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As we study them, complex systems have a way of asking questions back. About how a model can affect the system. About relationality of measurement. About what it means to observe.
And about who you are when you're doing the science. This workshop lives there.
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September 20 – 27, 2026 · INTP.science, French Pyrenees · 10–20 participants · Early bird price ends May 31 (8 spots left)
Interested? Sign up for an intro call to find out if it's a good fit. Can't make it this time? Tell us why — you'll receive a €50 discount on the next retreat.
What actually drives your science? Not the fundable version—the real thing. The questions you think about in the shower. The worldview you're not sure you're allowed to admit. The intuitions that feel too personal to put in a paper.
Most of us have forgotten, or learned not to say. We hide behind methodology. We perform "serious scientist" because the alternative feels too vulnerable, too crackpot, too intimate.
The reason this is so hard isn't just social pressure. Most of science trains you to avoid these questions entirely. In simple systems, you don't need to ask them—reductionism gives you a default worldview for free. But the more you work with complex systems, the more that default starts to strain. Emergence, agency, observer-dependence, meaning—these aren't questions you can keep deferring. They shape what you study, how you model it, and what you count as an explanation. At some point, you have to face them.
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This workshop is about facing them together.
The honest science we seek already exists—it's happening in the margins, in the conversations we're "not allowed" to have, in the questions that drive us that don't fit in grant proposals. This workshop brings that science from the margins to the center, for one week, to see what becomes possible.
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The workshop runs two intertwined arcs across the week. They support each other: the inner work makes the research more honest; the research gives the inner work substance and direction.
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The research arc
Every participant presents their work—not the polished conference version, but the real questions underneath. We map the field's landscape together through structured discussions (World Café, fishbowl conversations), then self-organize into collaboration sessions around whatever has the most energy. By the end of the week, we're working toward shared research outputs: a collectively authored field-mapping document, collaboration commitments, and communication plans.
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The inner arc
You arrive in performance mode. Everyone does. The first days soften that—through nature, honest framing, and listening with curiosity rather than critique. Mid-week, we turn the lens inward: where have incentive structures distorted your scientific judgment? Where are you optimizing for proxies—publications, citations, fundability—instead of the questions you actually care about? This is epistemic debugging: noticing where fear, ego, and Goodhart effects have shaped your work. By the end, you articulate what you actually believe and what you're going to do about it.
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Think of it as "Scientists Anonymous"—how did we get here? What happened along the way? And where do we actually want to go?
Your worldview is the set of deep assumptions that shape your research before you even start. Everyone has one. Many scientists have never examined theirs explicitly—which means these assumptions operate invisibly, creating blind spots, unquestioned defaults, and failure modes you can't see because you're inside them.
Here's what it looks like in practice:
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Is science uncovering truth, or creating beautiful frameworks? If you believe there's an objective reality your models approximate, you optimize for predictive accuracy and treat anomalies as puzzles to solve within the existing paradigm. If you believe science constructs elegant frameworks that organize experience, you optimize for coherence and explanatory power—and you're more willing to abandon a framework entirely when a better one appears. Same data, same equations, but these two starting points lead to genuinely different research programs.
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