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I will say from the outside looking in the argument that any of these awards shows are "trade organizations" seems quite weak, and I would love to see how the court case goes here...

Yes, it's quite a weak argument when you publicly categorize yourself as a trade organization for an exemption from taxation by the IRS.

Maybe they should fictionalize (or not) Atomwaffen Division and use them as a (too close to reality) terrorist group. I suppose it would make the film hard to classify as drama or documentary.

The U.S. government needs FAR better management.

One example is the problems at the IRS:

The IRS Really Needs Some New Computers (April 17, 2018) "The tax agency's embrace of IBM in the 1950s helped drive down audit rates. It's still depending on the same code."

IRS says it's using technology from JFK's time (Feb. 3, 2015)

TurboTax, H&R Block Spend Big Bucks Lobbying for Us to Keep Doing Our Own Taxes (March 23, 2017)

How the IRS Was Gutted (Dec. 11, 2018) "An eight-year campaign to slash the agency's budget has left it understaffed, hamstrung and operating with archaic equipment. The result: billions less to fund the government. That's good news for corporations and the wealthy."

Who's More Likely to Be Audited: A Person Making $20,000 -- or $400,000? (Dec. 12, 2018) "If you claim the earned income tax credit, whose average recipient makes less than $20,000 a year, you're more likely to face IRS scrutiny than someone making twenty times as much. How a benefit for the working poor was turned against them."

After Budget Cuts, the IRS' Work Against Tax Cheats Is Facing "Collapse" (Oct. 1, 2018) "Audits and criminal referrals are down sharply since Congress cut the tax agency's budget and management changed priorities."

There are much earlier reports about IRS under-management: Internal Revenue Service is a den of thieves. (April 2, 2000. Not a "den of thieves", just terribly undermanaged, apparently.) "The GAO audit compared the agency to someone who can't balance his or her checkbook and instead just adjusts it to agree with the bank statement."

The U.S. government needs FAR better management.

One example is the problems at the IRS:

The IRS Really Needs Some New Computers (April 17, 2018) "The tax agency's embrace of IBM in the 1950s helped drive down audit rates. It's still depending on the same code."

IRS says it's using technology from JFK's time (Feb. 3, 2015)

TurboTax, H&R Block Spend Big Bucks Lobbying for Us to Keep Doing Our Own Taxes (March 23, 2017)

How the IRS Was Gutted (Dec. 11, 2018) "An eight-year campaign to slash the agency's budget has left it understaffed, hamstrung and operating with archaic equipment. The result: billions less to fund the government. That's good news for corporations and the wealthy."

Who's More Likely to Be Audited: A Person Making $20,000 -- or $400,000? (Dec. 12, 2018) "If you claim the earned income tax credit, whose average recipient makes less than $20,000 a year, you're more likely to face IRS scrutiny than someone making twenty times as much. How a benefit for the working poor was turned against them."

After Budget Cuts, the IRS' Work Against Tax Cheats Is Facing "Collapse" (Oct. 1, 2018) "Audits and criminal referrals are down sharply since Congress cut the tax agency's budget and management changed priorities."

There are much earlier reports about IRS under-management: Internal Revenue Service is a den of thieves. (April 2, 2000. Not a "den of thieves", just terribly undermanaged, apparently.) "The GAO audit compared the agency to someone who can't balance his or her checkbook and instead just adjusts it to agree with the bank statement."

The U.S. government needs FAR better management.

One example is the problems at the IRS:

The IRS Really Needs Some New Computers (April 17, 2018) "The tax agency's embrace of IBM in the 1950s helped drive down audit rates. It's still depending on the same code."

IRS says it's using technology from JFK's time (Feb. 3, 2015)

TurboTax, H&R Block Spend Big Bucks Lobbying for Us to Keep Doing Our Own Taxes (March 23, 2017)

How the IRS Was Gutted (Dec. 11, 2018) "An eight-year campaign to slash the agency's budget has left it understaffed, hamstrung and operating with archaic equipment. The result: billions less to fund the government. That's good news for corporations and the wealthy."

Who's More Likely to Be Audited: A Person Making $20,000 -- or $400,000? (Dec. 12, 2018) "If you claim the earned income tax credit, whose average recipient makes less than $20,000 a year, you're more likely to face IRS scrutiny than someone making twenty times as much. How a benefit for the working poor was turned against them."

After Budget Cuts, the IRS' Work Against Tax Cheats Is Facing "Collapse" (Oct. 1, 2018) "Audits and criminal referrals are down sharply since Congress cut the tax agency's budget and management changed priorities."

There are much earlier reports about IRS under-management: Internal Revenue Service is a den of thieves. (April 2, 2000. Not a "den of thieves", just terribly undermanaged, apparently.) "The GAO audit compared the agency to someone who can't balance his or her checkbook and instead just adjusts it to agree with the bank statement."

it's in the interest of that jurisdiction to ensure that people complete their tax returns accurately

Not necessarily for two reasons. First, it's in the government's interest for people who are entitled to deductions or credits to miss those deductions or credits. Second, it's in the (conflicted) interest of the members of the legislature to stay in office. Big tax preparers like Intuit and H&R Block have spent big bucks to convince legislators that only dirty commies would take tax money to drive private-sector tax preparers out of the market. (Source: "How the Maker of TurboTax Fought Free, Simple Tax Filing" by Liz Day; "CCIA's View on Government Competition")

Maybe you are not skilled or poorly skilled in Google Foo but it is widely accepted that it isn't a complete waste.

