Week
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Topic
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Content and Reading Assignment
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Teaching Activities and Homework
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1
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Introduction and course overview
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2
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What is Human-Robot Interaction and Human-AI Interaction?
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Nass, C., & Moon, Y. (2000). Machines and mindlessness: Social responses to computers. Journal of social issues, 56(1), 81-103.
Amershi, S., Weld, D., Vorvoreanu, M., Fourney, A., Nushi, B., Collisson, P., ... & Horvitz, E. (2019, May). Guidelines for human-AI interaction. In Proceedings of the 2019 chi conference on human factors in computing systems (pp. 1-13).
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Team Formation
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3
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Social Robots
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Forlizzi, J., & DiSalvo, C. (2006, March). Service robots in the domestic environment: a study of the roomba vacuum in the home. In Proceedings of the 1st ACM SIGCHI/SIGART conference on Human-robot interaction (pp. 258-265).
Breazeal, C., Dautenhahn, K., & Kanda, T. (2016). Social robotics. Springer handbook of robotics, 1935-1972.
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4
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Anthropomorphism
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Epley, N., Waytz, A., & Cacioppo, J. T. (2007). On seeing human: a three-factor theory of anthropomorphism. Psychological review, 114(4), 864.
Fink, J. (2012). Anthropomorphism and human likeness in the design of robots and human-robot interaction. In Social Robotics: 4th International Conference, ICSR 2012, Chengdu, China, October 29-31, 2012. Proceedings 4 (pp. 199-208). Springer Berlin Heidelberg.
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5
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Embodiment and Nonverbal Communication
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Mutlu, B., Shiwa, T., Kanda, T., Ishiguro, H., & Hagita, N. (2009, March). Footing in human-robot conversations: how robots might shape participant roles using gaze cues. In Proceedings of the 4th ACM/IEEE international conference on Human robot interaction (pp. 61-68).
Jung, M. F., Lee, J. J., DePalma, N., Adalgeirsson, S. O., Hinds, P. J., & Breazeal, C. (2013, February). Engaging robots: easing complex human-robot teamwork using backchanneling. In Proceedings of the 2013 conference on Computer supported cooperative work (pp. 1555-1566).
Mok, B. K. J., Yang, S., Sirkin, D., & Ju, W. (2015, August). A place for every tool and every tool in its place: Performing collaborative tasks with interactive robotic drawers. In 2015 24th IEEE international symposium on robot and human interactive communication (RO-MAN) (pp. 700-706). IEEE.
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6
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Chatbot and Verbal Communication
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Luger, E., & Sellen, A. (2016, May). " Like Having a Really Bad PA" The Gulf between User Expectation and Experience of Conversational Agents. In Proceedings of the 2016 CHI conference on human factors in computing systems (pp. 5286-5297).
Liao, Q. V., Mas-ud Hussain, M., Chandar, P., Davis, M., Khazaeni, Y., Crasso, M. P., ... & Geyer, W. (2018, April). All work and no play?. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (pp. 1-13).
Torrey, C., Fussell, S. R., & Kiesler, S. (2013, March). How a robot should give advice. In 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI) (pp. 275-282). IEEE.
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Team Projects:
Idea Pitch
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7
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Spring Break
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8
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Designing AI user experiences
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Yang, Q., Steinfeld, A., Rosé, C., & Zimmerman, J. (2020, April). Re-examining whether, why, and how human-AI interaction is uniquely difficult to design. In Proceedings of the 2020 chi conference on human factors in computing systems (pp. 1-13).
Yang, Q., Steinfeld, A., & Zimmerman, J. (2019, May). Unremarkable AI: Fitting intelligent decision support into critical, clinical decision-making processes. In Proceedings of the 2019 CHI conference on human factors in computing systems (pp. 1-11).
Kay, M., Kola, T., Hullman, J. R., & Munson, S. A. (2016, May). When (ish) is my bus? user-centered visualizations of uncertainty in everyday, mobile predictive systems. In Proceedings of the 2016 chi conference on human factors in computing systems (pp. 5092-5103).
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9
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Transparent and explainable AI
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Wang, D., Yang, Q., Abdul, A., & Lim, B. Y. (2019, May). Designing theory-driven user-centric explainable AI. In Proceedings of the 2019 CHI conference on human factors in computing systems (pp. 1-15).
Shneiderman, B. (2020). Human-centered artificial intelligence: Reliable, safe & trustworthy. International Journal of Human–Computer Interaction, 36(6), 495-504.
(Optional) Ehsan, U., Passi, S., Liao, Q. V., Chan, L., Lee, I. H., Muller, M., & Riedl, M. O. (2024, May). The Who in XAI: How AI Background Shapes Perceptions of AI Explanations. In Proceedings of the CHI Conference on Human Factors in Computing Systems (pp. 1-32).
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10
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Team Projects:
Midterm Research Proposal Presentation
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Presentation
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11
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Team Projects:
In-Class
Discussion
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12
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Collaboration, Teamwork, and Work settings
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Hinds, P. J., Roberts, T. L., & Jones, H. (2004). Whose job is it anyway? A study of human-robot interaction in a collaborative task. Human–Computer Interaction, 19(1-2), 151-181.
Jung, M. F., Martelaro, N., & Hinds, P. J. (2015, March). Using robots to moderate team conflict: the case of repairing violations. In Proceedings of the tenth annual ACM/IEEE international conference on human-robot interaction (pp. 229-236).
