The Lifecycle of Software Objects

by Ted Chiang

  The Lifecycle of Software Objects

  Ted Chiang

  What's the best way to create artificial intelligence? In 1950, Alan Turing wrote, “Many people think that a very abstract activity, like the playing of chess, would be best. It can also be maintained that it is best to provide the machine with the best sense organs that money can buy, and then teach it to understand and speak English. This process could follow the normal teaching of a child. Things would be pointed out and named, etc. Again I do not know what the right answer is, but I think both approaches should be tried.”

  The first approach has been tried many times in both science fiction and reality. In this new novella, at over 30,000 words, his longest work to date, Ted Chiang offers a detailed imagining of how the second approach might work within the contemporary landscape of startup companies, massively-multiplayer online gaming, and open-source software. It's a story of two people and the artificial intelligences they helped create, following them for more than a decade as they deal with the upgrades and obsolescence that are inevitable in the world of software. At the same time, it's an examination of the difference between processing power and intelligence, and of what it means to have a real relationship with an artificial entity.

  The Lifecycle of Software Objects

  by Ted Chiang

  Chapter One

  Her name is Ana Alvarado, and she’s having a bad day. She spent all week preparing for a job interview, the first one in months to reach the videoconference stage, but the recruiter’s face barely appeared onscreen before he told her that the company has decided to hire someone else. So she sits in front of her computer, wearing her good suit for nothing. She makes a halfhearted attempt to send queries to some other companies and immediately receives automated rejections. After an hour of this, Ana decides she needs some diversion: she opens a Next Dimension window to play her current favorite game, Age of Iridium.

  The beachhead is crowded, but her avatar is wearing the coveted mother-of-pearl combat armor, and it’s not long before some players ask her if she wants to join their fireteam. They cross the combat zone, hazy with the smoke of burning vehicles, and for an hour they work to clear out a stronghold of mantids; it’s the perfect mission for Ana’s mood, easy enough that she can be confident of victory but challenging enough that she can derive satisfaction from it. Her teammates are about to accept another mission when a phone window opens up in the corner of Ana’s video screen. It’s a voice call from her friend Robyn, so Ana switches her microphone over to take the call.

  “Hey Robyn.”

  “Hi Ana. How’s it going?”

  “I’ll give you a hint: right now I’m playing AoI.”

  Robyn smiles. “Had a rough morning?”

  “You could say that.” Ana tells her about the canceled interview.

  “Well, I’ve got some news that might cheer you up. Can you meet me in Data Earth?”

  “Sure, just give me a minute to log out.”

  “I’ll be at my place.”

  “Okay, see you soon.” Ana excuses herself from the fireteam and closes her Next Dimension window. She logs on to Data Earth, and the window zooms in to her last location, a dance club cut into a giant cliff face. Data Earth has its own gaming continents–Elderthorn, Orbis Tertius–but they aren’t to Ana’s taste, so she spends her time here on the social continents. Her avatar is still wearing a party outfit from her last visit; she changes to more conventional clothes and then opens a portal to Robyn’s home address. A step through and she’s in Robyn’s virtual living room, on a residential aerostat floating above a semicircular waterfall a mile across.

  Their avatars hug. “So what’s up?” says Ana.

  “Blue Gamma is up,” says Robyn. “We just got another round of funding, so we’re hiring. I showed your resume around, and everyone’s excited to meet you.”

  “Me? Because of my vast experience?” Ana has only just completed her certificate program in software testing. Robyn taught an introductory class, which is where they met.

  “Actually, that’s exactly it. It’s your last job that’s got them interested.”

  Ana spent six years working at a zoo; its closure was the only reason she went back to school. “I know things get crazy at a startup, but I’m sure you don’t need a zookeeper.”

  Robyn chuckles. “Let me show you what we’re working on. They said I could give you a peek under NDA.”

  This is a big deal; up until now, Robyn hasn’t been able to give any specifics about her work at Blue Gamma. Ana signs the NDA, and Robyn opens a portal. “We’ve got a private island; come take a look.” They walk their avatars through.

  Ana’s half expecting to see a fantastical landscape when the window refreshes, but instead her avatar shows up in what looks at first glance to be a daycare center. On second glance, it looks like a scene from a children’s book: there’s a little anthropomorphic tiger cub sliding colored beads along a frame of wires; a panda bear examining a toy car; a cartoon version of a chimpanzee rolling a foam rubber ball.

  The onscreen annotations identify them as digients, digital organisms that live in environments like Data Earth, but they don’t look like any that Ana’s seen before. These aren’t the idealized pets marketed to people who can’t commit to a real animal; they lack the picture-perfect cuteness, and their movements are too awkward. Neither do they look like inhabitants of Data Earth’s biomes: Ana has visited the Pangaea archipelago, seen the unipedal kangaroos and bidirectional snakes that evolved in its various hothouses, and these digients clearly didn’t originate there.

  “This is what Blue Gamma makes? Digients?”

  “Yes, but not ordinary digients. Check it out.” Robyn’s avatar walks over to the chimp rolling the ball and crouches down in front of it. “Hi Pongo. Whatcha doing?”

