Spring 2026
Designing Experiences and Futures Beyond AI Harm
Directed by: Pitch Sinlapanuntakul (PhD candidate) and advised by Mark Zachry (Faculty advisor)
AI systems can produce unintended harms that are difficult to predict or fully prevent, but designers play a formative role in shaping the concepts and experiences that guide how the products of these systems are built. This DRG focuses on the design of AI experiences, while ensuring that concepts are grounded in human-centered and value-sensitive thinking. Students do not need to build or code AI systems; prototypes can be conceptual, interactive, or optionally AI-enabled, depending on the idea.
Over the quarter, students will lead their own design projects (individually or in pairs), taking ideas from initial sketches to prototypes while iterating and refining based on design critiques along the way. Principles and early analysis of existing harmful AI products will provide inspiration and context, but the main focus is on ideation, making, and hands-on design exploration.
Each project will culminate in a polished AI design concept and supporting artifacts suitable for submission to a design competition or short research-through-design paper. This DRG provides a hands-on opportunity to practice creative design thinking while producing portfolio-ready work that demonstrates how thoughtful design can guide safer AI experiences.
Enrollment information
- Meeting time: Wednesdays, 3 – 4:30 pm.
- Credits: 2 credits (i.e., 6 total hours per week, including a meeting and outside work).
- Who should apply: We are looking for engaged students with interests in designing AI-enabled experiences and values in/through design. Students should be familiar with their proposed design approaches. HCDE students will be prioritized, though students from other departments are welcome to apply.
- This DRG does NOT meet the research requirement for PhD students
- How to apply and deadline: Apply via the Google form by Monday, March 2, 2026 (EoD). You may apply individually or as a pair and will be asked to briefly describe your design idea(s).
- Anticipated notification date: Friday, March 6, 2026
- Questions: Email Pitch Sinlapanuntakul at wspitch@uw.edu
Winter 2026
Harmful AI Patterns and Principles through Design
Co-Directed by Pitch Sinlapanuntakul (PhD candidate) and Mark Zachry (faculty advisor)
AI increasingly shapes our digital experiences, yet even when its unintentional harms are evident, designers often lack ways to address them early in product development. Identifying harmful patterns and designing to prevent them is essential for creating AI that supports human values. This DRG is structured in 2 connected parts:
First, we will curate and analyze real-world examples of problematic AI from academic studies, design critiques, and news articles. We will reflectively code, annotate, and discuss these cases to derive harmful AI patterns.
Second, building on patterns and insights from part 1, we will engage in a research-through-design process to iteratively generate and refine design principles/guidelines as an actionable resource for anticipating and preventing harm in early-stage AI concept development.
Through this DRG, you will gain hands-on experience analyzing harmful AI design patterns, co-developing actionable design resources (e.g., design principles), and building skills in research-through-design, qualitative coding, and value-sensitive design thinking.
Enrollment Information
- Meeting time: Wednesdays, 4:00pm - 5:30pm. Likely hybrid format, depending on the week.
- Credits: 2 credits (i.e., 6 total hours per week, including a meeting and outside work).
- Questions? Email Pitch Sinlapanuntakul at wspitch@uw.edu
Winter 2026
Understanding Online Community Norms to Build an AI Agent (2)
Co-Directed by PhD student Soobin Cho, Dr. Mark Zachry and Dr. David McDonald
Every online community has norms and policies that shape member behavior. This DRG focuses on Wikipedia, one of the largest examples of online collaboration, where massive collaborative efforts create encyclopedic articles supported by complex community policies. Wikipedia policies vary from relatively simple to intricate. Some policies are complex and multi-faceted making them difficult for humans to understand, presenting an opportunity for AI assistance.
In this DRG, students will gain foundational knowledge about online collaboration with a focus on Wikipedia and AI training methodologies. The core work involves collecting and conducting qualitative analysis of real cases where Wikipedia policies are applied, contributing to a dataset that will be used to train norm-aware AI agents.
This DRG is a continuation of our AU25 DRG. All are welcome to apply: students who are not currently participating; those who applied last quarter; as well as those who are participating now. Students interested in joining should have:
- An interest in online collaboration and online community dynamics
- Prior experience with qualitative analysis
This is a 2-credit DRG offered to undergraduate (HCDE 496) and graduate (HCDE 596) students. As a 2-credit DRG, students are expected to devote 4 hours per week outside of the meeting time. Everyone participating in the DRG must be registered for either HCDE 496 or 596. Students participating in this DRG will be meeting weekly on Wednesdays from 3:00 PM to 4:30 PM.
Deadline: Apply for this DRG by December 1st by filling out this survey. We expect to select and notify participants by December 15th. Please reach out to Soobin Cho through email (soobin30@uw.edu) or HCDE Slack with any questions.
Dr. Zachry's research group archive