AI 380: Human-AI Interaction

Fall 2026 · Willamette University

Fall 2026 · AI 380

Human-AI Interaction

Designing Intelligent Systems that Work for Humans

Explore the intersection of human-centered design, natural language processing, and conversational AI — building systems that are usable, inclusive, and trustworthy.


Course Overview

This course introduces the core principles of human-centered design for conversational AI systems — including chatbots, virtual assistants, and interactive voice interfaces. Students explore how natural language processing (NLP), dialogue management, and user experience (UX) principles converge to create intuitive, accessible, and inclusive AI interactions.

Through hands-on projects, students learn to design, prototype, and rigorously evaluate conversational interfaces that handle real-world user intent while accounting for system limitations, user trust, and safety. We draw inspiration and methodology from leading programs at top HCI institutions.

Note

Prerequisite: CS 151 is required before taking this course. Students who have completed a software engineering course will find it an additional advantage — however, because of the interdisciplinary nature of this course, non-CS majors are strongly encouraged to enroll as well.

Course Note: This course requires group project work. Students who enroll must be ready to collaborate with peers on a substantial design and evaluation project throughout the semester.


Key Information

📅
Lecture Days
Monday & Wednesday
10:20 AM – 11:50 AM
📍
Location
Smullin 119
Willamette University
🎓
Credits
4 Credits
Prerequisite: CS 151
👥
Project Groups
2–3 Members
Collaborative design
🕐
Office Hours
Tue & Thu
10:30 AM – 12:00 PM
💬
Communication
Discord + Email
fjagbo@willamette.edu

Instructor

Professor Fred Agbo, PhD

Fred Agbo, PhD

Assistant Professor of Computer Science

School of Computing & Information Sciences · Willamette University

📧 fjagbo@willamette.edu 🏢 Ford Hall 209 ⏰ Office Hours: Tue & Thu, 10:30 AM–12:00 PM


Course Learning Objectives

By the end of this course, you will be able to:

01

Critique & Synthesize Research

Review scientific literature in human-AI interaction to synthesize trends, evaluate technological tradeoffs, and inform evidence-based design decisions.

02

Design Conversational Systems

Apply human-centered design principles alongside NLP and dialogue management frameworks to prototype and build functional, context-aware conversational interfaces.

03

Evaluate Usability & Ethics

Conduct rigorous usability testing to assess user trust, efficiency, and error recovery, while analyzing ethical risks, accessibility constraints, and AI failure modes.

04

Collaborate & Communicate

Work in multidisciplinary teams to manage interactive AI projects, communicating outcomes through professional presentations and technical reports.


Course Modules

M1

Human-AI Interaction & User-Centered Design

Weeks 1–4 · Aug 24 – Sep 16

Foundations of HCI, the role of humans in AI, design thinking, needfinding, user research, and personas. Establishes the vocabulary and frameworks for human-centered practice.

Role of Humans in AI Need Finding Personas Design Process

M2

Human-AI Collaborations

Weeks 5–8 · Sep 21 – Oct 14

Conversational AI design, human-AI collaboration challenges, dialogue management guidelines, Lab 1, and Workshop 2. Midterm quiz in Week 7.

Conversational AI Lab 1 Guidelines for HAI Workshop 2

M3

AI Design & Conversational Orchestration

Weeks 9–11 · Oct 19 – Nov 4

Deep-dive into building AI assistants with Rasa CALM. Three hands-on lab sessions guide teams through implementation of their conversational AI assistant.

CALM Architecture Labs 2–4 (Rasa) Accessibility Docker

M4

UX, Usability Study, Report & Presentation

Weeks 12–15 · Nov 9 – Dec 2

Usability testing with real older adult users, heuristic evaluation, project documentation, peer review, and final public presentations.

Usability Testing Heuristic Eval Peer Review Final Demo


Grading at a Glance

20% Participation

20% HW & Personal Project

10% Quiz

40% Group Project

10% Final Essay

See the full syllabus for detailed grading criteria and the assignments page for deliverable descriptions.


Value Statement

This course is designed for students from all disciplinary backgrounds — not just Computer Science. We believe diverse perspectives are essential for designing AI systems that work for everyone. We are committed to creating a learning environment that is equitable, inclusive, and welcoming.

Students of different abilities, identities, and disciplinary backgrounds bring unique value to human-centered AI design. Your perspectives on how AI systems affect your community are not just welcome — they are essential to the course’s intellectual mission.

“The goal is not to build AI that thinks like humans, but AI that works for humans — in all their wonderful diversity.”

If you have any accessibility needs or accommodations, please contact the Accessible Education Services office or reach out to the instructor directly.

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