What was she hiding? Or rather, what was it that made him think she was hiding something? Dan wondered, listening to Olympia talk to his boss. He’d seen it before: some professor discovers a protein fold, or useful fractal pattern
or some other philosopher’s stone able to turn academic research into dollars and—Voila!—another startup is born.
Before the meeting, IiM, InformationInMotion, the company Dan worked,for, had GoogleSeurated her profile, of course: she didn’t do FB2—and only checked JoinApp to avoid flash mobs. But that didn’t necessarily mean she was a loner. FB2 had been bleeding users for years. Not that it mattered: every time she updated any app, they would have downloaded her complete cloud—just as the 75-page privacy notice she probably never read said they would. Facial recognition tagged her galaxy of weddings and birthdays and vacation photos—and the man who used to be in all of her photos until he began showing up in the photos of another woman, posed with a different set of kids. Her toothbrush reported that it switched on twice a day (6 a.m. and 10 p.m.) and stayed on for an average of 2.3 minutes. Your Privacy Is Our Business. (It really is!)
Just as her Fitbit used patterns of wrist movement to determine whether she was on an elevator, sleeping, eating, or driving over the speed limit, IiM extracted patterns from data traces to generate a portrait of her for its sales team: an ex-husband back in California, with her son (whose own FB account had tons of info on her). An annual spike in beer, hummus, and paper napkins indicated that she entertained her grad students once each year (the number of beers she bought having a high correlation with the number of grad students enrolled in her Lab Practices course, and indeed, the locations obtained from their phones showed that they converged at her house once a year), as though her annual party was an obligation, like going to the dentist (which she did twice a year).
The raw data from her car was so regular that its patterns could have been mistaken for those of a rat in a maze (she didn’t like cruise control), though there was something going on with her Thursdays. Every third or fourth Thursday she deviated from her commute by driving to a different high-end restaurant in the Tech Corridor outside the city. But her charge-card history indicated that she never paid for dinner. She started taking these trips about the time that the word cloud they extracted from her email began to change: for the previous 5 years her N-grams had been dominated by work vocabulary—’parasite’ ‘protein’ and ‘DNA’—except for that period when she first moved to Chicago. Emails to her (then) husband bumped up the use of words like ‘miss’ and ‘you’ to 19.7% but took on a slope of -3 as the usage of ‘apart’ increased. It flat-lined after ‘seeing someone else’ appeared. It was also during this time that her movie-watching history skewed toward chick flicks before dropping back to its annual average: 0.67 (what kind of person didn’t like movies?). She began using the gym in her condo with the regularity of a boxer. And her Google searches became even more work intense.
Over time, a picture emerged from all the patterns she generated the way the rings in a tree could tell a story of weather. Or so claimed profilers. But anyone who wrote algorithms knew that Big D portraits could be so much phrenology: determining moral qualities by reading the bumps in her Cloud. Meeting her in the flesh, Dan could see that there was something secret in her life that the data didn’t show. Or so he liked to imagine. Maybe because of her glasses—clear frames with racy green pinstripes that whispered something not in her profile. Or at least the desire for it. Each time she leaned forward to point out something about bird lice, her lab coat stretched and he couldn’t help notice a black strap though the report said she stayed squarely within the quintile that favored beige (SD-1 on the world map of Lingerie Use).
Back in the ’80s, she was saying, explaining the background to the project she wanted to bring IiM in on, a biologist in the last remnants of the Paraguayan rainforest noticed what indigenous people had known for centuries: that natives who hunted birds had some immunity to bird-borne diseases. The natives attributed it to the spirit of the birds themselves, but her guess was that it was the lice on the birds, not the birds, that gave the hunters immunity.
Instead of following up on her speculation, the biologist went down a research dead end about dinosaur feathers and lice. Olympia smiled wistfully. “The entomological community can be so competitive,” she said, “because the stakes are so small.
“Sorry, it’s an old entomology joke,” she muttered, apologizing for the pun—which was Dan’s Boss’s cue to laugh—louder than the joke was funny—and nodding for Dan to join in. Thinning hair, portly build. His boss was obviously uncomfortable, stuffed into his business suit, more used to loungeseats than the lab stools Olympia had offered them. Pants too short, his shins showed above the top of his socks.
“But there’s evidence that her hunch was right,” Olympia continued, “So that’s the first of our goals: to find out which protein in bird louse saliva gives mammals some protection, if in fact that’s what’s happening. Our long-range hope is that this knowledge can be used to make a vaccine.”
“A vaccine for birds or people?” Dan’s boss asked, taking notes.
“Both,” Olympia said. The answer just came out. But the moment it did, she acted as though she wished she could take it back. She stammered, “Eventually, I mean. There may be agricultural applications down the road but right now my lab is looking at antibodies in humans since that’s the mandate given us by our funder.”
By which she meant the military, Dan knew.
“But of course that’s proprietary information,” she said. Don’t ask, don’t tell. She breezed by the moment by going into some of the determinations they’d have to make, the first being the amount of genetic variability between different bird lice populations.