  “Pongo pliy bill,” says the digient, startling Ana.

  “Playing with the ball? That’s great. Can I play too?”

  “No. Pongo bill.”

  “Please?”

  The chimp looks around and then, never letting go of the ball, toddles over to a scattering of wooden blocks. It nudges one of them in Robyn’s direction. “Robyn pliy blicks.” It sits back down. “Pongo pliy bill.”

  “Okay then.” Robyn walks back over to Ana.”What do you think?”

  “That’s amazing. I didn’t know digients had come so far.”

  “It’s all pretty recent; our dev team hired a couple of PhDs after seeing their conference presentation last year. Now we’ve got a genomic engine that we call Neuroblast, and it supports more cognitive development than anything else currently out there. These fellows here”–she gestures at the daycare center inhabitants–”are the smartest ones we’ve generated so far.”

  “And you’re going to sell them as pets?”

  “That’s the plan. We’re going to pitch them as pets you can talk to, teach to do really cool tricks. There’s an unofficial slogan we use in-house: ‘All the fun of monkeys, with none of the poop-throwing.’”

  Ana smiles. “I’m starting to see where an animal-training background would be handy.”

  “Yeah. We aren’t always able to get these guys to do what they’re told, and we don’t know how much of that is in the genes and how much is just because we aren’t using the right techniques.”

  She watches as the panda-shaped digient picks up the toy car with one paw and examines the underside; with its other paw it cautiously bats at the wheels. “How much do these digients start out knowing?”

  “Practically nothing. Let me show you.” Robyn activates a video screen on one wall of the daycare center; it displays footage of a room decorated in primary colors with a handful of digient
s lying on the floor. Physically they’re no different from the ones in the daycare center now, but their movements are random, spasmodic. “These guys are newly instantiated. It takes them a few months subjective to learn the basics: how to interpret visual stimuli, how to move their limbs, how solid objects behave. We run them in a hothouse during that stage, so it all takes about a week. When they’re ready to learn language and social interaction, we switch to running them in real time. That’s where you would come in.”

  The panda pushes the toy car back and forth across the floor a few times, and then makes a braying sound, mo mo mo. Ana realizes that the digient is laughing. Robyn continues, “I know you studied primate communication in school. Here’s a chance to put that to use. What do you think? Are you interested?”

  Ana hesitates; this is not what she envisioned for herself when she went to college, and for a moment she wonders how it has come to this. As a girl she dreamed of following Fossey and Goodall to Africa; by the time she got out of grad school, there were so few apes left that her best option was to work in a zoo; now she’s looking at a job as a trainer of virtual pets. In her career trajectory you can see the diminution of the natural world, writ small.

  Snap out of it, she tells herself. It may not be what she had in mind, but this is a job in the software industry, which is what she went back to school for. And training virtual monkeys might actually be more fun than running test suites, so as long as Blue Gamma is offering a decent salary, why not?

  #

  His name is Derek Brooks, and he’s not happy with his current assignment. Derek designs the avatars for Blue Gamma’s digients, and normally he enjoys his job, but yesterday the product managers asked him for something he considers a bad idea. He tried to tell them that, but the decision is not his to make, so now he has to figure out how to do a decent job of it.

  Derek studied to be an animator, so in one respect creating digital characters is right up his alley. In other respects, his job is very different from that of a traditional animator. Normally he’d design a character’s gait and its gestures, but with digients those traits are emergent properties of the genome; what he has to do is design a body that manifests the digients’ gestures in a way that people can relate to. These differences are why a lot of animators–including his wife Wendy–don’t work on digital lifeforms, but Derek loves it. He feels that helping a new lifeform express itself is the most exciting work an animator could be doing.

  He subscribes to Blue Gamma’s philosophy of AI design: experience is the best teacher, so rather than try to program an AI with what you want it to know, sell ones capable of learning and have your customers teach them. To get customers to put in that kind of effort, everything about the digients has to be appealing: their personalities need to be charming, which the developers are working on, and their avatars need to be cute, which is where Derek comes in. But he can’t simply give the digients enormous eyes and short noses. If they look like cartoons, no one will take them seriously. Conversely, if they look too much like real animals, their facial expressions and ability to speak become disconcerting. It’s a delicate balancing act, and he has spent countless hours watching reference footage of baby animals, but he’s managed to design hybrid faces that are endearing but not exaggeratedly so.

  His current assignment is a bit different. Not satisfied with cats, dogs, monkeys, and pandas, the product managers have decided that there needs to be more variety among the avatars, something other than baby animals. They suggest robots.

  The idea makes no sense to Derek. Blue Gamma’s entire strategy relies on people’s affinity for animals. The digients learn through positive reinforcement, the way animals do, and their rewards include interactions like being scratched on the head or receiving virtual food pellets. These make perfect sense with an animal avatar, but with a robot avatar they look comical and forced. If they were selling physical toys, robots would have the advantage of being cheaper to build than plausible animals, but production costs don’t matter in the virtual realm, and animal faces are more expressive. Providing robotic avatars seems like offering imitations at the same time that you’re selling the real thing.

