In the Spring, Chris teaches a course on Human-AI Interaction, this page describes the course, its structure, and the topics covered for those that might be interested in taking it.

Course Description

Artificial Intelligence (AI) applications are widespread and already transforming nearly every aspect of society. As AI becomes more broadly embedded in technologies that interact with and affect everyday people, it is increasingly important to consider human-AI interaction design as part of the AI system development process. This class introduces the unique design challenges presented by AI. It explores questions of usability and user experience specific to AI systems, and it reflects more broadly on the relationship between humanity and emerging technologies. Students will practice skills in design, research and writing regarding the human side of AI. Topics include AI and society, interactive system design, speculative design, fairness, explainability, human augmentation/amplification, etc. No programming experience required.

Learning Goals

As a result of your experience in this course, you will be able to:

  • Develop a deep understanding of what human–AI interaction (HAII) is, including its foundations, current issues, and future potential.
  • Cultivate a critical mindset for thinking about AI, HAII, and related topics, that will enable you to more successfully navigate research and practice within the HAII space.
  • Develop your metacognition and your ability to learn about learning, so that you can managing your own learning and success.
  • Explain the design challenges that AI systems present.
  • Evaluate the arguments for and against the application of AI in various aspects of human society and participate in public discourse on these topics.
  • Advocate for AI applications and design choices you care about using the knowledge and skills gained in this course, such as ensuring fairness and accessibility in AI systems.

Schedule & Topics

1/13: Class Intro
READ: Syllabus

1/15: Human-Computer Symbiosis and AI vs. IA
READ: Licklider, J. C. (1960). Man-computer symbiosis.
IRE Transactions on Human Factors in Electronics, 1(1), 4–11.
READ: Markoff, J. (2015). Between human and machine.
In Machines of Loving Grace (ch. 1; pp. 1–18).
OPTIONAL: Full Markoff book (ProQuest).

1/20: Direct Manipulation vs. Interface Agents
READ: Shneiderman & Maes (1997). Direct manipulation vs. interface agents.
interactions, 4(6), 42–61.
DEBATE: In-class debate (assigned position).
OPTIONAL: DirectGPT; Agent Laboratory

1/21: DUE Learning Goals Self-Assessment

1/22: Broader Perspectives on Humans and AI Automation
READ: Wiener (1960). Some moral and technical consequences of automation.
Science, 131(3410), 1355–1358.
READ: Ito (2017). Resisting reduction: A manifesto.
Journal of Design and Science.
OPTIONAL: Bigham (2019).

1/27: LLMs
READ: Bender et al. (2021). On the dangers of stochastic parrots.
FAccT 2021.

1/29: LLMs and Human-AI Interaction
READ: Zamfirescu-Pereira et al. (2023). Why Johnny can’t prompt. CHI 2023.
OPTIONAL: Wu et al. (2022); Lin & Martelaro (2024).

2/3: Interactive Task Learning
READ: Laird et al. (2017). Interactive task learning.
IEEE Intelligent Systems, 32(4), 6–21.
READ: Lawley & MacLellan (2024). Val: Interactive task learning with GPT dialog parsing. CHI 2024.
OPTIONAL: MacLellan et al. (2018); Simard et al. (2017); Amershi et al. (2014).

2/5: Mixed-Initiative Systems
READ: Horvitz (1999). Principles of mixed-initiative user interfaces. CHI ’99.

2/9: DUE Project Proposal Materials

2/10: Presentation and Discussion of Project Ideas

2/12: Challenges in Human-AI Interaction Design
READ: Yang et al. (2020). Why human–AI interaction is uniquely difficult. CHI 2020.

2/17: AI as a Design Material
READ: Yildirim et al. (2023). Creating design resources to scaffold AI ideation. DIS 2023.
REVIEW: AI Brainstorming Kit
OPTIONAL: Google People + AI Guidebook

2/19: Guidelines for Human-AI Interaction
READ: Amershi et al. (2019). Guidelines for human-AI interaction. CHI 2019.
OPTIONAL: Design Principles for Generative AI Applications

2/23: DUE Critique of an Existing Human-AI Interaction Technology

2/24: Fair and Inclusive AI Systems
READ: ProPublica. Machine Bias.
READ: Winner (1980). Do artifacts have politics?