I didn't say it was net negative, budget-wise, just that there are surely much better investments for taxpayers. If, for example, avoidance of lost revenue is to be pursued here, as the article seems to suggest, what about stopping gutting the IRS instead? Taking the numbers from that article of yours at face value (which doesn't even seem to suggest any operational cost for the project, or did I misread it?), the wall is peanuts compared to the uncollected taxes.

https://www.kansas.com/news/po... [kansas.com]

"Another 34 were identified by the Sedgwick County Election Office when staff attended naturalization ceremonies to register new citizens and discovered some were already registered."

If you read your link, you will notice that Kris Kobach, who is anything but a neutral observer, offers ZERO EVIDENCE that these things happened, but assures us that they did. Let's see...can we think of any other instances where Kobach lied or whether he had an incentive to do so?

https://slate.com/news-and-pol...

https://www.kansascity.com/new...

https://www.aclu.org/blog/voti...

https://www.theatlantic.com/po...

Here's even more recent news about Kris Kobach lying in order to enrich himself at the expense of a bunch of small towns by selling them on a non-existent "immigrant crisis".

https://splinternews.com/kris-...

https://www.propublica.org/art...

modern environmentalism ... It's now a strange religion that mostly combines elements of primeval nature worship

I consider myself a level-headed person who sees the world reported to me by scientific study. I think you'd call me, therefore, a rabid environmentalist, and I'd call you a dogmatic, biased, neanderthal, stuck in the past, promoting buggy-whips.

But just in case you're capable of discussing topics like grownups, here's some real commentary:

I want to say thanks for opening my eyes a little about shale gas. I previously only knew that it probably caused local environmental damage like minor earthquakes and some correlation to flammable sink water. However, I'm not sure those effects are large-scale enough to dismiss the technology, given the real costly gorilla issue: climate change. Your comment and those above made me think more about it and look it up. I found, so far, that the real thing to consider with shale gas is methane leakage. The latest study I found says if it's kept below 3.2%, it's better than coal, and a 2009 study says it was at 2.4%, so I'm already on board with using shale to replace coal. I wonder if anyone can reply with more recent and definitive data.

However, "better than coal" is not necessarily good enough. I've lived through Hurricane Harvey. If that's indicating what the future holds, then the current cost of any fossil fuel is way higher than we think, we're just not paying for it yet. I therefore believe the best idea I've heard, is that we have to try and estimate that cost, and actually charge it so that we know what we're getting. A carbon tax that is calculated to cost less than 3% of GDP sounds right to me. I'm not mad if gas companies accidentally release methane, as long as they're paying the appropriate price for it.

First of all, this housing thing has been going on for quite a while now:
https://www.engadget.com/2017/...

Secondly, there are quite a few examples, such as:
https://consequenceofsound.net...

All this is just the stuff on the surface, where advertisers are abusing Facebook's targeting system. One abstraction layer further you get the Cambridge Analytica stuff. Databrokers taking your Facebook data, and then selling all kinds of derived scores to employers, insurers politicians.

Women don't see high paying job adds:
https://www.theguardian.com/te...

Getting red-lighted at job interviews:
https://www.theguardian.com/sc...

Easier to get a loan if you have 'good' friends:
https://trustingsocial.com/

IRS looking at social media posts to determine who gets an audit:
https://news.slashdot.org/stor...

Health insurers figuring out who they want to insure:
https://www.propublica.org/art...

As Cathy o Neill pointed out in her book "Weapons of Math Destruction", all this tech doesn't remove discrimination, it just hides it behind the facade of 'neutral math'.

And PraegerU, a conservative non-profit group that produces educational videos on conservative issues, was just banned by Facebook.

Meanwhile, leftist hate-speech is suspiciously ignored, until it's pointed out by the media:

In several instances, Facebook ignored repeated requests by users to delete hateful content that violated its guidelines. At least a dozen people, as well as the Anti-Defamation League in 2012, lodged protests with Facebook to no avail about a page called Jewish Ritual Murder. However, after ProPublica asked Facebook about the page, it was taken down.

Yep. "Jewish ritual murder" isn't hate speech, but a pro-gun-ownership political candidate is.

Scary times indeed.

Distribution is a service.

When economists talk about "distribution", then mean the distribution and allocation of goods and services. Economists don't care what logo is on the truck making shipments. They care about how many trucks are going to what places.

Capitalists see subsidies as Lemon Socialism. Liberals see subsides as a form of capitalism. The capitalists have a better claim: The TARP bank bailout, and the auto industry bailout were both passed by Democrats, and opposed by Republicans.

Partisanship somehow changes the merits of an argument? That's an... interesting... approach to debate. Politics aside, it's worth noting that the auto bailout ended up costing the US government about $14 billion, while TARP as a whole (including the auto bailout) actually ended up turning a $86 billion profit overall. All together, the program seems to have done exactly what it was intended to do: reduce the shock of the financial crisis, stabilizing the economy to protect against further snowball effects.

Your partisan analysis of subsidies also doesn't mesh with a socialist perspective. To a socialist, subsidies are a governmental decision that something risky is of such benefit to society that the risk (financial or otherwise) should be offset. In a totalitarian state like the USSR or DPRK, the state-run company in that area would just go order work on that project... and open the door to corruption because the state will ensure the project's success, no matter how poorly it's managed or how wasteful it may be. With private industry, however, the subsidies have to be financial offsets, either ensuring a minimum income or covering some expenses outright.

