About
Researchers I know are already using AI to write code, run analyses, draft papers, and prep for class. Most of them are figuring it out as they go. The interesting question isn't whether they should. It's what happens when they do.
I started Machine Collaborators to make space for that question. Every two weeks, a researcher walks through how AI has actually entered their work, the parts that went well and the parts that didn't, and then we talk about it.
No sales pitches. No policy panels. Just honest conversation about practice.
Next Session
September 3, 2026 · 7:00 PM ET
Paul Allison · Statistical Horizons
Vibe coding then and now
Allison compares two adventures in developing statistical software for Stata and R: enlisting a human programmer in 2015 and collaborating with AI coding assistants in 2026. The experiences were surprisingly similar—both required clear instructions, careful checking, and occasional expressions of disbelief—but the differences were just as revealing. He considers what AI does better, what it does worse, and why he now generally prefers the machine, despite a few important caveats and the persistent need to know when it is confidently wrong.
Upcoming
All SessionsUsing AI to extend what students can do
Ethical, Effective, and Transparent Workflows: How to Set Clear Guidelines Surrounding AI Usage for Academic Research
Speak
Share what you've learned.
I'm looking for researchers with firsthand experience: a workflow you built, something that broke, a question you're still working through.
You can nominate yourself or suggest someone else.
Nominate a SpeakerConvener
Charles Crabtree
Senior Lecturer, School of Social Sciences, Monash University.
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