Empathy in data work isn’t about emotion. It’s about intention.

When I build a synthetic audience, I’m not pretending those data points have feelings. I’m acknowledging that the people they represent do. That’s empathy. It’s knowing that every real test has a cost, and choosing to reduce it.

Synthetic audiences are empathy in practice. They let us learn without wearing people out. They let us explore what might resonate before we flood inboxes, feeds, or screens. They create room to think before we act.

But empathy only survives if the system stays honest. When synthetic data starts replacing validation or when outcomes are tuned to please leadership, the empathy goes missing. It stops protecting people and starts protecting pride.

Empathy isn’t sentimental. It’s structural. It’s in how we build, validate, and interpret. The more responsibly we simulate, the more freedom we have to experiment boldly without harm.

So yes, empathy can be synthetic. It just can’t be artificial.