Lab.: Advanced Digital Methods
A.Y. 2024/2025
Learning objectives
The laboratory will introduce the theoretical and practical skills for auditing and analysing social media algorithms and generative artificial intelligence outputs. The focus will be on the socio-cultural biases embedded within algorithmic systems recommending content on the one hand, and on the other, on content created by generative AI models and chatbots
Expected learning outcomes
At the end of the laboratory students will be able to:
- conduct a comparative analysis of a recommender algorithm or generative AI output
- identify the limits and strengths of a variety of qualitative and computational approaches for doing so
- conduct a comparative analysis of a recommender algorithm or generative AI output
- identify the limits and strengths of a variety of qualitative and computational approaches for doing so
Lesson period: First trimester
Assessment methods: Giudizio di approvazione
Assessment result: superato/non superato
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
First trimester
Course syllabus
The lab introduces the theoretical and practical skills for the audit and analysis of social media algorithms and generative artificial intelligence from a sociocultural perspective. Building upon the digital methods paradigm, students will be introduced to qualitative, quantitative, and computational methods for the study of the outputs of social media algorithmic feeds (e.g.: TikTok, Instagram) and textual and visual generative AI models (e.g.: ChatGPT, Gemini, Midjourney).
Concerning theory, the focus will be on different approaches to account for the sociotechnical dimensions of AI and algorithms. More specifically, the lab will consider: the political economy of AI, platforms, and social media, including data extraction; the functioning of algorithmic media and generative artificial intelligence models; the impact of AI and algorithms on culture and sociality within digital environments. At a practical level, students will learn the main techniques to collect, manipulate, and analyse data from a variety of AI models and social media, with a focus on Python; the methods considered include content analysis, text analysis, visual analysis, and the principles of algorithm auditing.
Lectures and hands-on classes will guide students towards a final project to be written and presented in class. Students are expected to bring their own laptops: the necessary software and tools will be introduced during the first week of class.
Concerning theory, the focus will be on different approaches to account for the sociotechnical dimensions of AI and algorithms. More specifically, the lab will consider: the political economy of AI, platforms, and social media, including data extraction; the functioning of algorithmic media and generative artificial intelligence models; the impact of AI and algorithms on culture and sociality within digital environments. At a practical level, students will learn the main techniques to collect, manipulate, and analyse data from a variety of AI models and social media, with a focus on Python; the methods considered include content analysis, text analysis, visual analysis, and the principles of algorithm auditing.
Lectures and hands-on classes will guide students towards a final project to be written and presented in class. Students are expected to bring their own laptops: the necessary software and tools will be introduced during the first week of class.
Prerequisites for admission
Students are expected to bring their own laptops: the necessary software and tools will be introduced during the first week of class.
Teaching methods
Lectures, hands-on classes, discussion
Teaching Resources
Readings will be suggested during class
Assessment methods and Criteria
A final project to be written and presented in class based on the content of the laboratory.
SPS/08 - SOCIOLOGY OF CULTURE AND COMMUNICATION - University credits: 3
Laboratories: 20 hours
Professor:
Rama Ilir
Professor(s)