QUANT UX CON 2026 · WORKSHOP RESOURCES
How to make informed decisions about incorporating AI in UX research workflows.
A practical framework for deciding how to incorporate AI responsibly in the research process, what evidence is needed to trust its work, and where human expertise matters most. Explore the framework, examine worked examples, and build an evaluation protocol for your own research.
ABOUT THE WORKSHOP
Us vs. Them: An Evaluation Framework for AI-Assisted End-to-End UX Research Workflows.
As AI becomes part of everyday research workflows, deciding where and how to use it requires more than comparing outputs or measuring efficiency.
In this 90-minute Quant UX Con workshop, we examine human, AI, and human + AI approaches through blinded evaluations across quantitative UX research tasks. Together, we explore how task characteristics, evidence quality, and delegation risk shape what we can reasonably trust, verify, or delegate.
These resources extend the workshop into practical methods you can use to design and evaluate AI participation in your own research.
Goal
Move beyond whether AI can complete a research task to what evidence would justify relying on its work, under which conditions, and with what human oversight.
Who this is for
UX researchers, research leaders, data scientists, and practitioners evaluating where AI belongs in their research processes without compromising methodological rigor or decision quality.
What you'll walk away with
A framework for assessing task characteristics, evidence requirements, and delegation risk, plus practical worksheets, worked examples, and a toolkit for designing your own evaluations.
RESOURCES & TOOLS
Learn how to apply this in your work.
FIND YOUR STARTING POINT
What are you trying to do?
RECOMMENDED START
Start with the Canvas
Use it to understand the evaluation questions before choosing criteria or testing AI outputs.
Completed Worked Example
Additional resources
All four resources are available to explore independently.
FRAMEWORK · WORKSHEET
Recommended for youAI Evaluation Design Canvas
Start here to frame your evaluation
Identify what you're evaluating, what evidence you'd need, and what risks affect AI use.
ANNOTATED REFERENCE
Recommended for youCompleted Worked Example
Use when you want to see the framework applied
Follow a survey design example to see how evaluation criteria, evidence, and oversight decisions were developed.
LEARNING GUIDE
Recommended for youUnderstand & Evaluate Research Tasks
Use when you want to understand how your task shapes AI evaluation.
Explore how task characteristics influence evaluation decisions, use the interactive guide to assess your own task, and compare three research workflows to see why evaluation approaches differ.
INTERACTIVE TOOL
Recommended for youPractical Evaluation Toolkit
Use when you're ready to evaluate your own task
Build a protocol with test cases, scoring criteria, review steps, and documentation you can reuse.
