Value and Impact of EMAI (Basic)

Name of Module:

Value and Impact of EMAI (Basic)

Credit Points (ECTS):

Module-ID:

Person Responsible for module (Name, Mail address):

Alvaro Pina Stranger : alvaro.pina-stranger@univ-rennes.fr

University: Université de Rennes

Department: ISTIC

1. Short description of the module

This course explores the emergence of Emotional Artificial Intelligence (EAI) as both a technological innovation and a societal phenomenon. Students will examine how conversational agents and affective computing simulate empathy, companionship, and social presence, shaping new relational norms in everyday life, education, healthcare, and professional contexts. Through the study of media narratives and real-world applications, the module highlights how emotional AI is framed as a promise of enhanced efficiency, personalization, and accessibility, while also becoming increasingly embedded in organizational practices and cultural habits.

At the same time, the course engages with the risks and vulnerabilities revealed by these technologies. Issues such as dependency, illusion of authentic connection, exploitation of sensitive emotional data, and manipulation of attention are critically assessed. Particular attention is given to the ambivalence of emotional AI as both a potential tool for support and a possible source of psychological or social harm, especially for vulnerable groups such as children, adolescents, or isolated individuals. These ambiguities are further situated within broader transformations of social norms, identity, and human autonomy in the digital age.

Finally, the course places emphasis on the ethical, economic, and regulatory tensions surrounding emotional AI. Students will investigate controversies on authenticity versus simulation, humanization versus dehumanization, and freedom versus affective influence. Case studies will shed light on the strategies of industrial actors, the responses of regulators, and the role of mediators such as educators, therapists, and journalists. By the end of the module, students will be equipped to critically analyze the promises and perils of emotional AI, and to reflect on the forms of governance, education, and ethical safeguards needed to channel its development responsibly.

2. Target audience

The module is primarily intended for master’s students in computer science, who generally have limited background in economics, sociology, or management sciences. It is therefore designed to provide them with a transdisciplinary perspective on their own practices, situating the technical development of Emotional AI within its broader social, ethical, and cultural implications. The course invites students to critically examine how affective technologies shape human–machine interactions, influence individual behaviors, and transform organizational dynamics. At the same time, the module is open to professionals who wish to broaden their understanding of Emotional AI. By combining insights from computer science, social sciences, and ethics, it enables participants to engage with the promises and risks of these technologies, and to anticipate the challenges of designing, deploying, and regulating emotionally responsive systems responsibly.

3. The self-standing module is included in the following course/s of the Master’s program (If not, add the text “N/A”)

N/A

4. Prerequisites for Participation (If not, add the text “N/A”)

N/A

5. The self-standing module belongs to the following Learning path/s  (If not, add the text “N/A”)

N/A

6. Intended Learning Outcomes

7. Teaching and Learning Methods

The course is structured around 10 lessons, each focusing on a key aspect of Emotional AI and its impact. Every lesson includes a video lecture, a PDF resource pack with excerpts from scholarly works, and a brief bibliography for further reading.

To support learning, each lesson also provides an individual exercise for self-assessment, helping students consolidate their knowledge and prepare for the final evaluation. This format ensures a progressive and transdisciplinary exploration of Emotional AI, accessible to both computer science students and professionals.

8. Structure (content, lessons, etc.)

9. Schedule (course agenda and dates, including synchronous and asynchronous sessions)

Total 25 hours (1 ECTS) / 50 hours (2 ECTS)

Number of hours in ASYNC delivery: X

Number of hours in SYNC delivery: X

11. Assessment and Grading Procedures (describe the passing Threshold used)

Assessment for this course will be based on participation in a variety of quizzes and completion of self-study modules. The final result will be recorded as Pass or Fail, depending on the number and quality of quiz attempts.

12. Description about how can successfully complete the module to obtain the certificate (needs to be done in your self-standing module to obtain the certificate)

Completion of all sessions and quizzes to obtain the certificate.