07158 - Artificial Intelligence

Learning outcomes

At the end of the course, students:

• know the historical development and applications of artificial intelligence, defined both as the artificial simulation of the mind (emotions and cognitive processes) and of behavior (actions and decisions);

• know the most important differences differences, in terms of structure and potential applications, between artificial systems (e.g. classical connectionist algorithms, deep convolutional networks, role of expectations and prediction error);

• know the main aspects, for instance in terms of potential applications and of reception problems, linked to the introduction of artificial systems in real contexts (eg chatbots, self-driving cars, cognitive ergonomics);

• are able to link psychological concepts learned in the course of study, with their use in artificial systems aimed at detecting (e.g. affective computing, brain computer interfaces) or simulating (machine learning) mental states or human behavior.

Course contents

The course is aimed at psychology students and does not require previous knowledge in informatics or engineering. Contents include:

- Main steps in the history of artificial intelligence, from the first attempts to build "thinking machines" at the beginning of the 20th century, to the birth and subsequent contrasts between symbolic and non-symbolic AI, tracing their development from the 1950s to today.

- Description of the main approaches to artificial systems in the field of AI (e.g., symbolic, connectionist, deep learning approach) and of robotics (e.g., the distinction between internal and external emotional robotics, the concept of embodiment).

- Application of the described algorithms to different psychological functions (eg: natural language understanding, artificial vision, prediction of agents' behavior).

- Social interaction between artificial and human beings. Distinction between artificial beings with a physical presence (robot) and virtual assistants (e.g., chatbots).

- Applications of AI to the psychological field (eg, detection of psychological states from textual and/or physiological data). Main results and design and ethical implications of this area.

Readings/Bibliography

• Slides of the lessons
• Margaret A. Boden, L'intelligenza Artificiale, Il Mulino
• Paul Dumouchel, Luisa Damiano, Vivere con i robot, Raffaello Cortina Editore
• Articles and chapters indicated by the teacher during the course.

Teaching methods

Frontal lessons.

Assessment methods

The exam consists of 4 open questions. Time available: 60 minutes. The program includes all the bibliographic material indicated in the texts section, including any topic which was not discussed during the classes.

Each response has a score of up to 8 points. The sum of all scores will be rounded to the nearest integer. “Lode” for tests with a minimum of 7,5 points in all questions.

Compensatory or dispensatory aids will be used, in the manner agreed with the teacher, for students diagnosed with SLD or other disability officially recognized and declared at the Service for students with disabilities and SLD of the University of Bologna.

Registration is required to take the exam through the function present on the AlmaEsami website, in compliance with the established deadlines.

Teaching tools

powerpoint presentations and IA examples on the web

Office hours

See the website of Andrea De Cesarei