Human-AI Interaction

Chinmay Kulkarni and Mary Beth Kery
Fall 2019, T/TH 3pm-4:20pm

Artificial Intelligence (AI) is inspired by human intelligence, made powerful by human data, and ultimately only useful in how it positively affects the human experience. This course is an introduction to harnessing the power of AI so that it is beneficial and useful to people. We will cover a number of general topics: agency and initiative, AI and ethics, bias and transparency, confidence and errors, human augmentation and amplification, trust and explainability, mixed-initiative systems, and programming by example. These topics will be explored via projects in dialog and speech-controlled systems, automatic speech recognition, computer vision, data science, recommender systems, text summarization, learning science, UI personalization, and visualization.

Students will complete individual bi-weekly mini-projects in which they will design and build AI systems and components across a wide variety of domains. Students should be comfortable with programming; assignments will be primarily in Python and Javascript. Prior experience with AI/machine learning will be useful but is not required. Students will also be responsible for weekly readings, participating on at least one reading panel in class, and short quizzes at the beginning of each class.

More information is on the course syllabus.

This class was previously taught by Jeff Bigham and Joseph Seering in Fall 2018.

Want to teach this class at your own university? Please reuse our slides and assignments: no need to ask permission! We'd love to hear from you about how they work out and how you improve them (and maybe share them back!) Please email Chinmay.