What's offensive to a socialist is the use of subsidies and financial incentives to support projects that aren't directly in the public interest. For example, I know of a particular company that promised to upgrade their factory in a small town, but only if they got a nice tax cut for a few decades (similar to a more-publicized event). While that made for nice headlines about "creating jobs", it hurt the town in the long run. Since the company's normal taxes were a significant percentage of the town's budget, local projects actually lost funding in order to keep the town's budget balanced. Sure, some folks got a new shiny office building, but the high school roof started collapsing.

Unfortunately, that's been a recurring theme with American government policies lately. A notable example is the coal industry, which is subsidized by about $850 million annually, yet only employs about 77,000 people. That's about an $11,000 cost per person per year, ostensibly to keep those 77,000 jobs. The question is, of course, whether we need those jobs as a society. To a socialist, that $11,000 would likely be better spent funding career education and training to support other industries (or even bringing new skills to the coal industry), with the key benefit being that even if the coal industry collapsed, the society would still have a larger wealth of skills to continue progress.

Again, it's a matter of philosophy. The socialists want societal improvement to be the primary goal of government, with industries benefiting indirectly. Who actually owns the company is relatively insignificant at this point.

Didn't Northpoint promise that for the parole/correction software?

https://www.propublica.org/art...

Not really needed by some pharmaceuticals lobby, maybe?

https://www.propublica.org/art...

Also you should remember:

"Price was the first director of HHS, AHRQ's parent agency, under the Trump Administration, before resigning under pressure last year over his spending on chartered flights."

And of course people appointed by Trump Administration think it's a duplicate. How convenient... Less money spent in research, more budget available for chartered flights!

Just as scientific racists hoped that science would justify and enable their racism, technoracists hope that technology will justify and enable theirs. Technoracism is only a couple of years old (about as old as this article), it's only arisen following recent advances in machine learning. The technoracists hope to exploit layered neural networks' inherent ability to launder and obscure the human biases they were trained on, and portray the results of this GIGO effect as being purely logical and therefore somehow justifiable.

The way to pull the rug out from under both scientific racism (which has been enjoying a renaissance recently) and technoracism is use the ethical problems inherent to prejudging people based on immutable traits to argue for why we should never engage in such activities on ethical grounds, no matter how scientifically rigorous or even statistically predictive they may be.

Here are some examples:

- In the USA some judges use sentencing software that analyses if a defendant would be likely to commit a crime again. This software turned out to be biased against black people.
https://www.propublica.org/art...

- Women were less likely to be shown Google adds for high paying jobs, as the algorithm had perceived the existing bias (women less often have high paying jobs), and then concluded that showing these adds to women would result in fewer clicks.
https://www.washingtonpost.com...

- An algorithm denied pregnant women medicare. "The scholar Danielle Keats Citron cites the example of Colorado, where coders placed more than 900 incorrect rules into its public benefits system in the mid-2000s, resulting in problems like pregnant women being denied Medicaid."
https://www.theverge.com/2018/3/21/17144260/healthcare-medicaid-algorithm-arkansas-cerebral-palsy

- Google's sentiment analysis algorithms gave gay related words a low score.
https://tech.slashdot.org/stor...

The list is endless.

The general assumption is: 'algorithms use math and data, thus they must be neutral and scientific'. But it's not that simple. This site explains it: https://www.mathwashing.com/ [mathwashing.com]

"The real danger, then, is not machines that are more intelligent than we are usurping our role as captains of our destinies. The real danger is basically clueless machines being ceded authority far beyond their competence." - Daniel Denett

Why always putting people in the correct categories is mathematically impossible:
https://medium.com/@mrtz/how-big-data-is-unfair-9aa544d739de

Books on the subject:
https://nyupress.org/books/978...
https://weaponsofmathdestructi...
http://www.hup.harvard.edu/cat...

In the USA some judges use sentencing software that analyses if a defendant would be likely to commit a crime again. This software turned out to be biased against black people. https://www.propublica.org/art...

Okay, that's pretty bad.

Women were less likely to be shown Google adds for high paying jobs, as the algorithm had perceived the existing bias (women less often have high paying jobs), and then concluded that showing these adds to women would result in fewer clicks. https://www.washingtonpost.com...

This is not an example of a human rights violation. In no way does this mean women aren't allowed to hold these jobs or apply for them, it just means they are less likely to have these positions advertised to them. Also, who the hell chooses a career based on an Internet advertisement? You should be blocking that shit, anyway. I wouldn't hire anyone -- man or woman -- who doesn't appreciate a good ad blocker.

An algorithm denied pregnant women medicare. "The scholar Danielle Keats Citron cites the example of Colorado, where coders placed more than 900 incorrect rules into its public benefits system in the mid-2000s, resulting in problems like pregnant women being denied Medicaid."
https://www.theverge.com/2018/...

As a public benefits recipient myself, I can pretty much guarantee that a lot of people were affected by this screw-up, not just pregnant women specifically. We really need a broader focus, rather than a focus on broads.

"Illinois ends risk prediction system that assigned hundreds of children a 100 percent chance of death or injury"https://www.theverge.com/2017/...

Again, no human rights violated here. Sounds like some math was done wrong and spit out a scary number.

The list is endless.

It could really use some pruning and trimming. Stick to actual human rights violations, throwing all that other crap in there is artificially inflating the size of the problem and making me want to tune it out entirely.

Here are some examples:

- In the USA some judges use sentencing software that analyses if a defendant would be likely to commit a crime again. This software turned out to be biased against black people. https://www.propublica.org/art...

