Last month, I utilized generative AI to analyze 20 hours of interviews in just 14 hours (instead of over 80). The efficiency is mind-blowing... but at what cost and what opportunity? According to a recent HBR article, 77% of researchers are concerned about AI bias, and only 31% rating AI-generated data as "great," we're facing a critical inflection point in our field.
In the article, I note:
• 3 game-changing opportunities AI brings to UX research
• 3 serious challenges we can't ignore
• Thoughts on the impact and future of research
As researchers, what's our responsibility in this AI revolution?
What's your take: Will AI fundamentally enhance or erode the quality of UX research?
The bias of Chat.GPT and AI
So I did a little experiment with ChatGTP...name me 100 of the most influential BIPOC women in the past 100 years? It's answer highlighted the need to intentionally and consciously train AI with a diverse and representative dataset.
UR + CS = <3
UXR meet your BFF, Customer Success.
If there’s one piece of sage advice or golden rule that I might be able to offer you that will make your life easier (like buttah!) it’s this: customer success is your new best friend. Here are the 5 keys to engaging with CS and unlocking your client research meetings.
Tale of Two Graphs
Once upon a time, there was a unintelligible and incomprehensible graph that was in desperate need of some updates. So a brave and valiant team of designers, researchers, and product managers set off on a quest to test not only their own wills, but also their assumptions in hopes of designing a better graph.





