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"[...] I also asked that they teach him Spanish."
"Spanish?"
"In case we ever want to bring him back. We really need a more diverse workforce."
Bobby was always one step ahead.
actually pretty funny but would be so much funnier without the last line which just hits you over the head
"So if we divert them to Poodlekek, that town in the Philippines dies," Bobby said.
"Well, it's more like that town doesn't get computers for its schools."
"That town dies," Bobby said. "So, the question is: Is an Anahata engineer's life worth more than thousands of Filipinos?"
the dramatic repetition is pretty funny. really chimes with the character
"Gregor, didn't we discuss you building an army just a few weeks ago?"
"It will take some time," Gregor said. "And as I understood it, it was an army of engineering evangelists you were asking for, not an army of real soldiers."
"Clearly our army should be multipurpose," Bobby said. [...]
bobby gets the best lines
Finally, in the darkest hours of the morning, taurine and glucose dripping from their pores, they reached the last, dramatic step. The team typed in the final line of code. The cursor blinked back at them, pulsing like an explosive light. They turned to Gregor, who gave them the nod. The team lead put his index finger atop a single "enter" key, closed his eyes, and on the count of three, pushed.
??????????????
The challenge of the “knowledge problem” is just one example of a general truth: What we do and don’t know about the social (as opposed to the natural) world is not inherent in its nature, but is itself a function of social constructs. Much of what we can find out about companies, governments, or even one another, is governed by law. Laws of privacy, trade secrecy, the so-called Freedom of Information Act— all set limits to inquiry. They rule certain investigations out of the question before they can even begin. We need to ask: To whose benefit?
More benignly, perhaps, these companies influence the choices we make ourselves. Recommendation engines at Amazon and YouTube affect an automated familiarity, gently suggesting offerings they think we’ll like. But don’t discount the significance of that “perhaps.” The economic, political, and cultural agendas behind their suggestions are hard to unravel. As middlemen, they specialize in shifting alliances, sometimes advancing the interests of customers, sometimes suppliers: all to orchestrate an online world that maximizes their own profits.
So why does this all matter? It matters because authority is increasingly expressed algorithmically. Decisions that used to be based on human reflection are now made automatically. [...]
[...] In their race for the most profitable methods of mapping social reality, the data scientists of Silicon Valley and Wall Street tend to treat recommendations as purely technical problems. The values and prerogatives that the encoded rules enact are hidden within black boxes.
[...] Companies were gathering millions of records from pharmacies. They then sold them on to insurers eager to gain a competitive advantage by avoiding people likely to incur high medical fees. Since 1 percent of patients account for over one-fifth of health care costs, and 5 percent account for nearly half of costs, insurers who can “cherry-pick” the healthy and “lemon-drop” the sick will see far more profit than those who take all comers. Prescription data gave insurers the information they needed to tailor policies to exclude preexisting conditions and to impose higher charges for some members.
in other news, for-profit healthcare is a giant scam=
[...] Marketers plot to tout beauty products at moments of the day that women feel least attractive. There’s little to stop them from compiling digital dossiers of the vulnerabilities of each of us. In the hall of mirrors of online marketing, discrimination can easily masquerade as innovation.
using data to overcome more of our natural defenses against advertising
[...] Runaway data can lead to cascading disadvantages as digital alchemy creates new analog realities. Once one piece of software has inferred that a person is a bad credit risk, a shirking worker, or a marginal consumer, that attribute may appear with decision-making clout in other systems all over the economy. [...]