ID:
509515
Durata (ore):
48
CFU:
6
SSD:
SOCIOLOGIA DEI PROCESSI CULTURALI E COMUNICATIVI
Anno:
2024
Dati Generali
Periodo di attività
Secondo Semestre (03/03/2025 - 13/06/2025)
Syllabus
Obiettivi Formativi
Students will:
- acquire knowledge of some of the main issues concerning the societal impact of AI;
- be able to apply the conceptual tools discussed over the course to concrete specific cases;
- be able to use critical skills to autonomously evaluate the societal impact of new AI technologies;
- learn how to effectively communicate their ideas to non-expert audiences;
- be able to analyze problems stemming from the use of AI systems from a socio-technical perspective.
- acquire knowledge of some of the main issues concerning the societal impact of AI;
- be able to apply the conceptual tools discussed over the course to concrete specific cases;
- be able to use critical skills to autonomously evaluate the societal impact of new AI technologies;
- learn how to effectively communicate their ideas to non-expert audiences;
- be able to analyze problems stemming from the use of AI systems from a socio-technical perspective.
Prerequisiti
Students should have basic knowledge of the main techniques used in AI. No prior knowledge of the specific issues addressed by the course is required.
Metodi didattici
The course will be articulated in lectures, seminars and in-class discussions of case studies. Students will be given the possibility to make group presentations on the topics of the course.
Verifica Apprendimento
Oral exam aiming at assessing the students' knowledge of the reference texts and critical elaboration capacities.
Here is an approximate evaluation table:
- 30-30L: excellent knowledge and good critical elaboration capacities;
- 27-29: good knowledge of the reference texts, accompanied by sufficient critical elaboration capacities;
- 22-26: adequate knowledge of the reference texts, with little to no critical elaboration capacities;
- 18-21: limited knowledge of the reference texts, with no critical elaboration capacities;
Poor knowledge of the reference texts will result in the exam failure.
Students will have the opportunity to give group presentations at the end of the course (more details will be provided during the first lesson). If positively evaluated, the presentation will grant up to two bonus points to be added to the oral exam grade.
Here is an approximate evaluation table:
- 30-30L: excellent knowledge and good critical elaboration capacities;
- 27-29: good knowledge of the reference texts, accompanied by sufficient critical elaboration capacities;
- 22-26: adequate knowledge of the reference texts, with little to no critical elaboration capacities;
- 18-21: limited knowledge of the reference texts, with no critical elaboration capacities;
Poor knowledge of the reference texts will result in the exam failure.
Students will have the opportunity to give group presentations at the end of the course (more details will be provided during the first lesson). If positively evaluated, the presentation will grant up to two bonus points to be added to the oral exam grade.
Testi
[1] Johnson, D.G., Verdicchio, M. (2017). Reframing AI Discourse. Minds & Machines, 27, 575–590. https://doi.org/10.1007/s11023-017-9417-6
[2] Mitchell, M. (2021). Why AI is harder than we think. https://arxiv.org/abs/2104.12871
[3] Natale, S. (2021). Deceitful media: Artificial intelligence and social life after the Turing test. New York: Oxford University Press.
[4] Nordström, M. (2022). AI under great uncertainty: implications and decision strategies for public policy. AI & Society, 37, 1703–1714. https://doi.org/10.1007/s00146-021-01263-4
[5] van de Poel, I. (2016). An Ethical Framework for Evaluating Experimental Technology. Science and Engineering Ethics, 22, 667–686. https://doi.org/10.1007/s11948-015-9724-3
[6] Zanotti, G., Chiffi, D. & Schiaffonati, V. (2024). AI-Related Risk: An Epistemological Approach. Philosophy & Technology, 37, 66. https://doi.org/10.1007/s13347-024-00755-7
Additional material (not required for the exam) will be provided throughout the course.
Note: [1], [2], [4], [5], [6] are available free of charge, either directly from the links or through the institutional login system.
[2] Mitchell, M. (2021). Why AI is harder than we think. https://arxiv.org/abs/2104.12871
[3] Natale, S. (2021). Deceitful media: Artificial intelligence and social life after the Turing test. New York: Oxford University Press.
[4] Nordström, M. (2022). AI under great uncertainty: implications and decision strategies for public policy. AI & Society, 37, 1703–1714. https://doi.org/10.1007/s00146-021-01263-4
[5] van de Poel, I. (2016). An Ethical Framework for Evaluating Experimental Technology. Science and Engineering Ethics, 22, 667–686. https://doi.org/10.1007/s11948-015-9724-3
[6] Zanotti, G., Chiffi, D. & Schiaffonati, V. (2024). AI-Related Risk: An Epistemological Approach. Philosophy & Technology, 37, 66. https://doi.org/10.1007/s13347-024-00755-7
Additional material (not required for the exam) will be provided throughout the course.
Note: [1], [2], [4], [5], [6] are available free of charge, either directly from the links or through the institutional login system.
Contenuti
The course will explore some of the main societal implications of AI. First, we will focus on the contraposition between technical definitions of AI and common misconceptions about the nature and capabilities of AI systems. This will give us the opportunity to discuss the issue of AI-related risk, starting with (some) public perceptions of the potential hazards involved in the use of AI systems and contrasting them with research on these systems’ actual risks. We will then consider how AI systems often generate contexts of uncertainty and how they can be conceived as experimental technologies, insisting on the role of the “Trustworthy AI” approach as a way to reduce risk and uncertainty in AI. Finally, we will discuss the issues of anthropomorphism, manipulation, and deception in AI.
Lingua Insegnamento
INGLESE
Altre informazioni
Although not mandatory, attendance is highly recommended.
Corsi
Corsi
ARTIFICIAL INTELLIGENCE
Laurea
3 anni
No Results Found
Persone
Persone
Docente
No Results Found