Using cognitive empathy with AI: name the audience, tone, format, and limits instead of giving it three words and a mood and hoping for the best.
The story
AI-ish patterns I’d cut:
– Too tidy before/after setup. It feels pre-packaged.
– Cute comparisons doing too much: vending machine, coworker, bridge.
– Generic signposts like “Here’s what changes.”
– Listy rhythm: context, task, audience, tone, format, constraints.
– Vague authority drops: “Microsoft folks,” “studies show.”
– Big finish line meant to sound quotable.
Rewrite:
I used to give AI three words and a mood, then feel annoyed when the answer missed.
Conflatulations, me. I explained almost nothing and expected mind reading. Great plan. I’m totally serious, unless I’m not.
Then I started using cognitive empathy. Not the warm fuzzy kind where we all hold hands and become enlightened forest creatures. The plain kind: What does this thing need from me to be useful?
Who is this for? What do they already know? What do I want them feeling, choosing, or making after they read it? Do I want a rough draft, a second opinion, or a cleaner version of my own messy thought pile?
If you manage people, this matters. AI will guess when you leave blanks. Sometimes it guesses well. Sometimes it spawns nonsense with confidence and a nice haircut.
You can blame the tool if you want. That’s an option. Notice the cost, though: same input, same output, same tiny rage snack.
A more useful move is naming the audience, tone, format, and limits. Then you keep your judgment. AI gives you a starting point. You decide what survives.
Oh and AI can write empathy-flavored sentences. People often like them until they learn a person didn’t write them. Then the room gets weird.
That tells me something. People don’t only want nice words. They want care, ownership, and lived experience. Still our turf, before the singularity.
Cognitive empathy helps me track the human and the machine without worshipping either one. Yay, adulthood.
That’s the bit I wrote about in “A Practical EmPath: Rewire
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