👓 ‘A Sort of Everyday Struggle’ | The Harvard Crimson

'A Sort of Everyday Struggle' by Hannah Natanson
Women in Harvard's math department report a bevy of inequalities—from a discouraging absence of female faculty to a culture of "math bro" condescension.

A story about math that sadly doesn’t feature equality.

Oddly not featured in the story was any reference to the Lawrence H. Summers incident of 2005. Naturally, one can’t pin the issue on him as this lack of diversity has spanned the life of the university, but apparently the math department didn’t get the memo when the university president left.

I’ve often heard that the fish stinks from the head, but apparently it’s the whole fish here.

Syndicated copies to:

👓 Filing errors knock rent control in Glendale out of consideration — for now | Glendale News-Press

Filing errors knock rent control in Glendale out of consideration — for now by Jeff Landa (Glendale News-Press)
The petition hit an administrative setback.
Syndicated copies to:

👓 Trump offered a grieving military father $25,000 in a call, but didn’t follow through | Washington Post

Trump offered a grieving military father $25,000 in a call, but didn’t follow through by Dan Lamothe, Lindsey Bever and Eli Rosenberg (Washington Post)
‘No other president has ever done something like this,’ Trump told the late soldier’s father.

It kills me that he’s so unfeeling, unkind, and generally has no empathy. The fact that he hasn’t caught on that people are going to fact check him and make him continually look like an even bigger looser is even more painful. The disrespect to our troops just becomes the icing on the cake. His actions really just hurt my brain because they just make no sense within the framework of humanity.

Syndicated copies to:

👓 Here’s a hack so you can tweet with 280 characters right now | The Verge

How to tweet with 280 characters right now by Tom Warren (The Verge)
Twitter doubled the character limit of tweets to 280 in a surprise move yesterday, but not every Twitter user will be able to use the new limit just yet. Twitter is rolling out the long tweets feature to select accounts as a test, but Twitter user Prof9 has discovered a workaround to get longer tweets a little early. Here’s how to tweet with 280 characters instead of 140: Download Tampermonkey for your browser of choice (Chrome webstore link) Visit this Github repository, click the “raw” button, then tell tampermonkey to “install” the script (or copy and paste the code into a new script in Tampermonkey) Now visit twitter.com, make sure the script in running in Tampermonkey, then tweet away It’s a simple workaround that will work automatically on Twitter.com every time you use the web client to tweet. Tampermonkey is a widely used userscript manager, and the javascript is a harmless workaround that simply bypasses the tweet button limit. Twitter is slowly testing its 280 character tweet limits with a variety of accounts, so if you don’t want to install Tampermonkey then you might get randomly selected for the test in the coming weeks or months.

Sadly Twitter has figured out the work around and disabled it so it doesn’t work anymore. Fortunately I can always write on my own site without character limits.

Syndicated copies to:

👓 Another USC medical school dean resigns | Washington Post

Another USC medical school dean resigns by Susan Svrluga (Washington Post)
The University of Southern California announced Thursday that Rohit Varma has resigned as dean of the Keck School of Medicine. He had replaced a dean who was banned from campus after allegations of drug use and partying.

I’ve been so busy in the last month, I had to do a double-take at the word ANOTHER!

The statement USC released seems highly disingenuous and inconsistent to me.

“As you may have heard, today Dr. Rohit Varma resigned as dean of the Keck School of Medicine of USC,” the school’s provost, Michael Quick, wrote in a message to the community.

“I understand how upsetting this situation is to all of us, but we felt it was in the best interest of the faculty, staff, and students for all of us to move in this direction. Today we learned previously undisclosed information that caused us to lose confidence in Dr. Varma’s ability to lead the school. Our leaders must be held to the highest standards. Dr. Varma understands this, and chose to step down.”

First they say Varma resigned as dean which makes it seem as if he’s stepping aside of his own accord when the next paragraph indicates that the University leadership has lost confidence in him and forced him out. So which is it? He resigned or was fired?

Secondly they mentioned “undisclosed information”. This is painful because the so-called undisclosed information was something that USC was not only aware of, but actually paid off a person involved to the tune of more than $100,000!

USC paid her more than $100,000 and temporarily blocked Varma from becoming a full member of the faculty, according to the records and interviews.

“The behavior you exhibited is inappropriate and unacceptable in the workplace, reflects poor judgment, is contrary to the University’s standards of conduct, and will not be tolerated at the University of Southern California,” a USC official wrote in a 2003 letter of reprimand.”

