Why can’t AI truly know without lived experience? A client recently asked me to localize their Russian website for a U.S. audience.
I asked, “What are your goals?”
They replied:
“We want to make sure it makes laser-sharp sense to the target audience. We’re not interested in translating words – AI can do that. We’re interested in creating a sense of connection. AI can’t do that. Do you have any relevant experience?”
I sent them a list of similar projects and explained what I could do for them.
In the meantime, I couldn’t resist looking up the etymology of the word experience.
What exactly is experience – and why doesn’t AI have it?
The word experience comes from the late 14th-century Latin experientia, meaning “trial, proof, understanding gained through repeated attempts.”
In other words, experience is the result of many experiments – learning through trial and error.
The distinction between knowledge and experience is essential.
No matter how much I “know” about cooking an omelet, I will never be good at it until I try it a thousand times.
To understand, I must “stand under.” To understand rain, I must “stand under” the rain. You don’t know what rain it by collecting all the information in the world about it.
Similarly, to understand a subject, we must stand (or sit) under it long enough to “get it.”
I am noticing a clear trend in my work – clients are increasingly looking for experience. The more proven experience you have, the more you bring to the table.
People instinctively (or consciously) distinguish between “knowledge as data” and “knowledge as UNDER – STANDING.”
