Course Overview

AI and machine learning technology has become increasingly integrated with our everyday lives. Yet, such systems are often complex, unpredictable and unfamiliar, making it difficult for users to understand, trust and adopt them. This graduate course will involve a survey of existing literature on Human-AI interaction, covering topics such as safety, fairness, engagement, interpretibility, trust. The course is also a methodology course---we will study different HCI methodologies (e.g., experiments, diary studies, interviews, etc) and analysis techniques (e.g., statistical modeling, grounded theory analysis) and apply them to research questions related to Human-AI interaction. There are three main components: Paper Critique, Presentation, Project.

1. Paper Critique

On alternate weeks, students will learn about a particular type of HCI methodologies through lecture and group work. Students will get into groups of 4-5 to discuss how prior work has applied the methodology to research questions, identify the methodological shortcomings and brainstorm ways to improve upon them. Each group will submit a summary of their discussion. Prior to each class, students must do the assigned reading in preparation for their group work.

2. Presentation

On alternate weeks, designated students will each give a 15-minute presentation on a paper that employs a particular type of methodology to tackle research questions relatd to human-AI interaction. The presenter will lead a short (5-10 minute) discussion with the class about the novelty/relevance of the research questions that the paper addresses and the validity/rigor of the methodologies.

3. Project

The class project is the most important component of this course. Students will work on an individual project to answer research questions related to human-AI interaction, and apply at least two of the methodologies we learned in class to answer the questions. Students are encouraged to choose topics that are closely aligned with their own research area. The project will have four deliverables: (a) a 2-page project proposal, (b) a 6-page paper draft (without results), and (c) a 10-page final paper (with results), and (d) a project poster or demo. The project proposal, draft and final paper must be in SIGCHI format. Students are encouraged to submit their work to conferences as a short or full paper. The project will be judged by its research impact (in terms of novelty of the research questions and the significance of the results) as well as the soundness and clarity of the employed methodologies.

Attendance and Classroom Etiquette

Students are expected to attend every class. Participation grade will be based, in part, on how many classes are missed. Special consideration can be made for a few exceptions (e.g., academic travel, illnesses and family emergencies). However, students must discuss their anticipated absence with the instructor, and provide the necessary justification and documentation. During class, students are strongly discouraged to use their laptops and mobile devices unless instructed to do so.


Students will be evaluated on the quality of their participation (in-class discussions), as well as their paper critique, presentation and project.