  His train of thought is interrupted by a knock at his doorway; it’s Ana, the new member of the testing team. “Hey Derek, you should watch the video of this morning’s training session. They were pretty funny.”

  “Thanks, I’ll check them out.” She’s about to leave, but then stops. “You look like you’re having a bad day.”

  Derek thinks hiring a former zookeeper was a good idea. Not only did she devise a training program for the digients, she had a great suggestion about improving their food.

  Other digient vendors provide a limited variety of digient food pellets, but Ana suggested that Blue Gamma radically open up the forms that digient food takes; she pointed out that a varied diet keeps zoo animals happier and makes feeding time more fun for visitors. Management agreed, and the development team edited the digients’ basic reward map to recognize a wide range of virtual foods; they couldn’t actually simulate different chemical compounds–Data Earth’s physics simulation is nowhere near good enough for that–but they added parameters to stand in for a food’s taste and texture, and designed an interface for the food-dispensing software allowing users to concoct their own recipes. It’s turned out to be a big success; the individual digients each have their own favorites, and the beta testers report that they love catering to their digient’s preferences.

  “Management decided that the animal avatars aren’t enough,” says Derek. “They want robot avatars, too. Can you believe it?”

  “That sounds like a good idea,” says Ana.

  He’s surprised. “You really think so? I’d have thought you’d prefer the animal avatars.”

  “Everyone here thinks of the digients as animals,” she says.”The thing is, the digients don’t behave like any real animal. They’ve got this non-animal quality to them, so it feels like we’re dressing them in circus costumes when we try to make them look like monkeys or pandas.”

  It hurts a little to hear his carefully crafted avatars compared to circus costumes. His face must give him away because she adds, “Not that the average person would notice. It’s just that I’ve spent a lot more time with animals than most people.”

  “That’s okay,” he says.”I appreciate hearing a different perspective.”

  “Sorry. The avatars look great, honestly. I like the tiger cub especially.”

  “It’s fine. Really.”

  She gives an apologetic wave and walks down the hall, while Derek thinks about what she said.

  Perhaps he’s gotten too wrapped up in the animal avatars, so much so that he’s begun thinking of the digients as something they’re not. Ana’s right, of course, that the digients aren’t animals any more than they’re traditional robots, and who’s to say that either analogy is more accurate than the other? If he works from the premise that a robotic avatar is just as good a way for this new lifeform to express itself as an animal avatar, then perhaps he’ll be able to design an avatar he’s happy with.

  #

  A year later, and Blue Gamma is days away from its big product launch. Ana is at work in her cubicle, across the aisle from Robyn’s; they sit with their backs to each other, but right now both of their video screens are displaying Data Earth, where their avatars stand side by side. Nearby, a dozen digients scamper around a playground, chasing each other over a tiny bridge or under it, climbing up a short flight of steps and sliding down a ramp. These digients are the release candidates; in a few days, they–or close approximations thereof–will be available for purchase to customers throughout the overlapping realms of the real world and Data Earth.

  Rather than teach the digients any new behaviors at this late date, Ana and Robyn are supposed to keep the digients in practice with what they’ve already learned. They’re in the middle of a session when Mahesh, one of the co-founders of Blue Gamma, walks past their cubicles. He pauses to wat
ch. “Don’t mind me; keep doing what you’re doing. What’s today’s skill?”

  “Shape identification,” says Robyn. She instantiates a scattering of colored blocks on the ground in front of her avatar. To one of the digients, she says, “Come here, Lolly.” A lion cub toddles over from the playground.

  Meanwhile Ana calls over Jax, whose avatar is a neo-Victorian robot made of polished copper. Derek did a great job designing it, from the proportions of the limbs to the shape of the face; Ana thinks Jax is adorable. She likewise instantiates a selection of colored blocks with different shapes, and directs Jax’s attention to them.

  “See the blocks, Jax? What shape is the blue one?”

  “Tringle,” says Jax.

  “Good. What shape is the red one?”

  “Squir.”

  “Good. What shape is the green one?”

  “Circle.”

  “Good job, Jax.” Ana gives him a food pellet, which he devours with enthusiasm.

  “Jax smirt,” says Jax.

  “Lolly smirt too,” Lolly volunteers.

  Ana smiles and rubs them on the backs of their heads. “Yes, you’re both very smart.”

  “Both smirt,” says Jax.

  “That’s what I like to see,” says Mahesh.

  The release candidates are the final distillation of countless trials, the cream of the crop in terms of teachability. It’s partly been a search for intelligence, but just as much it’s been a search for temperament, the personality that won’t frustrate customers. One element of that is the ability to play well with others. The development team has tried to reduce hierarchical behavior in the digients–Blue Gamma wants to sell a pet that owners won’t need to continually reassert their dominance over–but that doesn’t mean competition never arises. The digients love attention, and if one notices that Ana’s giving praise to another, it tries to get in on the action. Most of the time this is fine, but whenever a digient seemed particularly resentful of its peers or of Ana, she would flag it and its specific genome would be excluded from the next generation. The process has felt a bit like breeding dogs, but more like working in an enormous test kitchen, baking endless batches of brownies and sampling each one’s toothsomeness to find the perfect recipe.