21st Century Science Fiction (53 page)

The rest of the day was a blur. Getting to the field involved running the press: yes I’d cut my hair for “safety” reasons, yes I thought this was a good use of our money, not just first-world nations deserved space, it was there for everyone.

There were photos of me getting aboard the tiny rocket plane with a small brown package under my arm. The giant balloon platform that the plane hung from shifted in the gentle, salty island breeze. Not too far away the waves hit the sand of the beach. Inside, suited up, door closed, everything became electronic.

It was the cheapest way to get to orbit. Balloon up on a triangular platform to save on fuel, then light the rocket plane up and head for orbit. We’d scavenged balloons and material from several companies, one about to go out of business. The plane chassis had once been used by a Chinese corporation during trials, and the guidance systems were all open-source. Online betting parlors had our odds at 50 percent. We weren’t even the first, but we were the first island.

The countdown finished, my stomach lurched, and I saw palm trees slide by the portholes to my right. I reached back and patted the package, the hammered-together toy, and smiled.

“Hello out there, all of you,” I whispered into the radio. “We’re coming up too.”

K
EN
L
IU
Ken Liu was born in Lanzhou, China, and moved to the United States when he was eleven. He began publishing SF in 2002. In 2012, his story “The Paper Menagerie” became the first work of fiction, of any length, to win the Hugo Award, the Nebula Award, and the World Fantasy Award. He has also won the SF and Fantasy Translation Award, for his translation into English of “The Fish of Lijiang” by Chen Qiufan. He has translated several other significant works of Chinese SF and literary fiction into English as well.

“The Algorithms for Love,” published in 2004, is about a brilliant designer of robotic toys whose job is driving her crazy. Various segments of this idea could have been used (and some have been used, by other writers) to generate whole stories, but Liu lets it keep rolling along to see what will happen. It’s both a love story and an AI existential-horror story that turns the Turing test inside out.

S
o long as the nurse is in the room to keep an eye on me, I am allowed to dress myself and get ready for Brad. I slip on an old pair of jeans and a scarlet turtleneck sweater. I’ve lost so much weight that the jeans hang loosely from the bony points of my hips.

“Let’s go spend the weekend in Salem,” Brad says to me as he walks me out of the hospital, an arm protectively wrapped around my waist, “just the two of us.”

I wait in the car while Dr. West speaks with Brad just outside the hospital doors. I can’t hear them but I know what she’s telling him. “Make sure she takes her Oxetine every four hours. Don’t leave her alone for any length of time.”

Brad drives with a light touch on the pedals, the same way he used to when I was pregnant with Aimée. The traffic is smooth and light, and the foliage along the highway is postcard-perfect. The Oxetine relaxes the muscles around my mouth, and in the vanity mirror I see that I have a beatific smile on my face.

“I love you.” He says this quietly, the way he has always done, as if it were the sound of breathing and heartbeat.

I wait a few seconds. I picture myself opening the door and throwing my body onto the highway but of course I don’t do anything. I can’t even surprise myself.

“I love you too.” I look at him when I say this, the way I have always done, as if it were the answer to some question. He looks at me, smiles, and turns his eyes back to the road.

To him this means that the routines are back in place, that he is talking to the same woman he has known all these years, that things are back to normal. We are just another tourist couple from Boston on a mini-break for the weekend: stay at a bed-and-breakfast, visit the museums, recycle old jokes.

It’s an algorithm for love.

I want to scream.

• • • •

The first doll I designed was called Laura. Clever Laura™.

Laura had brown hair and blue eyes, fully articulated joints, twenty motors, a speech synthesizer in her throat, two video cameras disguised by the buttons on her blouse, temperature and touch sensors, and a microphone behind her nose. None of it was cutting-edge technology, and the software techniques I used were at least two decades old. But I was still proud of my work. She retailed for fifty dollars.

Not Your Average Toy could not keep up with the orders that were rolling in, even three months before Christmas. Brad, the CEO, went on CNN and MSNBC and TTV and the rest of the alphabet soup until the very air was saturated with Laura.

