Course Syllabus

Instructor: Daniel Brown Pre-requisites: N/A
Department: School of Computing Credit Hours: 3
Instructor's Office: MEB 2172 Semester: Fall 2023
Class Room: WEB L126 Links to an external site.

Communication

Office Hours: 

dsbrown@cs.utah.edu

by appointment (send me or the TA an email)

Class Time: MoWe / 11:50AM-01:10PM

Schedule and Website:

Human-AI Alignment (utah.edu) Links to an external site.

   
Teaching Assistant: Akansha Kalra
Email:

akansha.kalra@utah.edu

Overview

This course will cover a range of topics related to the problem of how to get AI systems to do what we, as humans, actually want them to do. We will explore a range of topics including active learning, human intent and preference learning, algorithmic teaching, and AI safety. Classes will be a mix of lectures covering foundational materials as well as hands-on analysis and exploration of both seminal and recent research papers. Throughout the semester, students will also be engaged in a novel research project or in-depth literature review, culminating in a final presentation and written technical report. By taking this course, students will develop a broad understanding of the common techniques and unique research challenges involved in building AI systems that learn from, interact with, and assist humans. Additionally, students will learn and practice fundamental research skills, including how to read, write, and review research papers, how to quickly prototype and test research ideas, and how to give technical presentations.

 

Course Summary:

Date Details Due