October, 2017 | Chris Aldrich

📗 Started reading Weapons of Math Destruction by Cathy O’Neil

📖 Read introduction of Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy by Cathy O’Neil

Based on the opening, I’m expecting some great examples many which are going to be as heavily biased as things like redlining seen in lending practices in the last century. They’ll come about as the result of missing data, missing assumptions, and even incorrect assumptions.

I’m aware that one of the biggest problems in so-called Big Data is that one needs to spend an inordinate amount of time cleaning up the data (often by hand) to get something even remotely usable. Even with this done I’ve heard about people not testing out their data and then relying on the results only to later find ridiculous error rates (sometimes over 100%!)

Of course there is some space here for the intelligent mathematician, scientist, or quant to create alternate models to take advantage of overlays in such areas, and particularly markets. By overlay here, I mean the gambling definition of the word in which the odds of a particular wager are higher than they should be, thus tending to favor an individual player (who typically has more knowledge or information about the game) rather than the house, which usually relies on a statistically biased game or by taking a rake off of the top of a parimutuel financial structure, or the bulk of other players who aren’t aware of the inequity. The mathematical models based on big data (aka Weapons of Math Destruction or WMDs) described here, particularly in financial markets, are going to often create such large inequities that users of alternate means can take tremendous advantage of the differences for their own benefits. Perhaps it’s the evolutionary competition that will more actively drive these differences to zero? If this is the case, it’s likely that it’s going to be a long time before they equilibrate based on current usage, especially when these algorithms are so opaque.

I suspect that some of this book will highlight uses of statistical errors and logical fallacies like cherry picking data, but which are hidden behind much more opaque mathematical algorithms thereby making them even harder to detect than simple policy decisions which use the simpler form. It’s this type of opacity that has caused major market shifts like the 2008 economic crash, which is still heavily unregulated to protect the masses.

I suspect that folks within Bryan Alexander’s book club will find that the example of Sarah Wysocki to be very compelling and damning evidence of how these big data algorithms work (or don’t work, as the case may be.) In this particular example, there are so many signals which are not only difficult to measure, if at all, that the thing they’re attempting to measure is so swamped with noise as to be unusable. Equally interesting, but not presented here, would be the alternate case of someone tremendously incompetent (perhaps who is cheating as indicated in the example) who actually scored tremendously high on the scale who was kept in their job.

Highlights, Quotes, & Marginalia

Introduction

Do you see the paradox? An algorithm processes a slew of statistics and comes up with a probability that a certain person might be a bad hire, a risky borrower, a terrorist, or a miserable teacher. That probability is distilled into a score, which can turn someone’s life upside down. And yet when the person fights back, “suggestive” countervailing evidence simply won’t cut it. The case must be ironclad. The human victims of WMDs, we’ll see time and again, are held to a far higher standard of evidence than the algorithms themselves.

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Added on Sunday, October 9, 2017

[WMDs are] opaque, unquestioned, and unaccountable, and they operate at a scale to sort, target or “optimize” millions of people. By confusing their findings with on-the-ground reality, most of them create pernicious WMD feedback loops.

Highlight (yellow) – Introduction > Location xxxx
Added on Sunday, October 9, 2017

The software is doing it’s job. The trouble is that profits end up serving as a stand-in, or proxy, for truth. We’ll see this dangerous confusion crop up again and again.

Highlight (yellow) – Introduction > Location xxxx
Added on Sunday, October 9, 2017

I’m reading this as part of Bryan Alexander’s online book club.

🎧 Antibiotics and agriculture | Eat This Podcast

Listened to Antibiotics and agriculture by Jeremy Cherfas from Eat This Podcast

Tackling the problem of antibiotic resistance at (one) source In the past year or so there has been a slew of high-level meetings pointing to antibiotic resistance as a growing threat to human well-being. But then, resistance was always an inevitable, Darwinian consequence of antibiotic use. Well before penicillin was widely available, Ernst Chain, who went on to win a Nobel Prize for his work on penicillin, noted that some bacteria were capable of neutralising the antibiotic. What is new about the recent pronouncements and decisions is that the use of antibiotics in agriculture is being recognised, somewhat belatedly, as a major source of resistance. Antibiotic manufacturers and the animal health industry have, since the start, done everything they can to deny that. Indeed, the history of efforts to regulate the use of antibiotics in agriculture reveals a pretty sordid approach to public health. But while it can be hard to prove the connection between agriculture and a specific case of antibiotic resistance, a look at hundreds of recent academic studies showed that almost three quarters of them did demonstrate a conclusive link. Antibiotic resistance – whether it originates with agriculture or inappropriate medical use – takes us back almost 100 years, when infectious diseases we now consider trivial could, and did, kill. It reduces the effectiveness of other procedures too, such as surgery and chemotherapy, by making it more likely that a subsequent infection will wreck the patient’s prospects. So it imposes huge costs on society as a whole. Maybe society as a whole needs to tackle the problem. The Oxford Martin School, which supports a portfolio of highly interdisciplinary research groups at Oxford University, has a Programme on Collective Responsibility for Infectious Disease. They recently published a paper proposing a tax on animal products produced with antibiotics. Could that possibly work?

Here’s another great example of a negative externality. Too often capitalism brushes over these and creates a larger longer term cost by not taking these into account. It’s almost assuredly the case that taxing the use of these types of antibiotics across the broadest base of users (eaters) (thereby minimizing the overall marginal cost), would help to minimize the use of these or at least we’d have the funding for improving the base issue in the future. In some sense, the additional cost of eating organic meat is similar to this type of “tax”, but the money is allocated in a different way.

Not covered here are some of the economic problems of developing future antibiotics when our current ones have ceased to function as the result of increased resistance over time. This additional problem is an even bigger worry for the longer term. In some sense, it’s all akin to the cost of smoking and second hand smoke–the present day marginal cost to the smoker of cigarettes and taxes is idiotically low in comparison to the massive future cost of their overall health as well as that of the society surrounding them. Better to put that cost upfront for those who really prefer to smoke so that the actual externalities are taken into account from the start.

This excellent story reminds me of a great series of stories that PBS NewsHour did on the general topic earlier this year.

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👓 Matt Damon, Russell Crowe Reportedly Helped Kill a 2004 Harvey Weinstein Article | Vulture

Read Ex-NYT Reporter Claims Weinstein Asked Damon to Help Kill 2004 Story; NYT Denies (Vulture)

The Wrap editor Sharon Waxman trades accusations with top Times editors, says Weinstein pressured celebrity friends to help kill the story.

👓 Half the universe’s missing matter has just been finally found | New Scientist

Read Half the universe’s missing matter has just been finally found by Leah Crane (New Scientist)

About half the normal matter in our universe had never been observed – until now. Two teams have finally seen it by combining millions of faint images into one