Human-machine language communication 3200-L2-NS-Hum

Human–Machine Communication (HMC) is an interdisciplinary course that examines how people interact with, interpret, and co-construct meaning with intelligent technologies, including conversational agents, robots, recommender systems, and large language models. The course integrates perspectives from communication studies, sociolinguistics, human–computer interaction, media studies, and AI ethics.
Students explore theoretical frameworks for understanding communication with nonhuman agents—such as mediation theory, symbolic interactionism, social presence theory, and communication accommodation theory—while also analyzing how machines generate language, adapt to users, and shape social behavior. A central theme is how cultural context, identity, and social norms influence (and are influenced by) machine communication practices.

Prerequisites (description)

This course is designed for undergraduate and graduate students whose first language of specialization is English. The curriculum requires a significant amount of student effort, so strong motivation is essential. The course consists of dedicated thematic modules and includes a presentation of key concepts in the field of English sociolinguistics.

Course coordinators

Olena Petrashchuk

Type of course

elective courses

Mode

Classroom

Learning outcomes

After completing the course, the student:
Knowledge:
- Knows the structure of language as a system, has basic knowledge of the place and importance of linguistics (general and applied) and literary studies within the scientific system, and understands their specific subject matter.
- Possesses structured knowledge of language and linguistic communication in various social contexts, including artificial intelligence.
- Knows and understands the connections between the given field and related philological and humanistic fields.
- Knows and understands the connections between applied linguistics and literary studies and other fields and disciplines.
K1_W06; K1_W01
Skills:
- is able to use basic theoretical approaches and paradigms appropriate for the research field;
- is able to work according to the goals and guidelines formulated by the academic supervisor;
- is able to use research tools appropriately;
Social Competencies:
- is aware of the differences in social contexts existing between communicators including AI communicator;
- understands and appreciates the importance of contexts and social elements for communication including social and cultural norms in human-machine communication;
- participates in cultural and social life (K_K06, S_K06).

Assessment criteria

1. The final grade consists of the following components:
Attendance - 30%
Activity during attendance - 15%
Term paper - 15%
Graded credit - 40%
2. Final grade percentage:
55%-69% = 3
70%-74% = 3+
75%-84% = 4
85%-89% = 4+
90%-100% = 5

Bibliography

-Guzman, A. L. (Ed.) (2018). Human–Machine Communication: Rethinking Communication, Technology, and Ourselves.
-Guzman, A. L., & Lewis, S. C. (2020). The Psychology of Human–Machine Communication.
-Hancock, P. A. et al. (2020). Human–Robot Interaction.
-Bucholtz, M., & Hall, K. (2005). “Identity and Interaction in Sociolinguistics.”
-Agha, A. (2007). Language and Social Relations.
-Bender, E., & Koller, A. (2020). “Climbing towards NLU: On Meaning, Form, and Understanding in NLP.”
-Crawford, K. (2021). Atlas of AI.
-Coeckelbergh, M. (2021). AI Ethics.
-Shneiderman, B. (2022). Human-Centered AI.
-Wang, Y., & Mark, G. (2021). Studies on AI-mediated communication and cultural norms.
-Neff, G. & Nagy, P. (2016). “Talking to Bots: Symbiotic Agency.”

Additional information

Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system:

Description of 3200-L2-NS-Hum in USOSweb