“I was going to come home and talk it over,” Tapani said.
“It’s not your home anymore.” The wedblock termination
passed the fractional house ownership to Alina, although Tapani
retained access to visit Sini.
“Exactly! I accept that. And that was the whole point. Not
even having to decide it was over. No pretending. No fights. No
mess. I don’t understand why you are so upset.”
Alina stared at him. Keep things simple, never make it a
prison, Tapani had said.
“What?” Tapani asked.
“What did you do? Or—who did you do?”
Tapani looked down.
“Are you sure you want to know?”
“What’s her name?”
“Riya. We always ended up sharing a car to work. She liked
to draw; she made a sketch of me. It was nice. It was a good
drawing. So we talked, about silly things. Palomino pencils, the
vlog she had as a teen. I liked her.”
He closed his eyes and massaged his eyelids. “I felt guilty at
first, even for that. Do you remember that old How I Met Your
Mother episode? Marshall imagines his wife dying of cancer and
giving him permission to have a fantasy about a hot pizza delivery
girl. It was like that.”
Tapani smiled sadly.
“And then I remembered my wedblock wife was cool. We
had worked all this out in advance, like grown-ups. So, one
morning … well. It was in the car, and after that, it was hard to
stop. It was like it was meant to happen. You can’t fight things
that are supposed to happen.”
Alina felt dizzy and backed away from the railing. Her
“Nothing,” she whispered, “is supposed to happen.”
“You never believed that, did you?” Tapani said quietly.
“Maybe that was the problem.”
Alina’s knuckles were white. She wanted to punch him in
the face with the wedblock ring, leave an indelible mark, like the
Phantom’s ring in comics.
Instead, she pulled it off and threw it into the stairwell. It
made a faint tinkling sound.
“You are an asshole,” she said.
“I understand that you are upset about Sini, but I found this
great chatbot that explains divorces to children. It’s aimed at
five-year-olds but she’s so smart, she’ll be fine—”
“Do you love her?”
“Of course I love Sini! How can you say that?”
“Not her. That woman. Riya.”
“DO YOU LOVE HER?”
The stairwell multiplied her voice. A door opened some-
“We are moving in together,” Tapani said. “I’ll get my things
next week. You still have my calendar.”
There was a heavy stone in Alina’s chest. A sob escaped, and
she realized she had been holding her breath.
Tapani moved toward her, then hesitated.
“Maybe you should go. I have to get back to work.”
Nothing made sense. It was as if two and two had suddenly
become five. Alina blinked back tears and eyeflicked her way to
the smart-contract app, ignoring Tapani’s hovering.
The termination had been triggered by an AI judge (Northern
Block lawchain public key 07dc74631), based on data from a
single sensor oracle. The wedblock’s deposit tokens had been
transferred to the oracle, for providing the key data for the ruling.
“The car,” she muttered. We always ended up in the same
car, he said.
“Of course,” Tapani said hastily. “I’ll get you a car right away.”
> Explain transaction $078232875b, Alina typed. The
answer came instantly.
> The transaction resulted from following policy
She swore. The explanation system was bolted on top of the
car’s AI. It tried to map decisions of differentiable software—a distant descendant of neural nets—into human-parsable sentences.
It didn’t always make sense. But Alina had to know.
And then she was going to kill the car and the DAO it
> Explain policy tree $3435, she typed with freezing
> Policy tree $3435 maximizes value of in-car sensory data using [ TIP_PREDICTION.py] to match users
whose combinations will result in high data value to
[oraclenet.api], conditional upon user [EULA_UPDATE_
CLICKTHROUGH] to update variable $privacysettings.
Alina stared at the screen. What did this have to do with her
She opened TIP_PREDICTION.py in a terminal text editor. It
was a mess. The original code was by a human coder: a neural net
predicting how much a rider would tip, based on body language.
But the AI had modified it. Those changes were incomprehensible—until she got to the training data set.
There were thousands of videos. She played a few at random.
A romantic comedy. Surveillance footage of a man and a woman
sitting together, the woman playing with her hair. A porn clip
that cut off before the sex.
She nearly dropped the laptop when she understood. It was