Theoretical Versus Empirical

Theoretical means what we expect based on how we think it works. We’ve done analysis and math, and drawn these conclusions through reasoning.

Empirical means what we expect based on what we’ve seen in the real world. We’ve watched and measured, and we’ve drawn these conclusions through observation.

• Theoretical: “We analyzed it and think this change should make the software faster.”
• Empirical: “We ran 1,000 tests and measured a 12% improvement.”

For thousands of years, humans worked in both worlds. Sometimes with tension (like in the Physics world) and friendly one-upmanship about which is more important. Both approaches require creativity and a solid knowledge base about the topic.

Now we can add AI in.

For theory, AI helps because it can find patterns that we can’t or haven’t yet and it’s really good at using tools that we’ve provided for it.

For empiricism, AI helps because it can run bajillions of tests and iterations, and it’s really good with massive data sets.

In both, it can connect the dots across its eidetic, almost infinite memory.

But it can’t create. Not the way we do.

Generative is not the same as creative. AI looks creative, but its still just statistical.

Whether we’re talking about theoretical or empirical, AI helps move everything forward, but we, the humans, are still the secret sauce.