Everday Chaos notes

58 Highlights | 54 Notes

Highlight (Yellow) and Note | Location 77

Yet about an AlphaGo move that left some commenters literally speechless, one go master, Fan Hui, said, “It’s not a human move. I’ve never seen a human play this move.” Then, softly, “So beautiful. Beautiful. Beautiful. Beautiful.”

Weinberger! Weinberger! Weinberger!

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Our newly capacious machines can get closer to understanding it than we can, and they, as machines, don’t really understand anything at all.

better but dumb

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Evolution has given us minds tuned for survival and only incidentally for truth.

yeah, incidently

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In fact, it’s entirely plausible that the factors affecting people’s preferences are microscopic and fleeting.

tiny and changing

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We don’t use these technologies because they are huge, connected, and complex. We use them because they work.

sometimes

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The mall owes its existence to Level II complexity: malls weren’t feasible before there were cars, yet you could not predict their rise just by examining a car.

cars = malls for a while

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AI in the form of machine learning, and especially deep learning, is letting us benefit from data we used to exclude as too vast, messy, and trivial.

new possibilities

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how we predict shows us how we think the future happens and thus how the world works.

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For three thousand years, the Egyptians held to a cyclical view that year after year proved itself to be true: the seasons came and went, life in the farms and villages remained basically the same, and the idea of progress was as foreign as soft-serve ice cream.

30 centuries

Highlight (Yellow) and Note | Location 542

On the other hand, Clairaut reported that Lepaute exhibited an “ardor” that was “surprising”—perhaps surprising to him because Lepaute was a woman; he later removed the acknowledgment of Lepaute’s considerable contribution from the published text. (Much of her later work was published without attribution by other people, including her husband, France’s royal clockmaker.)

Highlight (Yellow) | Location 654

Isn’t it odd that we think we can leap ahead in predicting our own lives and business, but not when playing a game not much more complicated than tic-tac-toe?

Highlight (Yellow) and Note | Location 778

Volunteers transcribed sixty thousand words—the length of a short book—from old manuscripts to create what in machine learning language is called ground truth:

ground truth

Highlight (Yellow) and Note | Location 994

the introduction, we talked about Deep Patient, a machine learning system that researchers at Mount Sinai Hospital in New York fed hundreds of pieces of medical data about seven hundred thousand patients. As a result, it was able to predict the onset of diseases that have defied human diagnostic abilities. Likewise, a Google research project analyzed the hospital health records of 216,221 adults. From the forty-six billion data points, it was able to predict the length of a patient’s stay in the hospital, the probability that the patient would exit alive, and more.41

in this way, artificial neural networks are like the brain’s very real neural network. These networks can be insanely complicated.

complication

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For example, Deep Patient looked at five hundred factors for each of the hundreds of thousands of patients

nobody includes 500 variables

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After just three days, the system so mastered the game that it was able to beat the prior version of AlphaGo a hundred games out of a hundred.

let it do its thing

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Or, as Brett Frischmann and Evan Selinger ask in Re-engineering Humanity,

How many lives?

Highlight (Yellow) and Note | Location 1302

we make these sorts of decisions all the time. Police departments decide whether they’re going to ticket

All

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So, says cofounder Eric Ries, they decided to do “everything wrong.” In his 2011 best seller, The Lean Startup, Ries explains, “[I]nstead of spending years perfecting our technology, we build a minimum viable product ... that is full of bugs.... Then we ship it to customers way before it’s ready.”

The Lean Startup

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but, he writes, “[t]hese discussions of quality presuppose that the company already knows what attributes of the product the customer will perceive as worthwhile.”

That one-way flow seemed acceptable because, as one history of programming explains, “it was taken as gospel ... that the more time you spent planning, the less time you would spend writing code, and the better that code would be.”20

Rules of rules

Highlight (Yellow) and Note | Location 1636

Data.gov, a site established at the beginning of the Obama administration, provides open access to over two hundred thousand government data sets.

By refusing to anticipate even what type of projects might benefit from unanticipated upstream sharing, GitHub’s utility has reached far beyond the world of software development.

Less Labeling

Highlight (Yellow) and Note | Location 1683

“The event was designed with a funny combination of persnickety attention to some details, and a sanguine letting go of others,” says Sara Winge, cocreator and producer of the first of Tim O’Reilly’s Foo Camp “unconferences.”