Even the LA Times reports: “The sexual harassment allegation is well known in the upper echelons of the university, but not among many of the students and staff.” How exactly was this “undisclosed?!”

So, somehow, a person who was formally reprimanded years ago (and whose reprimands were later greatly lessened by the way) was somehow accidentally promoted to dean of an already embattled division of the university?? I’m not really sure how he even maintained his position after the original incident much less subsequently promoted and allowed to continue on to eventually be appointed dean years later. Most shocking, there was no mention of his other positions at USC. I take this to mean that he’s still on the faculty, he’s still on staff at the hospital, and he’s still got all the rights and benefits of his previous positions at the University? I sincerely hope that he learned his lesson in 2003, but suspect that he didn’t, and if this is the case and others come forward, he will be summarily dispatched. For the University’s sake, I further hope they’re looking into it internally with a fine-toothed comb before they’re outed again by the Los Angeles Times reporting staff who seem to have a far higher level of morality than the USC leadership over the past several years.

During a month which has seen an inordinate amount of sexual harassment backlash, I’m shocked that USC has done so very little and has only acted (far too long after-the-fact) to sweep this all under the rug.

Syndicated copies to:

📖 Read chapter one of Weapons of Math Destruction by Cathy O’Neil

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

I don’t think she’s used the specific words in the book yet, but O’Neil is fundamentally writing about social justice and transparency. To a great extent both governments and increasingly large corporations are using these Weapons of Math Destruction inappropriately. Often it may be the case that the algorithms are so opaque as to be incomprehensible by their creators/users, but, as I suspect in many cases, they’re being used to actively create social injustice by benefiting some classes and decimating others. The evolving case of Facebook’s involvement in potentially shifting the outcome of the 2016 Presidential election especially via “dark posts” is an interesting case in point with regard to these examples.

In some sense these algorithms are like viruses running rampant in a large population without the availability of antibiotics to tamp down or modify their effects. Without feedback mechanisms and the ability to see what is going on as it happens the scale issue she touches on can quickly cause even greater harm over short periods of time.

I like that one of the first examples she uses for modeling is that of preparing food for a family. It’s simple, accessible, and generic enough that the majority of people can relate directly to it. It has lots of transparency (even more than her sabermetrics example from baseball). Sadly, however, there is a large swath of the American population that is poor, uneducated, and living in horrific food deserts that they may not grasp the subtleties of even this simple model. As I was reading, it occurred to me that there is a reasonable political football that gets pushed around from time to time in many countries that relates to food and food subsidies. In the United States it’s known as the Supplemental Nutrition Assistance Program (aka SNAP) and it’s regularly changing, though fortunately for many it has some nutritionists who help to provide a feedback mechanism for it. I suspect it would make a great example of the type of Weapon of Mass Destruction she’s discussing in this book. Those who are interested in a quick overview of it and some of the consequences can find a short audio introduction to it via the Eat This Podcast episode How much does a nutritious diet cost? Depends what you mean by “nutritious” or Crime and nourishment Some costs and consequences of the Supplemental Nutrition Assistance Program which discusses an interesting crime related sub-consequence of something as simple as when SNAP benefits are distributed.

I suspect that O’Neil won’t go as far as to bring religion into her thesis, so I’ll do it for her, but I’ll do so from a more general moral philosophical standpoint which underpins much of the Judeo-Christian heritage so prevalent in our society. One of my pet peeves of moralizing (often Republican) conservatives (who often both wear their religion on their sleeves as well as beat others with it–here’s a good recent case in point) is that they never seem to follow the Golden Rule which is stated in multiple ways in the Bible including:

He will reply, ‘Truly I tell you, whatever you did not do for one of the least of these, you did not do for me.

Matthew 25:45

In a country that (says it) values meritocracy, much of the establishment doesn’t seem to put much, if any value, into these basic principles as they would like to indicate that they do.

I’ve previously highlighted the application of mathematical game theory before briefly in relation to the Golden Rule, but from a meritocracy perspective, why can’t it operate at all levels? By this I’ll make tangential reference to Cesar Hidalgo‘s thesis in his book Why Information Grows in which he looks not at just individuals (person-bytes), but larger structures like firms/companies (firmbytes), governments, and even nations. Why can’t these larger structures have their own meritocracy? When America “competes” against other countries, why shouldn’t it be doing so in a meritocracy of nations? To do this requires that we as individuals (as well as corporations, city, state, and even national governments) need to help each other out to do what we can’t do alone. One often hears the aphorism that “a chain is only as strong as it’s weakest link”, why then would we actively go out of our way to create weak links within our own society, particularly as many in government decry the cultures and actions of other nations which we view as trying to defeat us? To me the statistical mechanics of the situation require that we help each other to advance the status quo of humanity. Evolution and the Red Queeen Hypothesis dictates that humanity won’t regress back to the mean, it may be regressing itself toward extinction otherwise.

