes

Students who successfully complete the course will understand basic elements of the philosophy of medicine and of the implications of contemporary artificial intelligence for decision making in clinical settings. They will learn to acknowledge and discuss different ways in which tools from artificial intelligence can be integrated with, and fostered by, knowledge and techniques in biology, medicine, and healthcare. The skills developed in the course will enhance a critical attitude towards such integration, including an awareness of scholarly analyses of its risks and opportunities and appreciation of relevant case-studies.

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Program

Topics addressed include both key concepts and fundamental problems to be clarified and discussed in an interdisciplinary perspective.

KEY CONCEPTS:
– prediction and prognosis
– causation and diagnosis
– intervention and treatment
– testing and learning
– models and modelling
– explanation and explainability
– bias and error

KEY PROBLEMS:
– strengths and limitations of human vs. artificial intelligence
– methodological challenges of AI in biology, medicine, and healthcare
– ethical and societal challenges of AI in biology, medicine, and healthcare

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Course delivery

Meetings will take place in attendance (in the classroom) and will include lectures as well as interactive tasks. Teaching materials will be made available through the Moodle platform.

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Learning assessment methods

The assessment of learning achievements will be made by (i) a test at the end of the term and (ii) the presentation of an essay or project based on relevant assigned readings (a detailed list will be provided). Assessment will be on a 0-30 scale. To meet the course requirements students will have to be able to describe and discuss the central issues addressed in class on the basis of the notions and skills acquired, including clarity and informed use of the terminology.

Suggested readings and bibliography

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A detailed list of readings assignments and suggestion (including relevant material for the final essay) will be made available in Materiale didattico and on the Moodle platform. By way of illustration, here are three key references from the literature on the target topics:

J. STEGENGA, Care and Cure: An Introduction to Philosophy of Medicine. University of Chicago Press, 2018

J. PEARL and D. MACKENZIE, The Book of Why: The New Science of Cause and Effect. Penguin, 2019

S. RUSSELL, Human Compatible: AI and the Problem of Control. Penguin, 2020



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