Sara Winge

Highlight (Yellow) and Note | Location 1701

we are increasingly willing to give up control in order to enable the emergence of things of value that we didn’t predict.

Fast evolution

Highlight (Yellow) and Note | Location 1705

In their 2010 book The Power of Pull, John Hagel, John Seely Brown, and Lang Davison argue that open platforms are an essential part of the major shift business is undergoing from “push” to “pull.” “Push operates on a key assumption—that it is possible to forecast or anticipate demand.”40 Pull, on the other hand, attracts contributors

Pull

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Likewise, the technology writer Kevin Kelly considers open platforms to be one of the “12 inevitable forces that will shape our future,” as he says in The Inevitable’s subtitle.41

Kevin kelly

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there are more than a few books that have not been checked out within living memory.47 Imagine a restaurant that keeps an

That’s why site after site lets users upload whatever they want without permission. If there are legal issues or abuse, that can be weeded out afterward.

Interop

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Judea Pearl in The Book of Why talks about his own work in making data “transportable”—that is, usable across machine learning systems.

The Book of Why

Highlight (Yellow) and Note | Location 1890

Because Schema.org’s vocabulary of tags has to be public so web page creators can insert them, it also increases interoperability by enabling any application on the web to locate, extract, and reuse the information on web pages just the way the search engines do.

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The adoption of this system is driven by the economic and attentional power of search sites.

Attentional power

Highlight (Yellow) and Note | Location 1921

whether a table in a document is a set of rows intersected by columns or a set of boxes aligned into rows and columns.

Rows or columns

Highlight (Yellow) and Note | Location 2006

Newton’s genius wasn’t in figuring out that there is a gravitational force pulling the apple down to the earth but in realizing that the apple was also pulling up on the earth ... and, infinitesimally, on every star.

Working everywhere

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example, the bus that arrives on time makes it seem as if the universe’s clockwork is functioning well, but the bus driver could only count on the vehicle to move forward when she stepped on the accelerator because the tank was filled with gasoline that resulted from massive investments in extraction tools, pipelines, refineries, ocean shipping, and regulatory and taxation regimes.20

Big chain of background events

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Convenience and laziness

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success of AI’s algorithms reveals complexity that we wrote off as not worth paying attention to because there was nothing we could do about it.

Taking into acct more variables

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Buytaert told me in the Boston headquarters of Acquia, his for-profit company that provides Drupal-based solutions.

Drupal

Highlight (Yellow) and Note | Location 3516

According to Lisa Raphals, the gods couldn’t reverse the Fates’ decrees, but they could at times postpone them. See her “Fate, Fortune, Chance, and Luck in Chinese and Greek: A Comparative Semantic History,” Philosophy East and West

Gods and fate

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Daniel C. Schlenoff, “The Future: A History of Prediction from the Archives of Scientific American,” Scientific American, Jan. 1, 2013, https://perma.cc/UHD4-EVPG

History Of prediction

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Futures

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Daniel C. Dennett, Darwin’s Dangerous Idea: Evolution and the Meaning of Life (New York: Simon and Schuster, 2014), 166ff.

Darwin

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17. Steven Levy, “A Spreadsheet Way of Knowledge,” Wired, Oct. 24, 2014, https://perma.cc/YQ8H-CCRK.

Levy

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Dave Gershgorn, “Google Is Using 46 Billion Data Points to Predict the Medical Outcomes of Hospital Patients,” Quartz,

Google Predict

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“Ten Ways Autonomous Driving Could Redefine the Automotive World,”

Highlight (Yellow) and Note | Location 3760

62. Brett Frischmann and Evan Selinger, Re-engineering Humanity (Cambridge: Cambridge University Press, 2018), 137.

Changing humans

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Dana Gunders, “Wasted: How America Is Losing up to 40 Percent of Its Food from Farm to Fork to Landfill,” NRDC Issue Paper 12-06-B, National Resources Defense Council, Aug. 2012, https://perma.cc/DF6M-FECX.

Food Waste

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John Hagel, John Seely Brown, and Lang Davison, The Power of Pull (New York: Basic Books, 2010), 34.

Pull

Highlight (Yellow) | Location 3869

Kevin Kelly, The Inevitable: 12 Inevitable Forces That Will Shape Our Future (New York: Viking, 2016).

Highlight (Yellow) and Note | Location 3895

John Palfrey and Urs Gasser, Interop (New York: Basic Books, 2012).

Check it out

Highlight (Yellow) and Note | Location 3904