Highlights, Quotes, & Marginalia

Chapter One – Bomb Parts: What is a Model

You can often see troubles when grandparents visit a grandchild they haven’t seen for a while.

Highlight (yellow) page 22 | Location 409-410
Added on Thursday, October 12, 2017 11:19:23 PM

Upon meeting her a year later, they can suffer a few awkward hours because their models are out of date.

Highlight (yellow) page 22 | Location 411-412
Added on Thursday, October 12, 2017 11:19:41 PM

Racism, at the individual level, can be seen as a predictive model whirring away in billions of human minds around the world. It is built from faulty, incomplete, or generalized data. Whether it comes from experience or hearsay, the data indicates that certain types of people have behaved badly. That generates a binary prediction that all people of that race will behave that same way.

Highlight (yellow) page 22 | Location 416-420
Added on Thursday, October 12, 2017 11:20:34 PM

Needless to say, racists don’t spend a lot of time hunting down reliable data to train their twisted models.

Highlight (yellow) page 23 | Location 420-421
Added on Thursday, October 12, 2017 11:20:52 PM

the workings of a recidivism model are tucked away in algorithms, intelligible only to a tiny elite.

Highlight (yellow) page 25 | Location 454-455
Added on Thursday, October 12, 2017 11:24:46 PM

A 2013 study by the New York Civil Liberties Union found that while black and Latino males between the ages of fourteen and twenty-four made up only 4.7 percent of the city’s population, they accounted for 40.6 percent of the stop-and-frisk checks by police.

Highlight (yellow) page 25 | Location 462-463
Added on Thursday, October 12, 2017 11:25:50 PM

So if early “involvement” with the police signals recidivism, poor people and racial minorities look far riskier.

Highlight (yellow) page 26 | Location 465-466
Added on Thursday, October 12, 2017 11:26:15 PM

The questionnaire does avoid asking about race, which is illegal. But with the wealth of detail each prisoner provides, that single illegal question is almost superfluous.

Highlight (yellow) page 26 | Location 468-469
Added on Friday, October 13, 2017 6:01:28 PM

judge would sustain it. This is the basis of our legal system. We are judged by what we do, not by who we are.

Highlight (yellow) page 26 | Location 478-478
Added on Friday, October 13, 2017 6:02:53 PM

(And they’ll be free to create them when they start buying their own food.) I should add that my model is highly unlikely to scale. I don’t see Walmart or the US Agriculture Department or any other titan embracing my app and imposing it on hundreds of millions of people, like some of the WMDs we’ll be discussing.

You have to love the obligatory parental aphorism about making your own rules when you have your own house.
Yet the US SNAP program does just this. It could be an interesting example of this type of WMD.
Highlight (yellow) page 28 | Location 497-499
Added on Friday, October 13, 2017 6:06:04 PM

three kinds of models.

namely: baseball, food, recidivism
Highlight (yellow) page 27 | Location 489-489
Added on Friday, October 13, 2017 6:08:26 PM

The first question: Even if the participant is aware of being modeled, or what the model is used for, is the model opaque, or even invisible?

Highlight (yellow) page 28 | Location 502-503
Added on Friday, October 13, 2017 6:08:59 PM

many companies go out of their way to hide the results of their models or even their existence. One common justification is that the algorithm constitutes a “secret sauce” crucial to their business. It’s intellectual property, and it must be defended,

Highlight (yellow) page 29 | Location 513-514
Added on Friday, October 13, 2017 6:11:03 PM

the second question: Does the model work against the subject’s interest? In short, is it unfair? Does it damage or destroy lives?

Highlight (yellow) page 29 | Location 516-518
Added on Friday, October 13, 2017 6:11:22 PM

While many may benefit from it, it leads to suffering for others.

Highlight (yellow) page 29 | Location 521-522
Added on Friday, October 13, 2017 6:12:19 PM

The third question is whether a model has the capacity to grow exponentially. As a statistician would put it, can it scale?

