The tech industry is wrong about being data-driven.
To them, "data-driven" means we should rely on data for ideas instead of intuition. We should be objective.
However, that is not even how science works in practice. Karl Popper calls this inductivism, to which he has two objections.
First, data is not objective. Observation is influenced by pre-existing theories that shape how we measure. Our view of the world is filtered through these precedents.
Second, data does not, in a strict sense, generate theories. Theories arise from our creativity. Creativity is our ability to simulate the world in our heads and create an endless stream of new explanations. Intuition is simply the output of our brain’s LLM, which is our world model.
Ideas can come from anywhere, not just data. They can come from a fever dream or an LSD trip (both of which have resulted in ground breaking scientific theories). Data is useful for the second step: rigorous testing. Data is used to falsify our theories, so that we can come up with better ones.
One of Popper’s core ideas is the asymmetry between proving a theory right vs proving it wrong. It is impossible to prove a theory right (Hume’s problem of induction), but it is possible (sometimes trivial) to prove a theory wrong.