Reflections on AI for Communication

The course will cover – among others – the following topics:
• Introduction to Natural Language Processing (NLP) and Artificial Intelligence (AI)
• Ethical issues of AI and AI regulations 

The aim of this course is to make students critically reflect on the use of AI for communication purposes, to understand the many opportunities it brings, but also to review the attested negative effects, and to discuss possible positive and negative long-term impact on society.

In order for students to be able to critically reflect on the societal impact of AI for communication, the course will start with an introduction to NLP, including Machine Learning (ML) and Large Language Models (LLMs) using excerpts from a textbook on NLP (Jurafsky and Martin, 2025). The focus will be on text-based models, but we will also touch upon other modalities such as vision. These introductions will make students understand the machinery behind AI tools that are currently widely used, such as AI chatbots, machine translation, and content generation tools using generative AI. After these introductions, the main topics in AI ethics, such as bias, issues related to data, transparency, privacy as well as initiatives for AI regulation will be discussed. Especially, this latter part of the course requires active student involvement and critical reflection. Students give presentations and co-lead class discussions with help from the lecturer.

This course has three main aims: 

• To give students a basic understanding of how popular AI tools used for communication work
• To introduce common topics of AI ethics
• To make students critically reflect on and discuss about the impact of AI tools on society

• Salute e benessere
• Istruzione di qualità
• Uguaglianza di genere
• Energia pulita e accessibile
• Lavoro dignitoso e crescita economica
• Industria, innovazione e infrastrutture
• Ridurre le disuguaglianze
• Consumo e produzione responsabili

In presenza

Each session is composed of a presentation and an exercise and/or discussion part. While during the introductory first part, the lecturer will give presentations to introduce the topic of NLP and machine leaning and AI in general, the latter part is reserved for student presentations. Students will give a presentation and co-lead a discussion on a topic of their choice, possibly linked to their thesis topic in the latter part of the class. A list of selected papers will be distributed that students can choose from.

Students are expected to hand in a report, give a presentation, lead a discussion and actively take part in discussions led by the lecturer and other students.