Highlight (yellow) page 29 | Location 524-525
Added on Friday, October 13, 2017 6:13:00 PM

scale is what turns WMDs from local nuisances into tsunami forces, ones that define and delimit our lives.

Highlight (yellow) page 30 | Location 526-527
Added on Friday, October 13, 2017 6:13:20 PM

So to sum up, these are the three elements of a WMD: Opacity, Scale, and Damage. All of them will be present, to one degree or another, in the examples we’ll be covering

Think about this for a bit. Are there other potential characteristics?
Highlight (yellow) page 31 | Location 540-542
Added on Friday, October 13, 2017 6:18:52 PM

You could argue, for example, that the recidivism scores are not totally opaque, since they spit out scores that prisoners, in some cases, can see. Yet they’re brimming with mystery, since the prisoners cannot see how their answers produce their score. The scoring algorithm is hidden.

This is similar to anti-class action laws and arbitration clauses that prevent classes from realizing they’re being discriminated against in the workplace or within healthcare. On behalf of insurance companies primarily, many lawmakers work to cap awards from litigation as well as to prevent class action suits which show much larger inequities that corporations would prefer to keep quiet. Some of the recent incidences like the cases of Ellen Pao, Susan J. Fowler, or even Harvey Weinstein are helping to remedy these types of things despite individuals being pressured to stay quiet so as not to bring others to the forefront and show a broader pattern of bad actions on the part of companies or individuals. (This topic could be an extended article or even book of its own.)
Highlight (yellow) page 31 | Location 542-544
Added on Friday, October 13, 2017 6:20:59 PM

the point is not whether some people benefit. It’s that so many suffer.

Highlight (yellow) page 31 | Location 547-547
Added on Friday, October 13, 2017 6:23:35 PM

And here’s one more thing about algorithms: they can leap from one field to the next, and they often do. Research in epidemiology can hold insights for box office predictions; spam filters are being retooled to identify the AIDS virus. This is true of WMDs as well. So if mathematical models in prisons appear to succeed at their job—which really boils down to efficient management of people—they could spread into the rest of the economy along with the other WMDs, leaving us as collateral damage.

Highlight (yellow) page 31 | Location 549-552
Added on Friday, October 13, 2017 6:24:09 PM

Guide to highlight colors

Yellow–general highlights and highlights which don’t fit under another category below
Orange–Vocabulary word; interesting and/or rare word
Green–Reference to read
Blue–Interesting Quote
Gray–Typography Problem
Red–Example to work through

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

Syndicated copies to:

👓 Going Indie. Step 2: Reclaiming Content | Matthias Ott

Going Indie. Step 2: Reclaiming Content by Matthias Ott (Matthias Ott | User Experience Designer)
We have lost control over our content. To change this, we need to reconsider the way we create and consume content online. We need to create a new set of tools that enable an independent, open web for everyone.

A nice narrative for the IndieWeb movement by Matthias.

Some of my favorite quotes from the piece:

Having your own website surely is a wonderful thing, but to be relevant, useful, and satisfactory, it needs to be connected to other sites and services. Because ultimately, human interactions are what fuels social life online and most of your friends will still be on social networks, for now.

…what the IndieWeb movement is about: Creating tools that enable a decentralized, people-focused alternative to the corporate web, putting you back in control, and building an active community around this idea of independence.

Tim Kadlec reminded us of the underlying promise of the web:

The web is for everyone.

Wilson Miner put it in his 2011 Build conference talk:
“The things that we choose to surround ourselves will shape what we become. We’re actually in the process of building an environment, where we’ll spend most of our time, for the rest of our lives.”

 

This also reminds me that I ought to swing by room 3420 in Boelter Hall on my way to math class this week. I forget that I’m always taking classes just a few floors away from the room that housed the birth of the internet.

Syndicated copies to:

👓 Two alternatives to #WomenBoycottTwitter that don’t rely on women’s silencing | Another Angry Woman

Two alternatives to #WomenBoycottTwitter that don’t rely on women’s silencing by Zoe Stavri (Another Angry Woman)
After Twitter extending their risible “abuse” policy to a suspension of a celebrity white woman speaking out against sexual violence, the problems in their model have been laid bare, and to my pleasant surprise, people are talking about taking action (I’d been pessimistic about this). Unfortunately, it’s entirely the wrong kind of action: a women’s boycott. This is a problem, because once again, it forces us to do the heavy lifting. And once again, it forces us to silence ourselves: the very opposite of what we should be doing. So, here’s two things that can be done. One is an activity for men who consider themselves allies. The other is for all of us. Especially women.