I tagged along on the interviews to give the demos because, as the VP of Marketing explained to me, I looked like a mother (even though I wasn’t one) and (he didn’t say this, but I could listen between the lines) I was blonde and pretty. The fact that I was Laura’s designer was an afterthought.

The first time I did a demo on TV was for a Hong Kong crew. Brad wanted me to get comfortable with being in front of the cameras before bringing me to the domestic morning shows.

We sat to the side while Cindy, the anchorwoman, interviewed the CEO of some company that made “moisture meters.” I hadn’t slept for forty-eight hours. I was so nervous I’d brought six Lauras with me, just in case five of them decided in concert to break down. Then Brad turned to me and whispered, “What do you think moisture meters are used for?”

I didn’t know Brad that well, having been at Not Your Average Toy for less than a year. I had chatted with him a few times before, but it was all professional. He seemed a very serious, driven sort of guy, the kind you could picture starting his first company while he was still in high school—arbitraging class notes, maybe. I wasn’t sure why he was asking me about moisture meters. Was he trying to see if I was too nervous?

“I don’t know. Maybe for cooking?” I ventured.

“Maybe,” he said. Then he gave me a conspiratorial wink. “But I think the name sounds kind of dirty.”

It was such an unexpected thing, coming from him, that for a moment I almost thought he was serious. Then he smiled, and I laughed out loud. I had a very hard time keeping a straight face while we waited for our turn, and I certainly wasn’t nervous anymore.

Brad and the young anchorwoman, Cindy, chatted amiably about Not Your Average Toy’s mission (“Not Average Toys for Not Average Kids”) and how Brad had come up with the idea for Laura. (Brad had nothing to do with the design, of course, since it was all my idea. But his answer was so good it almost convinced me that Laura was really his brainchild.) Then it was time for the dog-and-pony show.

I put Laura on the desk, her face towards the camera. I sat to the side of the desk. “Hello, Laura.”

Laura turned her head to me, the motors so quiet you couldn’t hear their whirr. “Hi! What’s your name?”

“I’m Elena,” I said.

“Nice to meet you,” Laura said. “I’m cold.”

The air conditioning was a bit chilly. I hadn’t even noticed.

Cindy was impressed. “That’s amazing. How much can she say?”

“Laura has a vocabulary of about two thousand English words, with semantic and syntactic encoding for common suffixes and prefixes. Her speech is regulated by a context-free grammar.” The look in Brad’s eye let me know that I was getting too technical. “That means that she’ll invent new sentences and they’ll always be syntactically correct.”

“I like new, shiny, new, bright, new, handsome clothes,” Laura said.

“Though they may not always make sense,” I added.

“Can she learn new words?” Cindy asked.

Laura turned her head the other way, to look at her. “I like learn-ing, please teach me a new word!”

I made a mental note that the speech synthesizer still had bugs that would have to be fixed in the firmware.

Cindy was visibly unnerved by the doll turning to face her on its own and responding to her question.

“Does she”—she searched for the right word—“
understand
me?”

“No, no.” I laughed. So did Brad. And a moment later Cindy joined us. “Laura’s speech algorithm is augmented with a Markov generator interspersed with—” Brad gave me that look again. “Basically, she just babbles sentences based on keywords in what she hears. And she has a small set of stock phrases that are triggered the same way.”

“Oh, it really seemed like she knew what I was saying. How does she learn new words?”

“It’s very simple. Laura has enough memory to learn hundreds of new words. However, they have to be nouns. You can show her the object while you are trying to teach her what it is. She has some very sophisticated pattern recognition capabilities and can even tell faces apart.”

For the rest of the interview I assured nervous parents that Laura would not require them to read the manual, that Laura would not explode when dropped in water, and no, she would never utter a naughty word, even if their little princesses “accidentally” taught Laura one.

“ ’Bye,” Cindy said to Laura at the end of the interview, and waved at her.

“ ’Bye,” Laura said. “You are nice.” She waved back.

