Dec 08, 2025  
2024-2025 Undergraduate Academic Catalog-June 
    
Catalog Navigation
  Catalog Home
  Academic Calendar
  University Overview
  Admissions
  Student Financial Services
  Academic Regulations and Policies
  Degree Programs, Minors, and Certificates
  Degrees, Minors, and Certificates by Department
  Course Descriptions
  The Raider Core
  MSOE Honors Program
  Global Opportunities
  Reserve Officers’ Training Corps. (ROTC)
  Administration, Regents, and Advisory Committees
  Departments and Faculty
  Campus Map
  Student Resources
  My Portfolio
HELP
2024-2025 Undergraduate Academic Catalog-June [ARCHIVED CATALOG]

Facebook this Page (opens a new window)
Tweet this Page (opens a new window)
Add to Portfolio (opens a new window)

UXD 2040 - People + Automation

3 lecture hours 0 lab hours 3 credits
Course Description
This course is designed as an introduction to much of the automated technology that exists in the world today. Through a human-centered lens, we will look at machine learning, artificial intelligence, recommender systems, computer vision, and more to understand the technology and where humans fit in. While you will not have to learn to code, you will gain a deep understanding of these different technologies, including how they differ and how they are constructed. We will also look at potential issues, sources of bias, and the ethics of these systems as well as following news stories about automation. Our focus will be human centered to allow students to advocate for or against said systems, based on the details surrounding them.
Prereq: COM 2001 , sophomore standing (quarter system prereq: GS 1002 or GS 1020H or GS 1002E)
Note: Not available for credit for students who have taken CSC 4601 , CSC 4611 , CSC 4631  or other technical courses around AI, machine learning, or other similar topics.
This course meets the following Raider Core CLO Requirement: None
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
  • Describe different automation technology and the underlying processes
  • Critique potential issues with automation when presented with an automation plan
  • Recognize sources for bias within an automated system
  • Differentiate between different types of automation (e.g., computer vision and natural language processing)
  • Debate the use of automation technology both from the perspective of the engineers and the users
  • Advocate for humans in new automation products
Prerequisites by Topic
  • None
Course Topics
  • What is automation?
  • Artificial intelligence
  • Neural networks
  • Machine learning
  • Deep learning
  • Computer vision
  • Natural language processing
  • Recommender systems
  • Bioinformatics
  • Data mining
  • Cryptography
  • Robotics
  • International audiences
  • Encoded bias
  • Ethics of automation
Coordinator
Dr. Katherine Panciera


Facebook this Page (opens a new window)
Tweet this Page (opens a new window)
Add to Portfolio (opens a new window)