Objectives
Demonstrate familiarity with the various assumptions and ideas behind the origins and the developments of artificial intelligence (AI)
Be able to discuss the epistemological problems implied in the AI techniques, especially those relative to learning on large training sets.
Understand the ethical and socio-political obstacles involved in designing AI systems.
Be prepared to interrogate novel claims about intelligence, intelligent behaviors of technical systems and promises of short- and medium-term developments.
Engage and have fun in lively discussion on the contemporary debate on AI, employing critical thinking and strong argumentative skills.
Demonstrate familiarity with the various assumptions and ideas behind the origins and the developments of artificial intelligence (AI)
Be able to discuss the epistemological problems implied in the AI techniques, especially those relative to learning on large training sets.
Understand the ethical and socio-political obstacles involved in designing AI systems.
Be prepared to interrogate novel claims about intelligence, intelligent behaviors of technical systems and promises of short- and medium-term developments.
Engage and have fun in lively discussion on the contemporary debate on AI, employing critical thinking and strong argumentative skills.
teacher profile teaching materials
The success of next-generation artificial intelligence (from the 2010s onwards) is based, among other things, on the vast availability of data. The advent of platforms has made it possible to obtain large amounts of personal data to organize in order to guide the representation of people's lives and behaviors, making it possible to predict their future preferences for future decisions. This course aims to analyze the tools for sharing information online to highlight the risks and opportunities.
The revolution in communication technologies is going through a phase of great transformations, where the partially open spaces of the early days have been replaced by private walled gardens. In these, users are welcomed and simultaneously retained. The activity of data mining, currently known as Big Data, i.e., the extraction of valuable information from what is directly or indirectly made available by users, has now become one of the central elements of network organization. This poses significant issues regarding privacy, as well as the model of knowledge that is activated in decision-making, which is not limited to marketing alone.
Big Data and algorithms build correlations, regularities, and quantifications to propose interpretations of social phenomena based on mathematical automatisms. However, the course will reveal that it is an illusion to think that an automatic understanding of habits and events can be objective and neutral. Artificial intelligence technologies aim to define what has been and anticipate what will be, but they were invented and developed by human beings and retain their genius, instability, biases, and often even arrogance. Moreover, the predictions rely on the assumption that the past is a good anticipation of the future.
Recent developments in artificial intelligence applied to human activities have three areas of intervention:
1. Automatic decision-making in uncertain contexts related to people's lives.
2. Image recognition capabilities, particularly regarding people's faces, and also the emotional expressiveness that may seem to derive from it.
3. The production of artificial content involving new techniques of generative, foundational, and multimodal artificial intelligence.
These developments present us with new challenges that society must address from a primarily political perspective. We need to decide how we want to coexist with these tools and how we want to imagine the hybrid future that these devices entail.
The course aims to identify the strategic issues in these areas and undertake a work of information literacy and cultural critique of the intelligence model proposed by the AI sector.
The course also focuses on the basic elements of information, AI, and media literacy to understand what is at stake in terms of freedom and control regarding the use of digital platforms for all types of activities, including those based on data interpretation within the realm of artificial intelligence.
Crawford K (2021) ATlas of AI. Power, Politics and the planetary cost of artificial intelligence, Yale University Press, New Haven and London.
Programme
Digital platform, data extraction and Artificial Intelligence: a critical viewThe success of next-generation artificial intelligence (from the 2010s onwards) is based, among other things, on the vast availability of data. The advent of platforms has made it possible to obtain large amounts of personal data to organize in order to guide the representation of people's lives and behaviors, making it possible to predict their future preferences for future decisions. This course aims to analyze the tools for sharing information online to highlight the risks and opportunities.
The revolution in communication technologies is going through a phase of great transformations, where the partially open spaces of the early days have been replaced by private walled gardens. In these, users are welcomed and simultaneously retained. The activity of data mining, currently known as Big Data, i.e., the extraction of valuable information from what is directly or indirectly made available by users, has now become one of the central elements of network organization. This poses significant issues regarding privacy, as well as the model of knowledge that is activated in decision-making, which is not limited to marketing alone.
Big Data and algorithms build correlations, regularities, and quantifications to propose interpretations of social phenomena based on mathematical automatisms. However, the course will reveal that it is an illusion to think that an automatic understanding of habits and events can be objective and neutral. Artificial intelligence technologies aim to define what has been and anticipate what will be, but they were invented and developed by human beings and retain their genius, instability, biases, and often even arrogance. Moreover, the predictions rely on the assumption that the past is a good anticipation of the future.
Recent developments in artificial intelligence applied to human activities have three areas of intervention:
1. Automatic decision-making in uncertain contexts related to people's lives.
2. Image recognition capabilities, particularly regarding people's faces, and also the emotional expressiveness that may seem to derive from it.
3. The production of artificial content involving new techniques of generative, foundational, and multimodal artificial intelligence.
These developments present us with new challenges that society must address from a primarily political perspective. We need to decide how we want to coexist with these tools and how we want to imagine the hybrid future that these devices entail.
The course aims to identify the strategic issues in these areas and undertake a work of information literacy and cultural critique of the intelligence model proposed by the AI sector.
The course also focuses on the basic elements of information, AI, and media literacy to understand what is at stake in terms of freedom and control regarding the use of digital platforms for all types of activities, including those based on data interpretation within the realm of artificial intelligence.
Core Documentation
Numerico T. (2021) Big Data e algoritmi, Carocci, Roma.Crawford K (2021) ATlas of AI. Power, Politics and the planetary cost of artificial intelligence, Yale University Press, New Haven and London.
Type of delivery of the course
The lectures are in presence at the university.Attendance
in-person lectures are not mandatory frequency is facultativeType of evaluation
For students attending the course it is possible to access a pre-test reserved for students who attend lectures. For students not attending the course there is a written exam whose aim is the evaluation of the knowledge of texts included in the program