Ateneo - UPO

The course is divided into two parts. The first part introduces the tools for identifying and presenting sound arguments. It will therefore teach students how to identify the structure of arguments, how to distinguish between different types of arguments (deductive, non-deductive, abductive, etc.), how to assess the soundness of arguments using established normative standards, and how to develop effective argumentative strategies. Considerable attention will be given to the study of fallacies and cognitive biases. The second part, which takes a more seminar-based approach, will explore some applications of artificial intelligence in the fields of argumentation and decision-making, and will provide the building blocks for an initial critical analysis of the most widely used AI-based tools. It will comprise both a theoretical component and practical exercises.

Canale, D., Ciuni, R:, Frigerio, A., Tuzet, G. “Critical thinking: un’introduzione”. Egea, Milano 2021. (english edition is also accepted: "Critical thinking: an introduction", Bocconi University Press 2022). Selected chapters.Santosuosso, A., Sartor, G. Decidere con l'IA. Intelligenze artificiali e naturali nel diritto. Bologna, Il Mulino 2024 (selected chapters).Slides posted on DIR.

The course acts as a kind of 'toolbox' for improving argumentation skills and mastering different styles of reasoning. It aims to refine students' ability to justify a thesis adequately, refute others' theses, identify errors in reasoning and judge alternative theses by critically evaluating the reasons given in support, in both everyday and scientific discourse. The course therefore provides fundamental cultural and scientific methodologies and competencies for developing logical, argumentative and critical reconstruction skills. It also provides techniques for constructing arguments and responding rationally to different types of argument. Finally, the course explores recently developed dialogue systems in artificial intelligence, using what has been learnt in the first part to evaluate their argumentative strengths and weaknesses.

Interest in reasoning and communication; curiosity about generative artificial intelligence.

Lectures, also with the use of audiovisuals; case discussions, work in classroom; structured debates.

Students are invited to follow the updates of the course page published on DIR for supplementary readings as well as for the detailed program of the course. Students with physical disabilities, Learning Disabilities or Special Education Needs can request specific services and tools via the Staff Sviluppo e Coordinamento Carriere e Servizi alle Studentesse e agli Studenti, consulting the University webpage: https://www.uniupo.it/en/services/servicesstudents-physical-or-learning-disabilities Students with disabilities, learning disabilities or special education needs, once they have contacted the University Staff, can refer to the tutor in charge of the course to define the examination modalities, concerning academic aspects.

The examination is oral and consists of five or six questions designed to assess students’ understanding of the topics covered and their ability to critically evaluate arguments and communicative exchanges. To pass, students must answer the majority of the questions correctly. To achieve a high mark, students are required to provide detailed, correct answers to all questions, incorporating their own personal reflections.

Part I. What is an argument? Argumentation and reasoning. The structure of an argument. Deductive and non-deductive arguments. Evaluating arguments. Rational discussion. Fallacies and biases. Strategies for rebuttal. Integrating gender issues: elements of pragmatics. Deductive arguments: an introduction to deductive logic. Counterfactual conditionals. Evaluating evidence: inductive reasoning. Causal and explanatory reasoning. Reasoning by analogy
Part II. From expert systems to LLMs. Data and algorithms. ‘Prediction’ in AI. Explainability. Argumentation systems: risks and opportunities.

The course will enable you to: identify the structure of an inductive or deductive argument; determine the conditions under which a specific deductive argument is valid, sound and/or persuasive, and an inductive argument is plausible and persuasive; recognise the most common fallacies and avoid committing them; initiate rational strategies for counter-argumentation; assess the robustness of causal and abductive inferences; evaluate the strength of arguments based on analogy; recognise the most common statistical and probabilistic errors; reason about the validity of a counterfactual argument; acquire the tools to critically navigate AI systems for argumentation and decision-making and begin to critically evaluate their output.