About
Researchers are already using AI to write, code, analyze data, and teach. The interesting question is not whether they should, but what happens when they do.
Machine Collaborators is a bi-weekly conversation series. Every session, a researcher presents how AI has entered their actual practice — then we discuss it openly.
Not a tech demo. Not a policy debate. A seminar about practice.
Accelerating Rigorous Quantitative Research with AI Agents: An Introduction to the Data Analyst Augmentation Framework (DAAF)
AI agents can now autonomously plan, write, review, and execute analytic code, raising urgent questions about their role in research given known risks like hallucinations and inaccuracies. This session introduces DAAF, an open-source framework for Claude Code, to help researchers leverage these tools for data analysis while maintaining transparency, reproducibility, and rigor.
Principles of Agentic Research
Silicon Sampling Under Different Sources of Uncertainty
TBD
TBD
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Present your work.
We're looking for researchers with firsthand experience — a workflow that worked, one that didn't, a methodological question you're still sorting out.
Nominate yourself or suggest a colleague.
Nominate a SpeakerConvener
Charles Crabtree
Senior Lecturer, School of Social Sciences, Monash University & K-Club Professor, University College, Korea University.
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