Colin MacArthur
Colin MacArthur is the former Director of Digital Practice, and Head of Design Research, at the Canadian Digital Service. Now he’s an Adjunct Professor of Design and Digital Government at Bocconi University in Milan, Italy. He also advises several organizations on design and research strategy. Colin was once described as a “die-hard artificial intelligence hater,” but has been teaching students to use AI to do UX research for several years now.
For more, keep up with Colin at colinmacarthur.org or on Twitter as @colinpmacarthur.
Presentations
Tent Talks with Colin MacArthur
The Designer’s Dilemma: Navigating AI’s Impact on Design
In this Tent Talks session with Colin MacArthur, we’ll explore the nuanced ways in which Artificial Intelligence, particularly Large Language Models, is reshaping the landscape of design. Colin, an expert in integrating AI with product design, will share his insights into how this technology is not just a tool but a collaborator that brings both challenges and opportunities to the creative process. From the evolution of human creativity in the age of AI to the ethical considerations and educational shifts required to navigate this new era, attendees will gain a comprehensive understanding of what the future holds for design professionals.
Why It Matters: As AI continues to make its mark across various industries, understanding its impact on design is crucial for professionals looking to stay ahead of the curve. This session promises to spark a thought-provoking discussion on the balance between technology and human creativity, the ethical implications of AI in design, and how we can prepare for a future where AI plays a central role in our creative processes. Join us to uncover the strategies, mindset, and skills needed to thrive in the ever-evolving world of design.
UX Camp Winter 2024
ChatGPT: UX Research Friend, Foe, or Both?
ChatGPT and other large language models (LLMs) seem like magical question answerers. So magical that they make some people wonder: why should I ask real people about my product, when I can ask ChatGPT what they think instead? Why do I need a researcher if an LLM seems to do research for me? And, if ChatGPT can do research, do we still need human UX researchers? LLMs’ vortex of questions are coming to our profession, and making some of us (me included) a tad anxious.
In this talk, I’ll show how UX researchers can see ChatGPT not as a research participant—or competitor—but as a collaborator. In particular, I’ll share:
- How LLMs actually work, and how they’re more like “persona builders” than human researchers
- The real strengths of LLMs that can help you plan more creative interviews and usability tests
- The human strengths you can bring to research analysis/synthesis that LLMs can’t replicate (and probably never will)
- Two ways LLMs can inadvertently lead humans astray – and how to avoid them when you use something like ChatGPT in research
You’ll come away with concrete tactics for appropriately incorporating LLMs into your UX research process, as well as ways to explain their limitations to over-enthusiasts. And hopefully some of you, like me, will learn to worry about LLMs a little less.
UX Camp Fall 2019
Fast, cheap or good research: pick all three!
Have you ever had too little time or money to do good UX research? Trying to fit research into your tight budget, agile sprints or fast-moving project? Feel like giving up? You can do good research under quick timelines and little budget.
I’ll share tricks for fast moving and cheap research that doesn’t compromise quality:
– Using the Goldilocks method to scope doable, but impactful research
– Writing a useful research plan that isn’t ten pages long
– Recruiting participants in under 24 hours with no money
– Building data collection process that surfaces insights as you conduct research
– “Make-in-an-afternoon” deliverables that are just detailed enough to compel your team
I’ll share examples from my experience coaching designers and researchers in lean environments. I’ll also share some of my fast moving research fails, and how you can avoid them. Hopefully, you can learn from my past mistakes and do research quickly, cheaply and well.