- Women were less likely to be shown Google adds for high paying jobs, as the algorithm had perceived the existing bias (women less often have high paying jobs), and then concluded that showing these adds to women would result in fewer clicks.
https://www.washingtonpost.com...

- An algorithm denied pregnant women medicare. "The scholar Danielle Keats Citron cites the example of Colorado, where coders placed more than 900 incorrect rules into its public benefits system in the mid-2000s, resulting in problems like pregnant women being denied Medicaid." https://www.theverge.com/2018/...

- "Illinois ends risk prediction system that assigned hundreds of children a 100 percent chance of death or injury"
https://www.theverge.com/2017/...

The list is endless.

The general assumption is: 'algorithms use math and data, thus they must be neutral and scientific'. But it's not that simple. This site explains it: https://www.mathwashing.com/

"The real danger, then, is not machines that are more intelligent than we are usurping our role as captains of our destinies. The real danger is basically clueless machines being ceded authority far beyond their competence." - Daniel Denett

You seem to be willing to ignore not only my sources but also my arguments. But I'll try linking more sources anyway.

https://www.propublica.org/art...

https://github.com/propublica/...

Again, the ProPublica analysis and the vendor's study basically agree on the numbers but define "bias" in different ways. The vendor's PDF says there was no racial bias for a statistician's definition of "bias" which in practical terms, is extremely utilitarian. Again, it basically says that it's fine to discriminate against people based on race as long as the discrimination results in outcomes consistent with the overall numbers for that race. It says that if black people are statistically more likely to reoffend, it's fine to apply higher risk numbers to any and all black people in response to this to produce a statistically unbiased outcome. This is unfair to any individual, who will suffer or benefit from the averages for their race. Propublica calls that biased, rather than using the statistician's definition.

I would ask you to read the article linked in this comment and my response to it to improve your understanding on the difference, and why I disagree with using the statistician's definition to argue that racist algorithms are "unbiased" and therefore acceptable:

https://slashdot.org/comments....

To weigh them in the manner you suggest they would have to have built in associations between places and these racial groups.

Not in the program, no.

Cite proof. The source code can be audited. Surely court cases could demand it. Where is the evidence?

Like I said, it's not in the program. The program doesn't know that race is a thing, it's not programmed explicitly to be racist, it's just learned to make decisions similar to the ones it's been trained on, which have a racial bias that is only reflected in proxy factors. The program only "knows" that certain values for these proxy factors are bad, especially in combination. But it's not so easy to audit the "source code" of neural networks anyway.

That means the correlating element is not race... its ability.

This would only be true if the training data was completely free of racial bias. If you want to argue that, we'll have to agree to disagree, which I'd be glad to do considering that you're ignoring a well-known problem with machine learning algorithms trained on biased human decisions which I can link to again. But you won't read it, you'll stick your head in the sand and call it a liberal witch hunt. Why, I wonder.

Address, name, employment and education history.

Yes the program can make racist decisions without even being aware of the concept of race, because it was trained on racist decisions which it blindly emulates. Educate yourself: https://www.propublica.org/art...

This report sounds legit, although I'm automatically-skeptical because every article I've read by ProPublica (except the one where they mentioned my Congressional campaign in a favorable light) has been deceptive and misleading, arranging facts in such a way as to draw incorrect conclusions and create unfair attacks on organizations people trust.

With the American Red Cross, they've repeatedly published the organization's leaked Lessons Learned--memos which state where they encountered difficulties and problems, and what to do about it in the future (or what to have further discussions over)--and claimed Red Cross is hiding and ignoring serious operating problems and generally wasting money. With Amazon, they went as far as claiming Amazon's offer being the cheapest was a lie because Amazon's offer has free shipping and "let's suppose shipping costs $6--now the competitor is cheaper!" Both of these roll off into bigger discussions that get heavily face-palmy, but let's avoid that here.

The first thing that sticks out here is IBM's memo, shown in part in the article:

Just as importantly, businesses need the gray hairs just as much as the old heads need and want the work. What businesses can't afford to do is simply rehire their experienced workers and put them back into their old jobs. Businesses have to think smarter than that. They need to leverage the experienced and practical intelligence of mature people, and get them to work with younger colleagues and reinvest their experience back into the business.

ProPublica adds:

While recognizing that older workers were important to high-tech employers such as IBM, it concluded that “successor generations are generally much more innovative and receptive to technology than baby boomers.”

These are not mutually-exclusive facts. They can both be true. That doesn't seem to get in the way of a good story:

The message was clear. To succeed at the new technologies, the company must, in the words of the presentation, “become one with the Millennial mindset.” Similar language found its way into a variety of IBM presentations in subsequent years.

I'm not saying IBM did nothing wrong--I need more facts for this--but the tone of the ProPublica article is one centered around generating a certain bias, a way of thinking about statements. "We need to appeal to a younger crowd"? "We need to bring in newer college graduates and their familiarity with new technologies"? Are these discriminatory? Well, okay, yes. So is selling youth baseball bats. Are they discriminatory in a manner of attack, or a manner of trying to extend business to meet modern trends?

I see here IBM making an up-front statement that the future is not throwing out the old and bringing in the new, but rather that the world is changing and that they must bring in the new and adapt to that change without making the mistake of discarding their experienced and important engineers. Yes, they're saying, "Hey, we specifically need to hire younger people to draw what they know and how they think into our corporate culture and organizational knowledge." That's a valid technical concern, although some old folks do behave as outliers and keep up on technology while also having that mindset common among the younger--and they should be hired if qualified.

None of that excuses abuses like this:

Paul Henry, a 61-year-old IBM sales and technical specialist who loved being on the road, had just returned to his Columbus home from a business trip in August 2016 when he learned he’d been let go. When he asked why, he said an executive told him to “keep your mouth shut and go quietly.”

Or especially like this:

Encouraged employees targeted for layof

NYT's correction appears to be at odds with ProPublica's correction.

NYT: "While Ms. Haspel oversaw the site during the torture of Abd al-Rahim al-Nashiri at the site"
via https://www.nytimes.com/2017/0...

ProPublica: "It is now clear that Haspel did not take charge of the base until after the interrogation of Zubaydah ended."
via https://www.propublica.org/art...

Do they also deny the sheep employment, housing, access to credit?

---

Seriously- they trained A.I. on actual cases and the A.I. gave much harsher sentences for the same crime to blacks.
https://www.propublica.org/art...

Because that's what decades of human judges have been doing.
https://www.nytimes.com/2016/1...

As an *old* white texan who voted for Reagan twice, racial bias and injustice bugs the shit out of me. I hate that our country doesn't treat people fairly. It hurts me everytime the police arrest or kill someone because they were driving or walking while black.

We should be better.

We can be better.

TurboTax mostly exists because our Intuit and similar companies fought against having it be simple to file your personal taxes. There is a corollary here, in that the tax system for corporations is similarly the result of bribery.

I disagree with what you say on multiple levels. I did NOT claim that criminal history is a proxy for race. Instead I claimed that blacks are disproportionately likely to have a criminal history. I also do not agree that race predicts recidivism independently, your blatantly racist belief that certain races commit more crimes. One study (or two or three) does not confirm your racist beliefs.

There are multitude other studies that contradict yours - and they have major holes in them. One of the big holes is that you assume arrest statistics are fair, the cops clearly are not. I.E. as demonstrated by this story: https://features.propublica.or..., blacks are far more likely to be punished by police for the same infraction that is ignored when white men do it. This negates the value of statistics showing blacks commit more crimes.

Finally, I do not eliminate valid independent variables. Instead, I claim they are not valid,.

> RACE ONLY MATTERS AS MUCH AS YOU LET IT MATTER.

Jim Crow
Jim Crow 2.0
Red-lining
Red-lining 2.0
Sundown Towns
Tuskegee Experiment
School Segregation
School Segregation 2.0
The War on Drugs specifically targeted blacks
Driving While Black
Walking While Black
Debtor's Prison 2.0

This is the original story that should have been linked to. Not that stupid Vox shit.

https://www.propublica.org/article/when-evidence-says-no-but-doctors-say-yes

Since you refused to read the article:
"The promotion was set to run on the Facebook feeds of users 25 to 36 years old who lived in the nation’s capital, or had recently visited there, and had demonstrated an interest in finance. For a vast majority of the hundreds of millions of people who check Facebook every day, the ad did not exist." https://www.propublica.org/art...
How's that ass-hole.

By correlating other information, it's possible for a piece of software to be racist without using race as an input. You should give this a read:

https://www.propublica.org/art...

Actually, much of the money that was given out has been paid back and most of that that wasn't the Government is earning money on. To date, they've earned more from it they've lost. https://projects.propublica.or...

Almost everything you think you know about Antifa is due to trolling. There are extensive troll campaigns out there involving fake Antifa accounts. Each tries to outdo each other with the most outrageous thing they can say to make gullible right wingers take them seriously.

"Antifa" has no ideology except hatred of Nazis and those espousing similar ideologies (general white supremecists). It is not a "group". It has no "leaders". No little black book. Nothing except "hates and will actively oppose Nazis and other white supremecists", and random people who are of that view describe themselves with the term Antifa. Not all people who identify as "Antifa" support violence as a means to counter Nazi activity (there's been a widespread "Is it okay to punch a Nazi?" debate since Richard Spencer was punched on camera). Of those who would answer that with "Yes", there's a further subset known as "Black Bloc"; which again is not an ideology but more of a style (dressing in black and actively physically engaging when Nazis and aligned groups come to town). The "Don't punch a Nazi" crowd thinks of them as counterproductive. Black Bloc style protesting existed before "Antifa"; before the most recent flareup, it was most commonly associated in the US with WTO protests.

To reiterate: Black Bloc does engage in violence - although you might have been misled about "innocent victims". To pick an example: the most famous viral video of Black Bloc actions was this attack. Who is that poor innocent victim? Why, that's Keith Campbell, known on Twitter as "PatriotWarriorMedia". He's involved in R.A.M. ("Rise Above Movement"), a group built specifically around active training to engage in street brawls with perceived leftists. Rather than all black, their hide-their-face approach is black skeleton masks.

What did Campbell have to say about that protest where he got beaten up beforehand? Why let's look!: "Fuck Antifa! Let them come to Berkeley on August 27th so we can kick their asses AGAIN! @1776RealNews @ProudBoysCA @BasedCops"

How did that work out for you, Keith?

Anyway, this is all secondary to my main point, which was to make you aware of the fact that the vast majority of "Antifa" accounts are just trolling to try to dupe gullible right wingers. My personal take on the whole thing? Black Bloc protesters and R.A.M. deserve each other, and both can go F* themselves as far as I'm concerned.

I get people not seeing it at first glance but they clearly are under the umbrella of larger groups and the major political parties use direct action groups as a blunt tool despite the individual members often not being aware of it. They do have leaders they just look like some loose affiliated collection of dudes from the outside. I know people who have been involved on both the extreme left and right in Europe, mainly the left but a few on the right. On a local level like the independent groups identifying as blackbloc are coordinated by someone, although not exactly a formal leader by any stretch. However these groups answer to someone who is a coordinater with some semblance of structure and order (despite the ones I knew mainly being a mess they sort of work) and they themselves interface with a mid

Almost everything you think you know about Antifa is due to trolling. There are extensive troll campaigns out there involving fake Antifa accounts. Each tries to outdo each other with the most outrageous thing they can say to make gullible right wingers take them seriously.

"Antifa" has no ideology except hatred of Nazis and those espousing similar ideologies (general white supremecists). It is not a "group". It has no "leaders". No little black book. Nothing except "hates and will actively oppose Nazis and other white supremecists", and random people who are of that view describe themselves with the term Antifa. Not all people who identify as "Antifa" support violence as a means to counter Nazi activity (there's been a widespread "Is it okay to punch a Nazi?" debate since Richard Spencer was punched on camera). Of those who would answer that with "Yes", there's a further subset known as "Black Bloc"; which again is not an ideology but more of a style (dressing in black and actively physically engaging when Nazis and aligned groups come to town). The "Don't punch a Nazi" crowd thinks of them as counterproductive. Black Bloc style protesting existed before "Antifa"; before the most recent flareup, it was most commonly associated in the US with WTO protests.

To reiterate: Black Bloc does engage in violence - although you might have been misled about "innocent victims". To pick an example: the most famous viral video of Black Bloc actions was this attack. Who is that poor innocent victim? Why, that's Keith Campbell, known on Twitter as "PatriotWarriorMedia". He's involved in R.A.M. ("Rise Above Movement"), a group built specifically around active training to engage in street brawls with perceived leftists. Rather than all black, their hide-their-face approach is black skeleton masks.

What did Campbell have to say about that protest where he got beaten up beforehand? Why let's look!: "Fuck Antifa! Let them come to Berkeley on August 27th so we can kick their asses AGAIN! @1776RealNews @ProudBoysCA @BasedCops"

How did that work out for you, Keith?

Anyway, this is all secondary to my main point, which was to make you aware of the fact that the vast majority of "Antifa" accounts are just trolling to try to dupe gullible right wingers. My personal take on the whole thing? Black Bloc protesters and R.A.M. deserve each other, and both can go F* themselves as far as I'm concerned.

To be fair, Google has been an excellent custodian of our data, thus far.

To be fair, no, they haven't been. In fact, there have been so many problems with their handling of our data that Wikipedia even has a dedicated page to privacy concerns regarding Google. Which is in addition to the Criticism of Google page that has a section dedicated to criticisms regarding their handling of our privacy.

But in the last 10 years alone, Google has been the subject of several hacks (e.g. a Google Docs vulnerability that allowed anyone access to any document, the Operation Aurora hacks from China, etc.), has given our data away without our permission on more than one occasion (the most egregious of which was their handling of Google Buzz that allowed stalkers and abusive ex-husbands to rediscover their victims), and has eliminated the barrier preventing them from using private information in selling ads.

I know it sounds like I'm dishing a lot on Google, but that's actually not my point here. Google has every reason to protect that data to the best of its ability, since their business depends on protecting our data so well that we continue giving our data to them voluntarily. The fact that not even Google—a company who lives and breathes in this space—can protect us from hackers, their own greed, and their lack of creativity in imagining how a feature could go wrong should tell us that no company who builds their business on collecting this sort of data can be trusted to keep it safe.

That's my point.

Hate crimes and bias incidents are a national problem, but there’s no reliable data on the nature or prevalence of the violence. We’re collecting and verifying reports to create a national database for use by journalists, researchers and civil-rights organizations.

The 2016 election left many in America afraid – of intolerance and the violence it can inspire. The need for trustworthy facts on the details and frequency of hate crimes and other incidents born of prejudice has never been more urgent.

At this point, there is simply no reliable national data on hate crimes. And no government agency documents lower-level incidents of harassment and intimidation, such as online or real-life bullying. Documenting and understanding all of these incidents – from hate-inspired murders to anti-Semitic graffiti to racist online trolling – requires new, more creative approaches.

This is a dangerous idea. Some group, not answerable to anyone, gets to put people into a database of "wrongthink". TFS and TFA talk about "hate crimes" - one would like that to imply that they would only collect law enforcement data, ideally restricted to actual convictions. That might be ok, but that's not what they're doing.

In fact, the "hate crime" collection apparently involves becoming a central repository for any sort of article, blog post, or whatever that talks about supposed incidents of "hate". That would be bad enough, since the criteria are entirely subjective.

But it's worse than that. If you go to the actual project page, they want to document hate crimes and "bias incidents". For the latter, they are happy to accept individual stories. Who gets to define what constitutes a "bias" incident?

At best, this is just another SJW right-think project, giving the long list of corporate sponsors a wonderful opportunity to virtue signal. At worst, if individual people are named in the individual stories they intend to collect, it will become a form of arbitrary, non-judicial punishment with no recourse to the people named.

If you actually read the article, you will see that they are not saying black people are more likely to be judged as a threat, but that black people are judged as more of a threat than they end up being, relative to white people. They're not comparing predictions, they're comparing predictions and results.

"Bias" in these articles (and the studies they talk about) mean that the algorithms' predictions are wrong in opposite directions for people of different groups. The ProPublica article compares the AI predictions with the actual recidivism of ex-prisoners, and looks at the rates of "false" positives and "false" negatives for blacks and whites. The cases in the MIT article also compare predictions with results.

"Bias" in these articles (and the studies they talk about) mean that the algorithms' predictions are wrong in opposite directions for people of different groups. The ProPublica article compares the AI predictions with the actual recidivism of ex-prisoners, and looks at the rates of "false" positives and "false" negatives for blacks and whites. The cases in the MIT article also compare predictions with results.

mistakes

This seems unlikely. I figure it's far more likely that the AI is simply solving the wrong problem.

No, the problem is that the input data it used had invisible bias. There is an old saying in the computer industry "Garbage in, garbage out.". If the input is biased, the output will be biased.

If the AI's job is to assess the odds of recidivism, taking into account all available data, then it's neither going to go out of its way to be racist, nor go out of its way not to be racist.

What the heck is wrong with computer engineers? You guys think "oh, the problem can't be bad programming, the computer is never wrong. It has to be the user. Somehow."

No, of course it didn't "go out of its way" to be racist. It just happened that the results were racist. One easy explanation for this is that the racism was inherent in the input data.

If it's showing a bias against black convicts, presumably that's because black convicts really do have worse recidivism rates for whatever reason.

So, what you're saying here is that you didn't read the article. (here)

The point of the article was that data showed that the predictions of the AI did not match the data, and the way in which they did not match the data was that they overpredicted recidivism for blacks, and underpredicted recidivism for whites.

(Of course, that's 'recidivism rate' according to the data. It doesn't disprove, say, the existence of a racist police force with a racially-biased arrest pattern.)

True. That's another, different reason that an AI might give output results that are racist.

I'd be willing to bet that if you did a backtesting study, pitting the AI against human judges, the AI would beat them.

The data showed that the AI was slightly better than a coin flip.

Slightly.

It might well also be far more racist, as the judges are likely to want to discount race on moral grounds. They don't just want an AI that predicts recidivism rates, they want one that does so whilst incorporating our senses of morality and fairness. They're obviously not the same thing.

So, basically you're repeating here that you didn't read the article.

"Further, the fact that more people of a particular race are prosecuted is not a reflection of bias in the data, rather a bias in the prosecution."

In this case, "persecuted" was more accurate.

Data is Data. It cannot exhibit a bias.

I can only surmise that you're not an experimental scientist. Data has bias all the time.
In physics (my field) the bias usually has no social consequence-- astronomical statistics, for example, are biased toward bright stars (since they're much easier to see than faint ones, and hence overrepresented in the data set). In social "sciences," however, the bias very often does have social consequences. SAT scores from children whose parents spend tens of thousands of dollars on SAT Prep courses, for example-- surprise!-- score better on SAT exams than ones who don't. The data shows a correlation of SAT score with parental income. Is this real? Better correct for the SAT-prep course effect before making a conclusion.

Data is biased. All the time. Be ready for it.

...Plus, being from the Guardian, I am skeptical that they didn't twist the data some to obtain their desired outcome, which ironically touches on the subject of this story.

Huh? MIT Tecnology Review and Propublica were the source. The link in the summary was this: https://www.axios.com/algorith... which linked here: https://www.propublica.org/art... and here MIT Technology Review

Exactly. The bias is not in the machine, it's in our interpretations of the results

No, the bias is that when you compare the predictions of the algorithm with the actual results, the algorithm predicted that blacks will offend much more than the data shows that they actually do, and predicted white will offend much less often than the data shows that they do.

This is what we mean by bias: the predictions vary from the actual data in a way that is not random, but is biased.

The article being discussed is here, by the way: https://www.propublica.org/art...

The data is incomplete. AI, like humans, makes mistakes like "correlation = causation". The problem is, like some humans, AI doesn't understand this and can't ask for additional information or self-correct.

Very much this. Reading the ProPublica article (the Axios one in the summary doesn't have anything useful except a couple of links - this being one), it's easy to see that the real complaint is that the sentencing algorithm appears to have problems with accuracy when its predictions are compared to what really happens.

Interestingly, if this article is correct, race is not one of the inputs into the system in question (Northpointe's Compas system).

Reading the field guide for the system here I was impressed by the depth of coverage of various facets of criminality the system attempts to analyze in section 4.2, but I can see how whoever came up with those facets could have put a statistical bias into the system if they simply looked at data points of past studies as future predictors. My suspicion is that the underlying problem is that there are dimensions that we either don't understand correctly/are applying inappropriately or that the system was built to use past statistics as future predictors and that races can tend to have those input data points in common.

The problem is not that the data set reflects the reality. The problem is not that the AI makes mistakes, but that the particular mistakes the AI makes reflect the bias of the society that programmed it.

The link in the summary is to an article which is itself a summary. From the original (here: Machine Bias There’s software used across the country to predict future criminals. And it’s biased against blacks.), the software attempted to predict the probability of future offenses of criminals on probation. It did not, of course, always get it right. But when the actual percentage of re-offenses was compared to the predictions, the AI got it wrong differently for blacks than for whites. Here's what the article said.

We also turned up significant racial disparities, just as Holder feared. In forecasting who would re-offend, the algorithm made mistakes with black and white defendants at roughly the same rate but in very different ways.
The formula was particularly likely to falsely flag black defendants as future criminals, wrongly labeling them this way at almost twice the rate as white defendants. White defendants were mislabeled as low risk more often than black defendants.

What are they calling "bias"? We read constantly about so-called racism based merely on the fact that one race objectively exhibits a particular trait over other races. That's called data, not bias.

It's a tricky question. Just because something is data, does not mean that it isn't biased: data can be biased-- in fact, 90% of what we do in experimental science is understanding the bias in data and figuring out how to get an unbiased measurement out of a biased data set. Almost all data is biased one way or another.

If, for example, white people caught shoplifting are usually given a warning and let off while black people caught shoplifting are arrested and prosecuted ("shopping while black"), the data will show a higher rate of shoplifting among blacks. You will need to go to the raw data to see the actuality. See: https://www.theguardian.com/la...

An AI with no correction for bias will reflect the bias of society.

The article linked is merely a summery of the propublica article, which is has more detail, here: https://www.propublica.org/art...

GP mistyped. Look up "libertarianism" or "liberty" or the select readings of a select few people. I won't give a name for the very reason you already mentioned (indirectly): fucking pointless nitpicks. Find someone for whom you already align somewhat either philosophically or religiously - hopefully there's a libertarian in that small circle. Don't challenge yourself too much, your reply above ... well just be careful!

A libertarian doesn't believe that the people upstream of them has the right to poison the water. How this addressed is a detail. Important, but only a detail.

What matters is that a libertarian OUGHT oppose endless war (military industrial complex), domestic prohibition - literally a modern day holocaust in the millions of lives ruined year after year for decades on end (war on drugs / big alcohol / big tobacco), the prison industrial complex, intrusions into our personal lives (domestic spying*, TSA, 4th amendment breaches), the medical cartels (via the pharmaceutical industry, AMA - look up what they did to black medical colleges and learn why your EPA comment is such a trifling, pointless nitpick). Yes, they oppose educational monopolies (or monopolies on those tax dollars) that are contrary to the students this money ought to serve (not bloated pension funds approved by politicians only concerned with the next election, not the next decade).

You're probably lazy, so here's a link:

https://www.propublica.org/art...
"The AMA apologized to black physicians specifically for a history of systematic exclusion of black physicians from the AMA and its constituent societies. In order to join the AMA for most of its history, you had to belong to a local medical society. Many of those local medical societies were closed to black physicians, particularly in the South. And this condition persisted right up to the civil rights era."

They weren't racists though! It's all about control and restricting the medical profession so they can control prices. Of course that is the motivation for many seemingly racist activities (like WoD).

Dumbfucks who aren't libertarians (small "l") hand this type of control over to entities like AMA. Note that it matters not whether it is nominally "private" or nominally "public". If ultimately they use the force of law to prevent Person A from cooperating** with Person B, then that private/public label doesn't matter.

TLDR - you suck at evaluating ideologies

PS: "regulating pollution with private lawsuits" - somewhat contradictory since "lawsuits" are not private though they can be brought on by a private party - other parties can do the same, even in a civil context - maybe you meant to use the word "civil"???

*because - in reality - international spying is the pretext for monitoring domestic (read "political") threats - which is the main concern.

**cooperation could mean contracting, doing business with, trading, working together, etc - it the most natural, social instinct we have and naturally the one fascist, bootlicking dumbfucks who are not libertarians attack the most vehemently

CAptchA! gratuity - well ... you're very f-ing welcome!

And it is, of course, highly unlikely that race is even an input into the system. It is, however, still possible that other criteria which might be used (income, education level, home address, etc.) could cause the system to end up predicting that members of one race are more likely to be repeat offenders than those of another.

I'm sure it comes as no surprise There have been suggestions of bias against Black people. The accuracy of that report has also been attacked, of course (although seemingly by people with an interest). Personally, I wonder how you can measure the accuracyof the test in the first place, if the score is simply a number from 1-10. Surely the only results to calibrate against are "did not re-offend" and "did re-offend".

Yes. It was two massive tax cuts with rebates. I know I got mine and while happy at the pittance of a check, was rather disappointed that we couldn't just let the budget balance.

The rest is just hyperbole. After 9/11 we spent ten trillion bailing out the banks and airlines and paying for an unfunded war. Consequently, All this ghost money was borrowed from SSI and will probably never paid back. And this was all before the collapse of 2008. This current 20 trillion dollar deficient could get fixed real quick if we give the banks the 11 T they were handed. Airlines another 2 or 3. Boeing a couple of hundred billion them selves. After all the corporate bailouts are paid back what's left of our deficit?

Food for thought. Flame on.
Here's some links for starters:
http://money.cnn.com/news/stor...
http://money.cnn.com/news/spec...
https://projects.propublica.or...

Ah, Clapper, and Comey? Please! Stop digging... Word!

For some reason the link was to the CNET article. The actual propublica article is here: https://www.propublica.org/art...

Quote:
"Cloudflare also has an added appeal to sites such as The Daily Stormer [the neo-Nazi web site]. It turns over to the hate sites the personal information of people who criticize their content. For instance, when a reader figures out that Cloudflare is the internet company serving sites like The Daily Stormer, they sometimes write to the company to protest. Cloudflare, per its policy, then relays the name and email address of the person complaining to the hate site, often to the surprise and regret of those complaining....
“I wasn’t aware that my information would be sent on. I suppose I, naively, had an expectation of privacy,” said Jennifer Dalton, who had complained that The Daily Stormer was asking its readers to harass Twitter users after the election.
Andrew Anglin, the owner of The Daily Stormer, has been candid about how he feels about people reporting his site for its content. “We need to make it clear to all of these people that there are consequences for messing with us,” Anglin wrote in one online post. “We are not a bunch of babies to be kicked around. We will take revenge. And we will do it now.”