She pulled her chair closer to Dan and pulled up a sleeve of her lab coat, motioning for Dan to lend her his arm. “I’m a woman; you’re a man,” she said, pushing the sleeve of his suit up high enough to expose his forearm. Dan noticed his Boss frown at his tattoo, an NGer tattoo of the Red Marble Earth that he always kept covered at work. She laid her arm next to his on the desk. “Your hair is coarser than mine,” she said, demonstrating. Had she noticed him looking at her and decided to yank his chain? “Within the human species, there’s a lot of genetic variability. Same with lice: the geese in Venezuela may eat prairie grass, while geese in Bolivia might feed primarily on clover, or even bread thrown to them in urban areas. Their lice will be the same species, but their genetic makeup will have drifted in respect to one another. How much difference is there in their saliva?” She pulled his sleeve back down briskly, as though she’d just finished giving a demonstration on a CPR dummy. “To determine this, we’ll first sequence the genome of the lice from the same species of birds native to different areas.
“Hopefully we’ll find at least one protein that is conserved across species. That would make it possible to develop a one-drug-fits-all vaccine, instead of a different vaccine for each type of louse.”
“This is all familiar to us,” Dan’s Boss said, unrolling his Flexscreen on her desk. As he did, the company’s demo began to play: Introducing InfoInMotion…. The demo went through past projects they had completed: city planners tracing fire extinguisher registrations to predict where future fire trucks would have to be sent; another forecast the resources that a hospital would need to treat schizophrenia in twenty years by correlating the number of cats at the Humane Society to the number of playgrounds (cats in shelters correlate highly to cats in neighborhoods; cats in neighborhoods use sandboxes in playgrounds; cat feces in sandboxes carry the T. gondii parasite; kids exposed to T. gondii develop schizophrenia in adulthood)…. In one project for the CDC, IiM had layered data harvested from the cell phones of travelers to show that the Honolulu Airport, with its connections between the U.S. and Asia, would be the world’s largest hub for the next pandemic.
He told her about some of the other projects they worked on for Big Pharma where biology and information had been synonymous for years, then finished by saying, as if it were no big deal, “Basically, you want us to come up with a new Tree of Life.”
“Just for bird lice,” she said flatly, a poker face. “Only it has to be dynamic, changing as the biochemistry of the lice changes.”
“Uh yeah, we can do that,” Boss said, less sure, turning for confirmation to Dan, the guy who would actually have to supervise the work.
The both of them were looking at him.
In his mind he saw an evolutionary tree, but instead of the static drawings in textbooks, its branches slowly swayed as seaweed undulates in a tide, some strands flourishing, others dying out, all in real time. “Cool,” he murmured.
“InfoInMotion doesn’t do static, do we?” his Boss chuckled. Dan could tell that the chuckle was meant to paper over his use of ‘cool.’ He’d hear about it later. About ‘cool,’ his tight jeans, his tattoo.
Dan didn’t know the ins and outs of the contract between IiM and the venture capitalists paying for everything, but he’d bet it involved the use of the cheap stuff—the 1,000 terabytes of census reports, NASA climate data, and all the rest of the 90,000 government databases that are always available gratis; they’d probably link those to databases that the company had amassed on its own in order to magnify their usefulness—the way Google first married a free phone book to a free map, multiplying the power of each, which they then raised to an exponent through software that merged this database with street-level photos, then IP addresses and text messages gathered by trucks taking those street-level photos. It was all multiplied yet again when merged with terabytes of corporate data on everyone who lived at those addresses—the cameras in their laptops tracking their eyes as they skipped over captions (0.2/ s/caption avg.); how far people traveled to work, happy hour, or church; whether they walked, drove, or rode a pogo stick; who paid for gas at the pump and who paid inside, and so bought cigarettes, and so were higher insurance risks; who, in 5 years, could be sold a yacht.... Terabytes of data gathered for each and every person—or rather, each of these 6.2 billion data nodes, as IiM called them.
Life Is Data, as the promos said…. Basically, that’s what Darwin did: look at masses of data points, i.e., the shapes of snails, to discern a pattern, which he called Evolution.
But this was teaching the software to teach itself to recognize patterns in snails as they morph into other mollusks, the dynamics of open systems—’live prediction’—like mapping networks of rivets and welds and icebergs and ocean currents, then using it to see the Titanic sink before it pulled away from the pier. From spikes in phone-card purchases, the software was able to predict outbreaks of genocide among the Bottom Billion, its refugees converting their chickens and goats into phone cards, a form of money for those on the run. Guns, counterfeit watches, slaves, laundered money, refugees—anything in flux—background radiation, city growth, or the night sky—all reality could be seen as flux in patterns, smaller patterns coalescing as larger patterns, that formed still larger patterns….
Workaholic, is how the software labeled her personality cluster.
Dan’s Boss chuckled. “Kind of ironic, how a footnote about dinosaur lice could end up saving millions of people.”
Olympia just sat there with that tight little smile of hers.
Military funding.
Or kill them, Dan wanted to say, a vaccine for one side being a gun pointed to the head of the other. What was it like, he wondered, to walk around in skin that tight?