We've rebuilt Research Lunch Club from the ground up 🛠️ — a brand-new website and a member app that takes the faff out of meeting fellow researchers over lunch.

What's new:

⏱️ The result from our test groups? Members now spend 74% less time working out when and where to meet—from days of back-and-forth down to a couple of taps. 👇

🧪 Believability Is Not Validity: What Synthetic Respondents Actually Do (and Don’t) Tell You, by Tonie Marie Gordon, PhD : Gordon takes apart a quiet assumption behind synthetic respondents: that because an LLM's answers sound plausible, they must be methodologically sound. Her point is that language models capture the distribution of language, not the distribution of real attitudes or behaviours — so synthetic samples can distort incidence rates, overfit to dominant narratives, and quietly erase marginalised or niche voices, all while reading as detailed and convincingly human. She isn't anti-synthetic: she sees a genuine role for these tools in pressure-testing concepts, generating hypotheses, and exploring edge cases. The line she draws is that they can't stand in for empirical human data, and when used they need to be clearly framed, constrained, and audited rather than trusted on vibes.

🧠 Qualitative Researchers Point Out The Limitations of AI’s Contributions Kelley Cotter, Ankolika De & Priya C. Kumar for Social Science Space : Kelley Cotter, Ankolika De and Priya C. Kumar make the case that AI can support qualitative work without actually doing qualitative work. They contrast AI interviewing systems with human interviews, where good research is flexible, relational, and responsive to context in ways a scripted system can't match. Their sharpest argument is about positionality: AI has no lived experience, identity, or reflexive awareness, so it can't shape questions, read what a participant isn't saying, or account for its own bias the way a researcher does. The takeaway is a clean distinction worth keeping handy — AI may generate data, but it doesn't do inquiry.

⏳ What Gets Lost When UX Research Speeds Up by Maria Panagiotidi : Maria Panagiotidi, who writes the UX Psychology newsletter, makes the practitioner's case that the speed AI brings to research carries a quiet cost. Thematic analysis and interpretation are the parts that actually build understanding — and they're exactly the parts that don't compress, even as organisations increasingly treat research as a task to optimise rather than thinking to protect. She backs it with uncomfortable signals: researcher sentiment falling, dedicated research roles thinning out, and methodology quietly vanishing from shortened reports. Her ask isn't to refuse the tools but to be honest about the trade-offs — protect the methods section, document what got skipped, and use your expertise to counsel the right depth rather than ship an answer at any cost.

🔗 Submit An Article!

The detailed ones. The ones with examples and edge cases. Wispr Flow lets you speak them instead — clean, structured, ready to paste into any AI tool. Free on Mac, Windows, and iPhone.

Try Wispr Flow free

Are you a hiring manager looking to share research opportunities with a global network of over 7,500 researchers in more than 60 countries? We'd love to hear from you! Just drop us an email ✉️.

Europe & UK

North & South America

Our weekly newsletter is a fantastic way to connect with a global audience! With over 7,500 researchers tuning in from more than +65 countries, it's a great chance for sponsors to boost their brand visibility and make a real impact. - 💬 let’s talk!

We’re People of Research & Research Lunch Club - a global hybrid community uniting researchers across the industries, from UX Research to Behavioural Science. We connect, collab and grow. Created by @faysel.