2/26: Fair and Inclusive AI
READ: Costanza-Chock (2018). Design Justice, A.I.
WATCH: Buolamwini (2018). AI, Ain’t I a Woman.

3/2: DUE Peer Reviews

3/3: Fair and Inclusive AI
READ: Keyes et al. (2019). A mulching proposal.
OPTIONAL: Wired article

3/5: Data — Where Does It Come From?
READ: Baack & Mozilla Insights (2024). Training Data for the Price of a Sandwich.
OPTIONAL: Fiesler & Hallinan (2018).

3/9: DUE Midterm Learning Self-Assessment

3/10: Ethical Challenges
READ: Rezwana & Maher (2023). Ethical challenges in Human-AI co-creativity.
OPTIONAL: Wang et al. (2023); Munteanu et al. (2015).

3/12: AI Literacy
READ: Long & Magerko (2020). What is AI literacy? CHI 2020.

3/17: AI and Education
READ: Jurenka et al. (2024). Responsible generative AI for education.

3/19: Writing Assistants
READ: Lee et al. (2022). Coauthor. CHI 2022.
OPTIONAL: Siddiqui et al. (2025).

Spring Break (No Class)

3/31: Agentic AI and Design Challenges
READ: Passi (2025). Agentic AI has a human oversight problem.
OPTIONAL: Bansal et al. (2024).

4/1: DUE Reviews for Assigned Papers

4/2: Mock Paper Review

4/6: DUE Proposal for a Novel Human-AI Interaction Technology

4/7: AI and Risks
READ: Harvey et al. (2025). Educator-centered harms from LLMs.

4/9: AI and Risks
READ: Zhou et al. (2023). Synthetic Lies.
OPTIONAL: Lee et al. (2024).

4/13: DUE Peer Feedback

4/14: AI and Risks
READ: Jakesch et al. (2023). Opinionated language models.
OPTIONAL: Doshi & Hauser (2024).

4/16: Child-AI Interaction
READ: Druga et al. (2017).

4/20: DUE Define What Human-AI Interaction Is

4/21: Human-AI Teaming and the Future of Work
READ: Stowers et al. (2021).
OPTIONAL: Future of Work readings/videos

4/23: Project Presentations

4/27: DUE Peer Feedback

4/29: Project Presentations

4/30: DUE Final Project Materials; Finals (No Class) 5/4: DUE Final Learning Self-Assessment & Course Feedback
DUE: CIOS Course Evaluation

5/5–5/7: Finals (No Class)

Participation & Attendance

Evidence suggests that time spent actively and deliberately engaging with content is directly correlated with learning (see Chi’s ICAP Framework). We will utilize class time to discuss the readings and class topics as a group. I expect you to complete the readings each week, post on Ed discussion something about the paper, and to come to every class ready to discuss the papers, what you posted, and to engage in group activities.

Readings

There is no required textbook in this course. We will read several articles each week, but these will be made available freely. If you would like to supplement your reading in this course with other books and podcasts on the topic of HAII, see the Additional Resources section below.

Key Activities

The primary activity for the course will be reading and discussion. I have intentionally designed the class to not have lots of assignment, so I fully expect you to do the reading in preparation for each class.

Prior to each class you will:

  • READ the papers outlined on the schedule
  • POST approximately 1 paragraph about the paper on Ed Discussion. As part of this paragraph, please list questions, issues, comments, or thoughts you have about each paper. The main purpose of this post is to anchor your reading and to force you to think about and refine a few key ideas to discuss in class. It also will enable the teaching team to track your participation.

In addition to the activities you will do for each class, you will also write three short essays (1-2 pages) and review your peers essays on the following topics:

  • WRITE a 1-2 page critique of an existing human-AI interaction technology;
  • WRITE a 1-2 page proposal for a new human-AI interaction technology; and
  • WRITE a 1-2 page essay reflecting on what they think human-AI interaction is.

Course Grading

This course will utilize an “ungrading” model. What this means is that I will not provide numerical or letter grades to assess your performance. Instead, I will provide you with feedback and guidance in whatever form I believe will best support your learning. As this feedback is intended solely for your development, it will not be linked to your grade within the class.