Fraune, M. R., Šabanović, S., & Smith, E. R. (2017, August). Teammates first: Favoring ingroup robots over outgroup humans. In 2017 26th IEEE international symposium on robot and human interactive communication (RO-MAN) (pp. 1432-1437). IEEE.
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13
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Team Projects:
In-Class
Data Collection
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14
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Emotion
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Boehner, K., DePaula, R., Dourish, P., & Sengers, P. (2007). How emotion is made and measured. International Journal of Human-Computer Studies, 65(4), 275-291.
Breazeal, C., & Brooks, R. (2005). Robot emotion: A functional perspective. Who needs emotions, 271-310.
Lee, M. K., Kiesler, S., Forlizzi, J., & Rybski, P. (2012, May). Ripple effects of an embedded social agent: a field study of a social robot in the workplace. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 695-704).
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15
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Fairness, Trust, and Ethics
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Malle, B. F., Scheutz, M., Arnold, T., Voiklis, J., & Cusimano, C. (2015, March). Sacrifice one for the good of many? People apply different moral norms to human and robot agents. In Proceedings of the tenth annual ACM/IEEE international conference on human-robot interaction (pp. 117-124).
Claure, H., Kim, S., Kizilcec, R. F., & Jung, M. (2023). The social consequences of machine allocation behavior: Fairness, interpersonal perceptions and performance. Computers in human behavior, 146, 107628.
Hou, Y. T. Y., & Jung, M. F. (2021). Who is the expert? Reconciling algorithm aversion and algorithm appreciation in AI-supported decision making. Proceedings of the ACM on Human-Computer Interaction, 5(CSCW2), 1-25.
Hou, Y. T. Y., Lee, W. Y., & Jung, M. (2023, April). “Should I Follow the Human, or Follow the Robot?”—Robots in Power Can Have More Influence Than Humans on Decision-Making. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (pp. 1-13).
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16
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Team Projects: Final Poster Session
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Poster Session
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17
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Flexible week
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18
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Flexible week
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Team Projects:
Final Report
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* This syllabus is developed with reference to Professor Malte Jung's courses at Cornell University (USA): Robots, Teamwork, Emotion.
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The total score of 100 points will be the accumulation of these activities:
- Leading a class (20%): Each student will lead one class over the course of the semester. (Students may form a team to co-lead. I will decide the size of the teams in the first week.) The class lead(s) will be responsible for the assigned readings and, if preferred, selecting 1-2 additional articles for students to read that apply concepts from that week’s readings to current work in Human-AI Interaction (HAII), Human-Robot Interaction (HRI), Computer-mediated communication (CMC), human-computer interaction (HCI), or a related area. Readings must be assigned to the rest of the class a week in advance. During the class session, the student(s) will be the class lead(s) to lead the discussion. The class lead(s) are encouraged to include multiple activities and up-to-date examples (such as short videos, memes, recent popular SNS posts, other student’s online discussion) to facilitate the discussion.
- Online Discussion (15%): Each week (except for Week 1, team project presentation, team project data collection, and final poster sessions), students are expected to post comments on the topic in the online forum set up for that week.
Each post should include (a) a short description of one surprising or interesting point from the readings assigned for that week, something you did not know before or had not thought deeply about; and (b) some implications of this interesting point for your own research or experience. Posts should be about 150-300 words and must be completed by 6 PM one day before the class to receive credit.
Students should also comment on two other student's posts by 10 PM one day before the class to receive full credit.
Each student is allowed to miss two weeks without any need for explanation, but no late submission will be accepted. If a student misses more than two assignments, no excuses will be accepted for the additional misses.
- Team Research Projects (55%): Students will work in teams to conduct a research project on an HRI or HAII topic. This project can be design-oriented, theoretical analysis, or related to human’s behavior related to intelligent agents.
Students are expected to work on:
- Idea Pitch (5%): Students will prepare 2-3 research topics, why they find these topics interesting and important, supported by key previous studies (at least 2 for each topic). This written report should be 2-3 pages, double spaced, excluding tables and figures.
- Midterm Research Proposal Presentation (15%): Students will present (1) one chosen research topic, (2) a refined introduction of research motivation supported by a brief literature review (with clear definitions of the main concepts, and at least 4 relevant studies), and (3) proposed research methods. The presentation should be between 8-12 minutes, followed by 5 minutes of Q&A.
- Final Poster Session (15%): Each research project team will present its research and results to the class via a short oral presentation and a poster. Students also need to prepare a 1-2 minute of short video and upload it onto YouTube to attract attention about their research. Further details will be provided later in the semester.
- Final Report (20%): Students will write a report of the project using standard report-writing style (e.g., introduction, related work (literature review), hypotheses, method, results, discussion). The research report should be 10-15 pages, double spaced, excluding tables and figures.
- Class participation (10%): Students are expected to prepare for each class by reading and taking notes on the assigned readings and participating actively in class discussions. Students may be called on to summarize the major arguments, strengths, weaknesses, or problems in any assigned reading.
Each student is allowed to miss two classes without any need for explanation. However, if a student misses more than two classes, no excuses will be accepted. Also, students should not miss their own class leading, team project presentation, data collection, or the poster session.
- Bonus (2%): Participating in any user studies related to communication, design, psychology, and human-computer interaction at NCCU will lead to +0.5 of the final semester points. Students can participate in up to 4 studies. (If a study takes more than 30 minutes, it counts as 2 studies.)
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