Soulware · No. 010
The algorithmic double
Somewhere in the feed's machinery there is a portrait of you — inferred, confidence-scored, monetizable, and never shown. A second self that decides what you see. This interface commits the one crime no platform will: it lets you meet your double, and talk back.
Your double
It is 74% sure it knows you
What the double feeds you
Every card has a reason. The reasons are usually about your softest spots.
What it breaks. The one-way mirror. Recommender systems already maintain a model of you — researchers call it the data double — but the relationship is asymmetric by design: it studies you; you never get to study it back, much less correct it.
Why it might work. Psychology calls it the looking-glass self: we become, in part, what we believe others see in us. A feed is an other that sees you millions of times a day. Making its beliefs visible — and disputable — turns a behavioral extraction loop into something closer to a conversation about who you are.
Where it fails. The double might be right. The genuinely disturbing outcome isn't the wrong inference you can dispute — it's the correct one you would never have admitted. No consent flow prepares you to meet yourself.
If you could read the machine's portrait of you — would you correct it, or would it correct you?