I took part in #WomenBoycottTwitter today and it honestly wasn’t too difficult, though I did miss out on some of the scientific chatter that crosses my desk during the day. Since I post mostly to my own website more often and syndicate to Twitter only occasionally, the change didn’t feel too drastic to me, though there were one or two times I almost accidentally opened Twitter to track down people’s sites. Fortunately I’ve taken control of more of my online experience back for myself using IndieWeb principles.

This particular post has some seemingly interesting methods for fighting against the status quo on Twitter for those who are entrenched though. The first #AmplifyWomen sounds a lot like the great advice I heard from Valerie Alexander a few months ago at an Innovate Pasadena event.

Some of the others almost seek to reverse-gamify Twitter’s business model. People often complain about silos and how they work, but few ever seek to actively subvert or do this type of reverse-gamification of those models. This is an interesting concept though to be as useful tools as they might be, it may be somewhat difficult to accomplish in some cases and may hamper one’s experience on such platforms.  This being said, having ultimate control over your domain, data, and interactions is still a far preferable model.

And while we’re thinking about amplifying women, do take a look at some of Zoe’s other content, she’s got a wealth of good writing. I’ll be adding her to my follow list/reader.

h/t Richard Eriksson

Syndicated copies to:

👓 Towards a more democratic Web | Tara Vancil

Towards a more democratic Web by Tara Vancil (Tara Vancil)
Many people who have suffered harassment on Twitter (largely women), are understandably fed up with Twitter’s practices, and have staged a boycott of Twitter today October 13, 2017. Presumably the goal is to highlight the flaws in Twitter’s moderation policies, and to push the company to make meaningful changes in their policies, but I’d like to argue that we shouldn’t expect Twitter’s policies to change.

I think I believe Tara when she says about Twitter:

It’s not going to get better.

I think there are a lot of people, including myself, who also think like she does here:

I want online media to work much more like a democracy, where users are empowered to decide what their experience is like.

The difference for her is that she’s actively building something to attempt to make things better not only for herself, but for others. This is tremendously laudable.

I’d heard of her project Beaker and Mastodon before, but hadn’t heard anything before about Patchwork, which sounds rather interesting.

h/t Richard Eriksson for highlighting this article on Reading.am though I would have come across it tomorrow morning likely in my own feed reader.

Syndicated copies to:

👓 Twitter CEO promises to crack down on hate, violence and harassment with “more aggressive” rules | Tech Crunch

Twitter CEO promises to crack down on hate, violence and harassment with “more aggressive” rules by Matthew Panzarino (Tech Crunch)
Twitter CEO Jack Dorsey took to…Twitter today to promise a “more aggressive” stance in its rules and how it enforces them. The tweet storm was based in a response to the #WomenBoycottTwitter protest, as well as work that Dorsey says Twitter has been working ‘intensely’ on over the past few months. Dorsey says that critical decisions were made today in how to go about preventing the rampant and vicious harassment many women, minorities and other users undergo daily on the platform. “We decided to take a more aggressive stance in our rules and how we enforce them,” Dorsey says. “New rules around: unwanted sexual advances, non-consensual nudity, hate symbols, violent groups, and tweets that glorifies violence. These changes will start rolling out in the next few weeks. More to share next week.”

I don’t have very high hopes for the climate changing on this issue though I did participate in the Twitter boycott today.

Syndicated copies to:

📖 Read pages 112-121 of Abstract Algebra: An Introduction by Thomas W. Hungerford

📖 Read pages 112-121 of Abstract Algebra: An Introduction (First Edition) by Thomas W. Hungerford
Chapter 5: Congruence in F[x] and Congruence-Class arithmetic, Sections 1 and 2

Reviewing over some algebra for my algebraic geometry class tonight. I always did love the pedagogic design of this textbook. The way he builds up algebraic structures is really lovely.

Abstract Algebra: An Introduction

Syndicated copies to:

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

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

Model of universe structureDiscoveries seem to back up many of our ideas about how the universe got its large-scale structure

Andrey Kravtsov (The University of Chicago) and Anatoly Klypin (New Mexico State University). Visualisation by Andrey Kravtsov

The missing links between galaxies have finally been found. This is the first detection of the roughly half of the normal matter in our universe – protons, neutrons and electrons – unaccounted for by previous observations of stars, galaxies and other bright objects in space.