Every interview followed the same pattern. The moment when Laura first turned to the interviewer and answered a question there was always some awkwardness and unease. Seeing an inanimate object display intelligent behavior had that effect on people. They probably all thought the doll was possessed. Then I would explain how Laura worked and everyone would be delighted. I memorized the non-technical, warm-and-fuzzy answers to all the questions until I could recite them even without my morning coffee. I got so good at it that I sometimes coasted through entire interviews on autopilot, not even paying attention to the questions and letting the same words I heard over and over again spark off my responses.

The interviews, along with all the other marketing tricks, did their job. We had to outsource manufacturing so quickly that for a while every shantytown along the coast of China must have been turning out Lauras.

• • • •

The foyer of the bed-and-breakfast we are staying at is predictably filled with brochures from local attractions. Most of them are witch-themed. The lurid pictures and language somehow manage to convey moral outrage and adolescent fascination with the occult at the same time.

David, the innkeeper, wants us to check out Ye Olde Poppet Shoppe, featuring “Dolls Made by Salem’s Official Witch.” Bridget Bishop, one of the twenty executed during the Salem Witch Trials, was convicted partly based on the hard evidence of “poppets” found in her cellar with pins stuck in them.

Maybe she was just like me, a crazy, grown woman playing with dolls. The very idea of visiting a doll shop makes my stomach turn.

While Brad is asking David about restaurants and possible discounts I go up to our room. I want to be sleeping, or at least pretending to be sleeping, by the time he comes up. Maybe then he will leave me alone, and give me a few minutes to think. It’s hard to think with the Oxetine. There’s a wall in my head, a gauzy wall that tries to cushion every thought with contentment.

If only I can remember what went wrong.

• • • •

For our honeymoon Brad and I went to Europe. We went on the transorbital shuttle, the tickets for which cost more than my yearly rent. But we could afford it. Witty Kimberly™, our latest model, was selling well, and the stock price was transorbital itself.

When we got back from the shuttleport, we were tired but happy. And I still couldn’t quite believe that we were in our own home, thinking of each other as husband and wife. It felt like playing house. We made dinner together, like we used to when we were dating (like always, Brad was wildly ambitious but couldn’t follow a recipe longer than a paragraph and I had to come and rescue his shrimp étouffée). The familiarity of the routine made everything seem more real.

Over dinner Brad told me something interesting. According to a market survey, over 20% of the customers for Kimberly were not buying it for their kids at all. They played with the dolls themselves.

“Many of them are engineers and comp sci students,” Brad said. “And there are already tons of Net sites devoted to hacking efforts on Kimberly. My favorite one had step-by-step instructions on how to teach Kimberly to make up and tell lawyer jokes. I can’t wait to see the faces of the guys in the legal department when they get to drafting the cease-and-desist letter for that one.”

I could understand the interest in Kimberly. When I was struggling with my problem sets at MIT I would have loved to take apart something like Kimberly to figure out how she worked. How
it
worked, I corrected myself mentally. Kimberly’s illusion of intelligence was so real that sometimes even I unconsciously gave her, it, too much credit.

“Actually, maybe we shouldn’t try to shut the hacking efforts down,” I said. “Maybe we can capitalize on it. We can release some of the APIs and sell a developer’s kit for the geeks.”

“What do you mean?”

“Well, Kimberly is a toy, but that doesn’t mean only little girls would be interested in her.” I gave up trying to manage the pronouns. “She does, after all, have the most sophisticated,
working
, natural conversation library in the world.”

“A library that you wrote,” Brad said. Well, maybe I was a little vain about it. But I’d worked damned hard on that library and I was proud of it.

“It would be a shame if the language processing module never got any application besides sitting in a doll that everyone is going to forget in a year. We can release the interface to the modules at least, a programming guide, and maybe even some of the source code. Let’s see what happens and make an extra dollar while we’re at it.” I never got into academic AI research because I couldn’t take the tedium, but I did have greater ambitions than just making talking dolls. I wanted to see smart and talking machines doing something real, like teaching kids to read or helping the elderly with chores.