Principles of social psychology for ai design
A.A. 2023/2024
Obiettivi formativi
This course aims to provide the students with a perspective on the interdisciplinary nature of AI design and its social implications. It will equip the students with the knowledge and skills to contribute to the development of AI systems that are ethically sound, user-friendly, and aligned with human needs.
Knowledge and understanding
· Gaining an understanding of key theories and concepts in social psychology and how they relate to AI design
· Exploring the impact of AI on human behavior and interactions at an interpersonal, intragroup and intergroup level
· Examining the role of social influence, group dynamics, and user experience in AI design
· Investigating socio-cognitive processes likely to affect person-AI interaction and use
· Analyzing ethical considerations and potential biases in AI algorithms and decision-making
Applying knowledge and understanding
· Developing critical thinking skills to evaluate and improve the social implications of AI systems
· Applying social psychological principles to design AI systems that enhance user experiences at an individual and group level
· Applying social psychological principles to design AI systems that promote ethical practices and reduce social biases
· Understanding and application of best practices
Knowledge and understanding
· Gaining an understanding of key theories and concepts in social psychology and how they relate to AI design
· Exploring the impact of AI on human behavior and interactions at an interpersonal, intragroup and intergroup level
· Examining the role of social influence, group dynamics, and user experience in AI design
· Investigating socio-cognitive processes likely to affect person-AI interaction and use
· Analyzing ethical considerations and potential biases in AI algorithms and decision-making
Applying knowledge and understanding
· Developing critical thinking skills to evaluate and improve the social implications of AI systems
· Applying social psychological principles to design AI systems that enhance user experiences at an individual and group level
· Applying social psychological principles to design AI systems that promote ethical practices and reduce social biases
· Understanding and application of best practices
Risultati apprendimento attesi
At the end of the course, the students are expected to have achieved the following learning objectives:
· Understand the principles and theories of social psychology and their relevance to AI design
· Analyze the impact of AI systems on social behavior, attitudes, and decision-making processes
· Identify and evaluate potential ethical considerations and social implications of AI design in various contexts
· Apply social psychological concepts to improve AI design
· Explore the role of perception, cognition, and social influence in shaping user interactions with AI technologies
· Investigate the influence of biases, stereotypes, and prejudices on AI algorithms and their potential impact on marginalized groups; vice versa, apply social psychological principles to design AI systems that promote inclusivity, diversity, and fairness
· Examine the psychological effects of human-computer interaction and the design principles that can enhance users' trust and satisfaction
· Understand the normative and social psychological factors that influence user acceptance and adoption of AI technologies
· Analyze the role of emotions, empathy, and social connections in AI design and its impact on user engagement
· Collaborate effectively in teams to design and present AI systems that incorporate social psychological principles
· Develop critical thinking skills to promote ethical use of AI systems in society, taking into account the perspectives of different stakeholders
· Understand the principles and theories of social psychology and their relevance to AI design
· Analyze the impact of AI systems on social behavior, attitudes, and decision-making processes
· Identify and evaluate potential ethical considerations and social implications of AI design in various contexts
· Apply social psychological concepts to improve AI design
· Explore the role of perception, cognition, and social influence in shaping user interactions with AI technologies
· Investigate the influence of biases, stereotypes, and prejudices on AI algorithms and their potential impact on marginalized groups; vice versa, apply social psychological principles to design AI systems that promote inclusivity, diversity, and fairness
· Examine the psychological effects of human-computer interaction and the design principles that can enhance users' trust and satisfaction
· Understand the normative and social psychological factors that influence user acceptance and adoption of AI technologies
· Analyze the role of emotions, empathy, and social connections in AI design and its impact on user engagement
· Collaborate effectively in teams to design and present AI systems that incorporate social psychological principles
· Develop critical thinking skills to promote ethical use of AI systems in society, taking into account the perspectives of different stakeholders
Periodo: Secondo semestre
Modalità di valutazione: Esame
Giudizio di valutazione: voto verbalizzato in trentesimi
Corso singolo
Questo insegnamento può essere seguito come corso singolo.
Programma e organizzazione didattica
Edizione unica
Periodo
Secondo semestre
Programma
As AI continues to play an increasingly significant role in our lives, it is crucial to understand, on one side, how our social life might be affected by AI and, on the other, how social-psychological processes might forge our interaction with AI systems.
Hence, the course aims to provide an overview of the current and up-to-date research in social psychology on person-AI interaction and Human-Centered Artificial Intelligence.
More specifically, the course will present the principles of social cognition and social psychology that can shape AI systems' design, development, and implementation. The students will have the opportunity to analyze fundamentals of social psychology at the individual (e.g., impression formation processes), intragroup (e.g., intragroup cooperation processes, negotiation, trust) and intergroup level (e.g., reduction of bias against outgroups and minority groups, the definition of non-prejudicial and/or discriminatory responses) to improve the AI design and the user-AI interactions.
Moreover, the course will focus on the social psychological processes (cognitive, affective and motivational) that might be elicited by AI and are likely to forge the user's experience. Such processes range, for example, from anthropomorphization of a non-human agent, to backlash effects on Self-perception (e.g., self-objectification) and the perception and interaction with other human beings.
The analysis and understanding of these mechanisms are essential not only to refine the design of AI systems and improve person-AI interactions but also to use AI to promote positive social changes and collective well-being.
Hence, the course aims to provide an overview of the current and up-to-date research in social psychology on person-AI interaction and Human-Centered Artificial Intelligence.
More specifically, the course will present the principles of social cognition and social psychology that can shape AI systems' design, development, and implementation. The students will have the opportunity to analyze fundamentals of social psychology at the individual (e.g., impression formation processes), intragroup (e.g., intragroup cooperation processes, negotiation, trust) and intergroup level (e.g., reduction of bias against outgroups and minority groups, the definition of non-prejudicial and/or discriminatory responses) to improve the AI design and the user-AI interactions.
Moreover, the course will focus on the social psychological processes (cognitive, affective and motivational) that might be elicited by AI and are likely to forge the user's experience. Such processes range, for example, from anthropomorphization of a non-human agent, to backlash effects on Self-perception (e.g., self-objectification) and the perception and interaction with other human beings.
The analysis and understanding of these mechanisms are essential not only to refine the design of AI systems and improve person-AI interactions but also to use AI to promote positive social changes and collective well-being.
Prerequisiti
There are no formal prerequisites for this course. However, a basic understanding of psychology and familiarity with AI concepts would be beneficial.
Metodi didattici
The course will employ a combination of lectures, interactive discussions, case studies, group activities. You will have the opportunity to engage with cutting-edge research articles and real-world examples to deepen your understanding of the course material.
Materiale di riferimento
Slides and peer-reviewed articles provided during the course and in the e-learning Platform.
Modalità di verifica dell’apprendimento e criteri di valutazione
The assessment will take place through the final exam, which verifies the acquisition of principles of social psychology useful for the design, development, and deployment of AI systems. A written exam will take place, with multiple responses and open questions (expected exam duration 1 hour). The exam is considered passed with a minimum score of 18 out of 30 points.
M-PSI/05 - PSICOLOGIA SOCIALE - CFU: 6
Lezioni: 48 ore
Docente:
Vergallito Alessandra
Siti didattici