To support this grading model, I am asking you to provide me with three short reflective essays over the course of the term:

  • A learning goals self-assessment, a description of your learning goals for the course, outlining what you hope to learn and how you hope to use it in the future;
  • A Midterm learning self-assessment, where you outline the effort they have invested in the course, reflect on your progress and what works or does not work for promoting your learning; and
  • A final learning self-assessment, where you outline your overall effort and achievements over the duration of the course. You will also provide a grade (in percentages) that you believe that you deserve with a justification of the grade. I will review your grade and justification with the goal of honoring your assessment and entering it as your overall grade for the course. If I see any major discrepancies between your self-assessment and my own assessment, I will reach out to discuss with you.

Contacting Me

Student–instructor interaction is an important part of any course. I am available to you, and I want to help you succeed in this course, in your program at Georgia Tech, and in life. Please come to me with any questions, problems, discoveries, or anything else you’d like to share. If you have a question that may be of interest to others in the class (e.g., syllabus, readings, logistics, etc.), please ask it during class so that others can benefit. With personal or urgent questions, email me directly or speak to me before or after class.

Office Hours

I will not be hosting fixed office hours. If you’d like to quickly discuss something, then please come speak with me after class. If it requires a longer discussion, then please send me an email and we can arrange a meeting.

Emailing Me

If you email me, then please put “HAII” in the subject line so that I do not overlook your email. Please note that I do not generally check email on nights or weekends. In our always-on society, it is important to set boundaries because healthy lives require off-time, and because our academic activities require uninterrupted periods of time for reading, writing, and thinking. Moreover, taking time to rest and pursue leisure activities has been shown to improve productivity, creativity and accomplishment, as Alex Pang discusses in his book Rest: Why You Get More Done When You Work Less. I hope you will join me in living with more balance.

Health & Wellness

I understand that this course is being offered in a time of tremendous change and uncertainty, and I recognize that you (and I) may encounter unexpected challenges during this term. That includes challenges related to health and illness, technology, caregiving responsibilities, work responsibilities, and more.

My goal this semester is to support you in doing the best work you can in light of the challenges you face. I understand that students face tremendous pressure to work hard, get “good” grades, and be as “successful” as possible. That said, I encourage you to remember that your health and well-being are far more important than the work you do in this class or any class. And I encourage you to take the time you need to care for yourself and for your loved ones.

If you are finding it difficult to balance your health and well-being with your work in this class, please let me know. It is okay to ask for help and to acknowledge when you are struggling, and I am happy to help connect you with resources and services on campus and also make accommodations to our course plan as needed. If you or anyone you know experiences any academic stress, difficult life events, or feelings like anxiety or depression, we strongly encourage you to seek support. The Center for Mental Health Care & Resources is here to help: https://mentalhealth.gatech.edu. Lastly, I also ask that you be patient with me. The challenges of this semester may force me to make last-minute changes to the course. I will do my best to communicate any changes clearly and make them with respect for the inconvenience, frustration, and confusion that change may cause.

Accomodations

If you are a student with learning needs that require special accommodation, contact the Office of Disability Services at (404)894-2563 or http://disabilityservices.gatech.edu/, as soon as possible, to make an appointment to discuss your special needs and to obtain an accommodations letter. Please also e-mail me as soon as possible in order to set up a time to discuss your learning needs.

Additional Resources

If you are interested in the topic of this course and want to investigate these topics more, I recommend the following books and podcasts. If you know of other recommended books along these lines, please share with the class!

Acknowledgements

The design of this course is indebted to the courses on Human–AI Interaction offered at Carnegie Mellon University (https://sites.google.com/andrew.cmu.edu/haii-cmu/home), Virginia Tech (https://cs.vt.edu/Graduate/Courses/GradCourseDescriptions.html#CS6724), the University of Texas at Austin (https://www.ischool.utexas.edu/courses/class-description?courseID=5245), and Williams College (https://sites.google.com/williams.edu/haiiteaching/schedule/). These courses cover additional topics and readings that may be interesting to you as you continue your journey learning about HAII.