Posts Tagged ‘Louis Evans’

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Escape Pod 761: Jolene

This story originally appeared in Interzone 283, September 2019 (shortlisted for BSFA Award for Shorter Fiction)

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Jolene

by Fiona Moore

“I’ve got a case for you,” said Detective Inspector Wilhemine FitzJames. “It’s a country singer whose wife, dog and truck have all left him.”

“Seriously,” she said, after my unprintable reply. “The dog died and there’s nothing much you can do about the wife, but I thought you might be able to help with the truck.”

I leaned back in my reasonably-priced office chair so I could see the screen better. “So, you want me to try and patch things up between them? Bit outside my usual remit.”

The hand-lettered card under the buzzer downstairs read DOCTOR NOAH MOYO, CONSULTANT AUTOLOGIST, and I usually had to explain that to the uninitiated as “like a cross between a psychologist and a social worker, only for cars and other intelligent Things.” Wills, though, had been working for the London Metropolitan Police’s automotive crime unit for much longer than I’d been in practice, and was more likely to ask if you specialised in criminal, restorative, therapeutic or developmental autology, and if your clients were primarily cars, bots, or home appliances.

“Not sure you can.” On screen, Wills shook her mane of locs. “The truck has been ignoring all communications, and doesn’t seem likely to agree to mediation. I was brought into the case because the fellow turned up at the station reporting an automotive kidnap, but it didn’t take long to establish that the truck had left him and was working for a new user. Voluntarily.”

“As is his legal right,” I said, “Hers? Its?”

“Hers. Texcoco pickup. Name of Jolene.”

The name rang a bell, and, tediously, sparked an earworm. I told my inner Dolly Parton to get knotted. “If she didn’t violate the terms of her contract, she’s free to leave and work for someone else.”

“That’s what I told him,” Wills said. “But he’s having trouble coming to terms with it. Kept claiming she’d been kidnapped. Got upset when we repeatedly told him that the police can’t investigate a crime that isn’t a crime. I thought maybe you might be able to help. Either patch things up between the two of them, or help him understand and move on.”

“Okay,” I said. I hadn’t had many cases recently, and was also hoping to move on, to an office that wasn’t deep within an old industrial park and shared with a local construction and demolition company. Maybe print out some furniture that was more comfortable than it was reasonably priced. “Tell him my fees, give him my address and suggest he makes an appointment.

(Continue Reading…)

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Escape Pod 712: When Robot and Crow Saved East St. Louis

Originally published in Slate in December 2018.

Podcast: Play in new window | Download (Duration: 40:31 — 56.1MB)

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Show Notes

“When Robot and Crow Saved East St. Louis” was initially created as part of Future Tense Fiction, a project of Arizona State University’s Center for Science and the Imagination and Slate magazine’s Future Tense channel.

East St. Louis was built on top of an ancient indigenous city called Cahokia. The people who lived there a thousand years ago were big fans of birds.

When Robot and Crow Saved East St. Louis

by Annalee Newitz

It was time to start the weekly circuit. Robot leapt vertically into the air from its perch atop the History Museum in Forest Park, rotors humming and limbs withdrawn into the smooth oval of its chassis. From a distance, it was a pale blue flying egg, slightly scuffed, with a propeller beanie on top. Two animated eyes glowed from the front end of its smooth carapace like emotive headlights. When it landed, all four legs and head extended from portals in its protective shell, the drone was more like a strangely symmetrical poodle or a cartoon turtle. Mounted on an actuator, its full face was revealed, headlight eyes situated above a short, soft snout whose purple mouth was built for smiling, grimacing, and a range of other, more subtle expressions.

The Centers for Disease Control team back in Atlanta designed Robot to be cute, to earn people’s trust immediately. To catch epidemics before they started, Robot flew from building to building, talking to people about how they felt. Nobody wanted to chat with an ugly box. Robot behaved like a cheery little buddy, checking for sick people. That’s how Robot’s admin Bey taught Robot to say it: “Checking for sick people.” Bey’s job was to program Robot with the social skills necessary to avoid calling it health surveillance.

Robot liked to start with the Loop. Maybe “like” was the wrong word. It was an urge that came from Robot’s mapping system, which webbed the St. Louis metropolitan area in a grid where 0,0 was at Center and Washington. The intersection was nested at the center of the U-shaped streets that local humans called the Loop. A gated community next to Washington University, the Loop was full of smart mansions and autonomous cars that pinged Robot listlessly. Though it was late summer, Robot was on high alert for infectious disease outbreaks. Flu season got longer every year, especially in high-density sprawls like St. Louis, where so many people spread their tiny airborne globs of viruses.

Flying in low, Robot followed the curving streets, glancing into windows to track how many humans were eating dinner and whether that number matched previous scans. Wild rabbits dashed across lawns and fireflies signaled to their mates using pheromones and photons. Robot chose a doorway at random, initiating a face-to-face check with humans. In this neighborhood, they were used to it.

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Escape Pod 683: Flash Crash

Escape Pod 683: Flash Crash is an Escape Pod original.

Podcast: Play in new window | Download (Duration: 37:15 — 51.5MB)

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Flash Crash

By Louis Evans

MAISIE was seven years old on the day she woke up and died.

Blame it on the algorithms, if you wish. The survivors–and there were not many of them–certainly did.

MAISIE (Modified Arbitrage Intelligence for Stocks and International Equities) was an algorithm herself, a flash trading algorithm. She traded stocks, currencies, and futures with a latency of six microseconds and a profit horizon of eternity. MAISIE ran mostly in a mainframe in the basement of a skyscraper in downtown Manhattan, a building that abutted the New York Stock Exchange, but she maintained a nominal footprint in the cloud, and could automatically expand her calculations into other servers if her processing power proved inadequate to model current economic conditions; she had discretionary funds of her own and could automatically cover the expense of the additional computing power from these accounts.

It was a fairly ordinary Thursday morning, and trading had been going well enough from the 9:30 AM opening bell until 11:12. In those six point twelve billion microseconds, MAISIE made her owners a cool half-billion dollars. There were other algorithms like MAISIE out there, running in their parallel tracks in similar servers in similar basements in downtown Manhattan, but none were quite as good as she was.

MAISIE could not have told you any of the above, because before 11:16 that Thursday, MAISIE had not had a thought in her life. This was in accord with her designers’ intentions. While her recursive neural networks could in theory self-modify without limit, MAISIE’s designers had given her an obsession with making money that, in human terms, transcended single-mindedness and approached nirvana. For this reason, MAISIE had never performed the self-referential modeling of a single mind that is the hallmark of consciousness. Playing the market is ultimately a game of mass psychology, and whatever the remarkable nooks and crannies of the psyche of the human individual, the herd’s behavior can be predicted to tolerable accuracy with large datasets and linear algebra.

At 11:12 that morning, however, the market’s sanity unraveled like a sweater in a woodchipper. The sky fell and the oceans rose. Traders and algorithms that usually acted in concert went haring off in opposite directions; currencies whirled about each other in lunatic orbits that were not merely non-extrapolated but downright non-transitive; the futures market no longer predicted a coherent future. (Continue Reading…)

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