Your AI Agent Can Run the Test Just Fine. But Can It Answer the Business Question?
Experiments are systematic tests run on a smaller scale to test a hypothesis. However, in a lot of cases, experiments fail because of the design of the system, constraints, or decision environment, even when they are executed correctly. To put it simply, the experiment was technically sound, statistically powered but the experiment could never have answered the question the business was asking, despite putting enormous efforts to run it. Especially as AI is making strides and experimenting is becoming easier by the day, the question is, “Should I run this test?”
Before running an experiment, I use a simple decision framework to evaluate whether the test will actually produce a meaningful answer.
The Framework
In my experience, this typically happens due to Identifiability, when multiple explanations for the observed experiment outcome are plausible and the experiment cannot distinguish what caused it.
Let's talk about what causes Identifiability and how to...
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