BIG DATA AND AUTOMATIC LEARNING ALGORITHMS: KNOWLEDGE, INFORMATION, POWER
Stampa
Enrollment year
2019/2020
Academic year
2021/2022
Regulations
DM270
Academic discipline
SPS/08 (SOCIOLOGY OF CULTURE AND COMMUNICATION)
Department
DEPARTMENT OF POLITICAL AND SOCIAL SCIENCES
Course
COMMUNICATION, INNOVATION, MULTIMEDIA
Curriculum
PERCORSO COMUNE
Year of study
Period
1st semester (27/09/2021 - 10/12/2021)
ECTS
6
Lesson hours
36 lesson hours
Language
Italian
Activity type
ORAL TEST
Teacher
COSTA PAOLO (titolare) - 6 ECTS
Prerequisites
No special computing skills are required. Familiarity with Microsoft Excel or other programs that enable the user to tabulate and collate data can help. U
Inexperienced students are recommended to exploit online training opportunities (e.g. Coursera, Udemy, ...) or to take advantage of the free tutorials available on YouTube.
Some basic knowledge of statistics is also useful: attribute, distribution, arithmetic mean, mean square deviation, etc.
Learning outcomes
The course pursues two objectives:
1) provide students with the conceptual framework related to the economic and social models that are based on big data paradigm (i.e. large aggregations of data flowing in real time from multiple sources) and new artificial intelligence techniques (machine learning);
2) to encourage a reflection on the technical, socio-political, legal, cultural and ethical implication of that paradigm.
Course contents
The course is divided into three parts: an introductory part, an in-depth part, and a workshop.
The introductory part (5 lessons, 10 hours) allows to share the basic vocabulary required to understand the subject of teaching: difference between data, information and knowledge; concept of database and database management systems (DBMS); difference between relational and non-relational databases; elements of artificial intelligence history; learner algorithms; difference between machine learning and deep learning.
The in-depth part (5 lessons, 10 hours) explores the nature of the phenomenon and its historical roots, highlighting the factors that determine its pervasiveness: the explosion of big data, data-driven experiences, and spread of algorithmic logic in the main areas of economic and social life. In particular, four domains in which the big data paradigm is enabling the most significant changes are considered:
- Information and journalism
- Marketing and advertising
- Bioinformatics, medicine and pharmaceuticals
The workshop (5 encounters, 10 hours) is organized around the area of online information. Specific case studies will be analyzed and discussed with the students:
- the influence of large filters (Google and Facebook) in the formation of public opinion
- the technical basis of the so-called "fake news" and disinformation channels
- the evolution of technologies for the automatic news production
- the practice and tools for data journalism
Teaching methods
The course is structured with front-end lectures, including breaks for discussion and group activities that requires the students to familiarize with fact checking, data scraping and data visualization tools.
Reccomended or required readings
Hannah Fry, Hello World. Essere umani nell’era delle macchine, Torino, Bollati Boringhieri, 2019 (ed. originale Hello World. How to Be Human in the Age of the Machine, 2018).
Assessment methods
The exam will consist of a 15-20 minutes interview, aimed at verifying student's understanding of the subject.
The student can freely choose one of the following two methods of verification:
1) Interview on the contents of the essay by Hannah Fry (chapters on Crime and Art are optional, all other chapters are mandatory)
2) Presentation of personal research about one of the topics discussed during the workshop, supported by a multimedia deck (PowerPoint or similar).
Further information
Sustainable development goals - Agenda 2030