Real problems—pandemics, housing, misinformation—ignore department boundaries. Interdisciplinarity isn’t jargon soup; it’s selecting the right abstraction and testing ideas with multiple lenses.
Three Payoffs
- Better models: CS gives scalable computation; econ gives incentives; sociology gives norms and networks; public health gives measurement and ethics.
- Stronger validation: triangulate with experiments, observational data, and theory.
- Honest uncertainty: multiple methods reveal what’s robust vs. fragile.
Case Sketch: Mobility & Health
Link mobility networks (CS) to transmission models (epi) and behavior change (social science). Results: targeted closures at high-centrality venues can reduce spread with fewer economic costs.
Practice: “Two-column modeling.” Column A: mechanisms you can justify theoretically. Column B: data-driven components. Iterate until both columns tell the same story.
Collaboration Tips
- Agree on the question and stakes first.
- Expose assumptions explicitly; translate across vocabularies.
- Publish methods and data so others can reproduce or adapt.
Note: If two methods disagree, that’s signal—dig into where they diverge. You’ll often find the crucial mechanism.