The Scientific Method is wrong: Scientists don’t test hypotheses, but build models
I really enjoyed this interview with my colleague, Nancy Nersessian. (Yes, she’s a Professor in the College of Computing.) It helped me understand better why her perspective is revolutionary, and why she’s been racking up awards for the importance of her work.
One of her arguments is that they way we think about the scientific method is wrong, that our “received” notion of the scientific method is not how scientists really work. Rather than test hypotheses, scientists do experiments to influence their models of how the world works. The hypotheses they test come out of those models, and a “failed” experiment doesn’t disprove the hypotheses as much as it feeds more information into developing a more correct model. That’s another reason why failed experiments are so important — they lead to better models.
Georgia Tech’s Nancy Nersessian talked about a project that’s been running at her university since 2001 to investigate how bioengineering scientists think and work, and how to pass their skills on to students. Nersessian said that there is a “received view” of the scientific method — you formulate a hypothesis and then test it to either validate or invalidate it — and then there is the way scientists actually go about their day-to-day work.
In the real world of scientific investigation, she said, scientists usually rely on a model-based process rather than a hypothesis-driven one. They formulate models based on what they know from previous research and then derive testable hypotheses from those models. Data from experiments don’t validate or invalidate hypotheses as much as they feed back into the models to generate better research questions.