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COMP_SCI 396, 496: Human-AI Interaction Research


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Prerequisites

Instructor permission

Description

This graduate-level seminar explores the rapidly evolving field of Human-AI Interaction (HAI), focusing on how humans interact with artificial intelligence systems. The course will focus on discussing recent literature in the field of human-computer interaction relating to the design and evaluation of AI systems. Students will be expected to read and lead discussions on various dimensions of human-AI interaction, including ethics, explainability, design methods, human-AI collaboration, recommender systems, and a few notable application areas. You do not need to have a strong ML or HCI background to take this class, but research experience in a related field is strongly encouraged.

Learning Objectives:
By the end of the quarter, students will develop a deep understanding of HAI and related literature. They will practice core research skills, reading and discussing important papers in the field. Each week, there will be 2-3 reading assignments, for which you'll write a short response. Students will also practice core professional skills by leading discussions and presenting research ideas. By the end of the course students will be able to answer the following questions:

  1. What are principles, frameworks, and theories that guide Human-AI Interaction?
  2. What are methods for integrating user feedback into AI development to ensure systems align with human needs, values, and limitations?
  3. What are some of the ethical, legal, and societal implications of AI systems, including issues of bias, fairness, transparency, and accountability.?
  4. What are tools and techniques for evaluating the usability of AI interfaces and experiences?

Pre-Requisites:
Students in the class will likely have different backgrounds and there are no pre-required courses. The course is intended for graduate students and advanced undergraduate students with interest in learning about human-computer interaction research related to the creation of AI systems. Undergraduate and master’s students must receive instructor approval to register.

  • This course fulfills the Technical Elective area.

REFERENCE TEXTBOOKS: N/A
REQUIRED TEXTBOOK: N/A

COURSE COORDINATORS: Prof. Maia Jacobs

COURSE INSTRUCTOR: Prof. Maia Jacobs