You have probably heard about the hunt for dark matter, a mysterious substance thought to permeate the universe, the effects of which we can see through its gravitational pull. But our models of the universe also say there should be about twice as much ordinary matter out there, compared with what we have observed so far.

Two separate teams found the missing matter – made of particles called baryons rather than dark matter – linking galaxies together through filaments of hot, diffuse gas.
Continue reading “👓 Half the universe’s missing matter has just been finally found | New Scientist”

Syndicated copies to:

📗 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.

Highlight (yellow) – Introduction > Location xxxx
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.

Syndicated copies to:

👓 Vladimir Voevodsky, 1966 – 2017 | John Carlos Baez

Vladimir Voevodsky, 1966 - 2017 by John Carlos Baez (Google+)
This mathematician died last week. He won the Fields Medal in 2002 for proving the Milnor conjecture in a branch of algebra known as algebraic K-theory. He continued to work on this subject until he helped prove the more general Bloch-Kato conjecture in 2010. Proving these results — which are too technical to easily describe to nonmathematicians! — required him to develop a dream of Grothendieck: the theory of motives. Very roughly, this is a way of taking the space of solutions of a collection of polynomial equations and chopping it apart into building blocks. But the process of 'chopping up', and also these building blocks, called 'motives', are very abstract — nothing simple or obvious.

There’s some interesting personality and history in this short post of John’s.

Syndicated copies to:

👓 The Next Platform | Pierre Levy

The Next Platform by Pierre Levy (Pierre Levy's Blog)
One percent of the human population was connected to the Internet at the end of the 20th century. In 2017, more than 50% is. Most of the users interact in social media, search information, buy products and services online. But despite the ongoing success of digital communication, there is a growing dissatisfaction about the big tech companies (the “Silicon Valley”) who dominate the new communication environment. The big techs are the most valued companies in the world and the massive amount of data that they possess is considered the most precious good of our time. The Silicon Valley owns the big computers: the network of physical centers where our personal and business data are stored and processed. Their income comes from their economic exploitation of our data for marketing purpose and from their sales of hardware, software or services. But they also derive considerable power from the knowledge of markets and public opinions that stems from their information control.

Transparency is the very basis of trust and the precondition of authentic dialogue. Data and people (including the administrators of a platform), should be traceable and audit-able. Transparency should be reciprocal, without distinction between rulers and ruled. Such transparency will ultimately be the basis of reflexive collective intelligence, allowing teams and communities of any size to observe and compare their cognitive activity.

The trouble with some of this is the post-truth political climate in which basic “facts” are under debate. What will the battle between these two groups look like and how can actual facts win out in the end? Will the future Eloi and Morlocks be the descendants of them? I would have presumed that generally logical, intelligent, and educated people would generally come to a broadly general philosophical meeting of the minds as to how to best maximize life, but this seems to obviously not be the case as the result of the poorly educated who will seemingly believe almost anything. And this problem is generally separate from the terrifically selfish people who have differing philosophical stances on how to proceed. How will these differences evolve over time?

This article is sure to be interesting philosophy among some in the IndieWeb movement, but there are some complexities in the system which are sure to muddy the waters. I suspect that many in the Big History school of thought may enjoy the underpinnings of this as well.

I’m going to follow Pierre Levy’s blog to come back and read a bit more about his interesting research programme. There’s certainly a lot to unpack here.

 

Annotations

The Next Platform

Commonality means that people will not have to pay to get access to the new public sphere: all will be free and public property. Commonality means also transversality: de-silo and cross-pollination.


Openness is on the rise because it maximizes the improvement of goods and services, foster trust and support collaborative engagement.


We need a new kind of public sphere: a platform in the cloud where data and metadata would be our common good, dedicated to the recording and collaborative exploitation of our memory in the service of collective intelligence. According to the current zeitgeist, the core values orienting the construction of this new public sphere should be: openness, transparency and commonality


The practice of writing in ancient palace-temples gave birth to government as a separate entity. Alphabet and paper allowed the emergence of merchant city-states and the expansion of literate empires. The printing press, industrial economy, motorized transportation and electronic media sustained nation-states.


The digital revolution will foster new forms of government. We discuss political problems in a global public space taking advantage of the web and social media. The majority of humans live in interconnected cities and metropoles. Each urban node wants to be an accelerator of collective intelligence, a smart city.

Syndicated copies to: