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New York City Moves To Create Accountability For Algorithms (propublica.org)

The algorithms that play increasingly central roles in our lives often emanate from Silicon Valley, but the effort to hold them accountable may have another epicenter: New York City. From a report: Last week, the New York City Council unanimously passed a bill to tackle algorithmic discrimination -- the first measure of its kind in the country. The algorithmic accountability bill, waiting to be signed into law by Mayor Bill de Blasio, establishes a task force that will study how city agencies use algorithms to make decisions that affect New Yorkers' lives, and whether any of the systems appear to discriminate against people based on age, race, religion, gender, sexual orientation or citizenship status. The task force's report will also explore how to make these decision-making processes understandable to the public. The bill's sponsor, Council Member James Vacca, said he was inspired by ProPublica's investigation into racially biased algorithms used to assess the criminal risk of defendants. "My ambition here is transparency, as well as accountability," Vacca said.

103 of 183 comments (clear)

  1. Re:Now hold Trump accountable for TREASON by HornWumpus · · Score: 3, Insightful

    Republican!

    These people are obviously just fakes, making Democrats look unhinged.

    But it's believable because the Ds _have_ lost control of their loonies. Unless the Ds check their lunatic fringe, Trump is good for two terms.

    --
    John McAfee 'It was like that time I hired that Bangkok prostitute; to do my taxes, while I fucked my accountant'
  2. Mirror by Anonymous Coward · · Score: 1

    It's often these same people who impose systematic discrimination based on these exact criteria.

    1. Re:Mirror by cayenne8 · · Score: 3, Insightful
      Hmm.....so, if these councils reviewing these algorithms that are finding actual bonafide trends, that happen to break along racial, sexual, [insert special interest here]...and that don't happen to fit the politically correct meme of the day, that they will insist these be thrown out?

      So, facts....if inconvenient....are not to be used or trusted?

      Hmm...isn't that kinda deleting the purpose?

      --
      Light travels faster than sound. This is why some people appear bright until you hear them speak.........
    2. Re:Mirror by CanHasDIY · · Score: 4, Insightful

      Right.

      Because apparently, in 2017, math became racist.

      --
      An enigma, wrapped in a riddle, shrouded in bacon and cheese
    3. Re: Mirror by javaman235 · · Score: 1

      An algorithm is torturing me as we speak, they are worth a closer look. But its all about problems not intended by algorithm designers, so where liability lies is confusing. E.g a racially green programmer favors education for hiring, but education is correlated with money, and legacy racism made green families lower income than blue families, so the algorithm picks blue people overlooking green people.

      --
      -The art of programming is the pursuit of absolute simplicity.
    4. Re: Mirror by MBGMorden · · Score: 2

      That shouldn't really matter. If they are looking for educated people and more blue people are educated than green then the organization shouldn't have to worry about hiring less qualified people based on political correctness.

      Almost comically, these types of things also come from absolute hypocrites.

      If I say "Green people are less educated." I'm attacked for propagating a stereotype, yet the same people levying those attacks will say "You can't hire based on education because green people can't compete.".

      The stereotypes are both shunned and joyously embraced depending on whether one feels it'll help or hurt in the current scenario.

      --
      "People who think they know everything are very annoying to those of us who do."-Mark Twain
    5. Re:Mirror by JaredOfEuropa · · Score: 1

      That's kind of the problem with these algorithms: they are simply applying statistical facts without bothering about causation. Humans tend to do that too, but we've decided that in certain cases its not OK to assume that statistically significant traits of certain groups apply to any individual belonging to that group. It may be true that people of whatever race are statistically more likely to be involved in crime, but it's not OK to deny an individual a loan on that basis, for instance.

      But when you use an 'AI' algorithm, can you still tell which criteria were used to reach a decision, and if those criteria were based on the individual, or on superficial (but statistically significant) traits of a group that the individual belongs to? The obvious way to check is then to simply apply statistics to all decisions made by the algorithm... where you will find without a doubt that the 'AI' is 'racist', because that's how statistics work. If you aggregate multiple outcomes that each were reached based on a fair assessment of the individuals in question, you'll still find those bona fide trends that break along racial or sexual lines. And of course the obvious solution is then to apply a racial bias to the algorithm to compensate for 'undesirable' statistical outcomes. In other words: positive action, automated.

      --
      If construction was anything like programming, an incorrectly fitted lock would bring down the entire building...
    6. Re: Mirror by c6gunner · · Score: 2

      It may be true that people of whatever race are statistically more likely to be involved in crime, but it's not OK to deny an individual a loan on that basis, for instance.

      Where does that stop though? Statistically men die earlier than women; is it wrong to charge men more for life insurance? Statistically women cost the medical system more than men; is it wrong to charge women more for health insurance? Statistically men are more likely to be involved in a traffic accident; is it wrong to charge men more for car insurance?

    7. Re:Mirror by cayenne8 · · Score: 2

      That's kind of the problem with these algorithms: they are simply applying statistical facts without bothering about causation.

      But, if you're going for purely predictive results....what part does "causation" play in this at all?

      --
      Light travels faster than sound. This is why some people appear bright until you hear them speak.........
    8. Re:Mirror by Actually,+I+do+RTFA · · Score: 1

      that are finding actual bonafide trends

      What's a bonafide trend? How do you distinguish it from correctly identifying racism/sexism in the training data?

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      Your ad here. Ask me how!
    9. Re: Mirror by JaredOfEuropa · · Score: 2

      Not an easy question, and I'm hardly an expert on legal or ethical matters. But it seems to me that it's unfair to discriminate on traits where there is only an indirect correlation with undesirable outcomes. If men die earlier than women because of physiological traits, then perhaps it's ok to charge them more for life insurance (though insurers and goverments might not do or allow that for other reasons). But what if black people die earlier? Statistically speaking that's probably the case, but there is no direct correlation between being black and dying earlier; a white guy in the same situation probably faces the same odds. Certain groups are generaly poorer and more likely to eat bad foods as a result, more likely to be in gangs, etc... but that has little to do with race and more with their average economic position. So charge them more for life insurance if they are actually in a gang, or eat crappy food, in other words for the stuff that has a direct impact on their life expectancy, but not for skin color.

      --
      If construction was anything like programming, an incorrectly fitted lock would bring down the entire building...
    10. Re:Mirror by cayenne8 · · Score: 1

      What's a bonafide trend? How do you distinguish it from correctly identifying racism/sexism in the training data?

      I"m not an AI expert, far from it....

      But I would have to imagine that you could at least start with training data that did NOT list race/sex categories and the just turn it loose and see what it finds on its own?

      And look, there ARE differences between the sexes and the races in things. I'm sure if you never told a race and AI studied the NBA vs all other careers...you'd find a lot of trends that went down racial lines. Would you even consider that not to be true?

      Just because things do show up and fall along racial/ or sex lines, doesn't make them racist or sexist in the bad connotations we have put on those terms today. They can just be facts of nature, no?

      Until we see a preponderance of shorter jewish men infiltrating the ranks of the NBA, I"m gonna have to keep my opinions on this as they are...

      --
      Light travels faster than sound. This is why some people appear bright until you hear them speak.........
    11. Re:Mirror by Scroatzilla · · Score: 1

      This is exactly the line of thought that Sweden followed to cover up the negative effects of mass migration. So, good luck with this, New York.

    12. Re: Mirror by Plus1Entropy · · Score: 1

      It depends whether you are looking at correlation or causation. Say, for example, that men not only die earlier than women, they are also more likely to smoke than women. In this case, smoking is the cause of early death, not being a man. So the answer there is to charge smokers more than non-smokers.

      --
      Only crack the nuts that crack. You don't put the ones that don't crack in the sack.
    13. Re: Mirror by Hognoxious · · Score: 1

      there is no direct correlation between being black and dying earlier

      You appear to be using "correlation" to mean "causation".

      A correlation can't be direct or indirect; it's a mathematical fact reflecting how changes in one variable correspond to changes in another. It says nothing about how or why.

      --
      Confucius say, "Find worm in apple - bad. Find half a worm - worse."
    14. Re:Mirror by Actually,+I+do+RTFA · · Score: 1

      I'm assuming this is a legitimate question. It's hard to tell because it's a fairly similar argument to what trolls use.

      Basically, it seems unambiguous that racism (and sexism, but I'll limit myself to racism) existed in the past. The data fed into the AI will take into account racist decisions by humans. As a plausible example that we can pretend is true for this conversation, black people were given worse mortgage terms that led to more defaults. Therefore, the AI interprets black people as having less likelihood to pay back a mortgage (because it does not know and cannot control for the terms). So, that explains how racism from the past can affect the present.

      So, you just eliminate the race field. Everything fine right? Nope, because there are other variables that can predict race, well enough to keep the race based bias. What factors? I'm not sure. But you can certainly imagine that some variables are pretty easy imagine. Let's pretend black people are far more likely to buy a blue car (this one doesn't even seem plausible on face, but we'll assume it)

      So when the AI says that people with blue cars are more likely to default on mortgages, is it learning about a more honest correlation (blue cars are favored by people about to go bankrupt) or a less honest correlation (blue cars are more likely to be driven by black people which are more likely to get fucked over by bankers)? How do you tell?

      Well, TFA was about starting a process to try to identify which is which.

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    15. Re: Mirror by bickerdyke · · Score: 1

      Not neccessarily. Depends on who you blame of being "them".

      --
      bickerdyke
    16. Re:Mirror by bickerdyke · · Score: 1

      But I would have to imagine that you could at least start with training data that did NOT list race/sex categories and the just turn it loose and see what it finds on its own?

      Check out the story behind that whole story about that racist algorithm that decided on jail sentences.

      That is what they did. But you don't need sex/race/age data when e.g. income/education/prior convictions data lets you derive sex/race with a 99.9% result.

      --
      bickerdyke
    17. Re:Mirror by bickerdyke · · Score: 1

      Which Sweden? Has to be that Sweden where Trump saw something happening last night and not the northern European country...

      --
      bickerdyke
    18. Re: Mirror by Citizen+of+Earth · · Score: 1

      It's not "legacy racism", it's a full-standard-deviation lower average IQ that has made green people less educated. IQ is a strong predictor for success and has a strong genetic component that cannot easily be compensated for. OTOH, green people also have a toxic culture that celebrates failure, dependency, and violence; maybe algorithms could do something about that.

    19. Re:Mirror by cayenne8 · · Score: 1
      Hmm.....

      Well, let's say that you start training the AI with more recent data....and if that still shows, without using race as a factor....that black people still are less likely to pay back loans and default or mortgages, negating the factors of the past, is it still wrong to do so?

      What if for the sake of argument (not saying it is true), that black people in general by virtue of data analysis, are more likely to be a credit/loan risk, is that still not basis to see it as a trend that should be considered?

      Of course, that trend may be in large part due to more blacks being in the lower economic groups...then again, there are a lot more poor white people than black people in the US...so, I guess that might moot that point.

      While I agree that you have to be careful in training the AI, I feel we have to be also careful not to try to throw the results out JUST because they happen to fall along racial lines.

      If it is true, it is true....no matter how uncomfortable that truth is, you know?

      --
      Light travels faster than sound. This is why some people appear bright until you hear them speak.........
    20. Re:Mirror by cthulhu11 · · Score: 1

      They just want to ensure that nobody makes a mistake that causes NYC to become even slightly less intolerable.

    21. Re:Mirror by CanHasDIY · · Score: 1

      I'm white and most of those don't apply to me (although I do technically live in a suburb), so your assertion that such criteria is inherently racist rings falsely.

      --
      An enigma, wrapped in a riddle, shrouded in bacon and cheese
    22. Re:Mirror by ZorroXXX · · Score: 1

      In its majestic equality, the law forbids rich and poor alike to sleep under bridges, beg in the streets and steal loaves of bread.

      --
      When you are sure of something, you probably are wrong (search for "Unskilled and Unaware of It").
    23. Re:Mirror by CanHasDIY · · Score: 1

      non sequitur.

      --
      An enigma, wrapped in a riddle, shrouded in bacon and cheese
  3. At least you can examine an algorithm by Rick+Schumann · · Score: 2

    More and more so-called 'AIs' are being used in place of algorithms (due mainly to magical thinking) but even the designers of these AIs can't tell you what they're really doing under the hood. That's where we're going to get in trouble with regards to 'accountability'.

    1. Re:At least you can examine an algorithm by david_thornley · · Score: 1

      AIs do not have legal accountability. People have legal accountability, no matter what tools they use. Illegal discrimination conducted by scientific-sounding means is still illegal discrimination.

      --
      "When you have eliminated the unacceptable, whatever is left, however improbable, must be the truthiness" - Holmes
    2. Re:At least you can examine an algorithm by JoeDuncan · · Score: 1

      ...even the designers of these AIs can't tell you what they're really doing under the hood...

      What a garbage myth. It's simply untrue.

      The designers know what the AIs are doing, it's just never been a priority to make such explanations easily accessible. It is now, and so they're doing it; you're badly misinformed if you think the designers of these systems are clueless.

    3. Re: At least you can examine an algorithm by c6gunner · · Score: 1

      If Microsoft's "Tay" is any indication, teaching AI not to discriminate isn't going to be easy. She started off as a cheerful innocent teenager, and in under 24 hours the internet turned her into a raging Nazi.

    4. Re:At least you can examine an algorithm by JoeDuncan · · Score: 1

      If someone tells you they know how a neural network makes its decisions, they are lying to you.

      Nope, you have been misinformed, even I can tell you that!

      Neural networks make their decisions by using gradient descent to segment an N-dimensional hyperspace with N-1 dimensional hyperplanes.

      Researchers who know how ANNs work have known this for a long time, and can extract more "human readable" explanations from that understanding - it's just that there's never been an impetus to do so before. There is now, so we see researchers actually providing said info now. For example:

      NVidia's ANN for self-driving cars

    5. Re: At least you can examine an algorithm by JoeDuncan · · Score: 1

      ...in under 24 hours the internet turned her into a raging Nazi...

      This is just GIGO though. The internet is like 90% garbage content and trolling assholes - WTF did they expect using that as training data?!?!?!

    6. Re:At least you can examine an algorithm by whh3 · · Score: 1

      I was in a presentation on the ethics of AI at a very prominent computer science conference. Several experts stood up during the presentation to make this very point. Neural networks, what people call AI these days, /are/ black boxes and we know no more about how they make decisions than we do about how the brain makes decisions based on the network of synapses that have been trained by inputs from the time of our birth.

      Thank you for making this point!

      Will

      --
      remove nospam. to email!
    7. Re:At least you can examine an algorithm by bickerdyke · · Score: 1

      Nope, you have been misinformed, even I can tell you that!

      Neural networks make their decisions by using gradient descent to segment an N-dimensional hyperspace with N-1 dimensional hyperplanes.

      Well, that is the knowledge how EVERY neural networks is making its decisions.

      But you don't know why your trained network weighs that input in neuron #5 in layer 3 with .7 instead of .5. And you can not predict if changing it manually by .1 will make your results slightly worse or screw them up completly. You know that they WILL become worse as your training algorithm has already found a local minimum.

      --
      bickerdyke
    8. Re:At least you can examine an algorithm by ZorroXXX · · Score: 1

      The algorithms themselves are actually the least important aspect. As I have said before, even if the algorithms are 100% open and transparent, that means nothing if the data feed into them is poor. If the bank uses an algorithm to determine if it want to lend money to you, how is the data about you collected? Who decided to classify you as a say medium risk person? What criteria did he/she/they use for that? How thorough were he/she/they in gathering decision material? What did he/she/they miss/ignore/misunderstood?

      Unless there is full and complete transparency and accountability for data collection, the transparency for just the algorithms is without value.

      --
      When you are sure of something, you probably are wrong (search for "Unskilled and Unaware of It").
  4. If an algorithm does not have race/gender input by dslmodem · · Score: 1

    Can people figure out how it discriminates against certain race or gender?

    --

    ^(oo)^pig~

    1. Re:If an algorithm does not have race/gender input by Anonymous Coward · · Score: 1

      It would use proxies for this information, sometimes ones that are not always obvious.

    2. Re:If an algorithm does not have race/gender input by Actually,+I+do+RTFA · · Score: 1

      You can look at the outputs. It shouldn't be that hard.

      You can also look at if any of the inputs are proxies for race/gender.

      --
      Your ad here. Ask me how!
    3. Re:If an algorithm does not have race/gender input by ZorroXXX · · Score: 1

      The Anonymous Cowards will all be r a c i s t s. This much is obvious.

      --
      When you are sure of something, you probably are wrong (search for "Unskilled and Unaware of It").
  5. More idiocy by alvinrod · · Score: 4, Insightful

    Algorithms don't discriminate if you remove the kind of data (race, age, etc.) that would allow them to make categorizations or judgments based on that data. But if you examine the results after the fact and reapply those labels and find some difference in outcomes, its because there is some difference in input, not a category identifier. If you find your algorithm thinks African Americans are a worse lending risk, it's likely because they're categorically less well off financially than other demographic groups, not because its racist against black people.

    This kind of idiotic approach is just ignoring the actual underlying problems or differences in favor of trying to slap a band-aid on top of it to assuage guilty feelings. Worse yet, it prevents confronting the actual issues head on and is doomed to failure.

    1. Re:More idiocy by Baron_Yam · · Score: 1, Insightful

      If you're dealing with medicine, noting ethnic differences is important. Doctors understand probabilities and knowing when certain probabilities are elevated can significantly alter diagnostics and treatment to the benefit of the patient.

      Unfortunately, when you're dealing with most other things... you get discrimination. Maybe - to use your example - your algorithm thinks African Americans are a worse lending risk. That's a problem all on its own because that result will be used not to be more cautious financially with the group over all, but to discriminate against individuals and deny them loans based on skin colour.

      And yes, that's actually a problem with the people (mis)using the algorithms, but that's not an excuse for failing to take preventative measures against such misuse.

    2. Re:More idiocy by Anonymous Coward · · Score: 2, Insightful

      The more we learn about science, the more we are going to want to bury our head in the sand and ignore it.

      Yes, in medicine there are statistical differences between the races.

      What if, just maybe, beyond skin color, there are genetic differences between the races in how people value life, truth, and their propensity to violence. This is where people want to bury their heads in the sand. It's time we get honest and accept these truths.

    3. Re:More idiocy by CanHasDIY · · Score: 3, Insightful

      If you're dealing with medicine, noting ethnic differences is important. Doctors understand probabilities and knowing when certain probabilities are elevated can significantly alter diagnostics and treatment to the benefit of the patient.

      And yet, I guarantee some non-doctors out there will claim it's racist to only test black people for sickle-cell anemia. This is why we can't have nice things - we allow the ignorant people to have an equal voice to the knowledgeable.

      --
      An enigma, wrapped in a riddle, shrouded in bacon and cheese
    4. Re:More idiocy by alvinrod · · Score: 4, Interesting

      Please explain how an algorithm can be biased if you leave out ethnicity from the input data, but only after the fact discover that it results in fewer individuals of some group getting loans. It's not discriminating, it's just pointing out that two groups have very different input values as a very broad category. It probably also has different results between Asians, Jews, Hispanics, and most other groups. You're mistaking identifying different outcomes after the fact as a result of different initial factors with the usual human approach of lazily categorizing based on factors that aren't causal, but merely correlations.

      You can even prove its not racist by finding a set of input data for individuals from two different demographic groups and seeing if it returns the same results for both. My guess is that it gives loans to black people who have good credit scores, a stable income, etc. and denies them to white people who have poor credit history and no steady income.

      Algorithms are going to be far better than humans because they don't care about black, gay, atheist, etc. A human might well be intellectually lazy enough to group all blacks together as poor credit risks, but an algorithm isn't if you leave that irrelevant data out. In fact, using these algorithms would mean that if there is widespread discrimination against a group, that the company using the algorithm can actively pick out the people who will be able to repay loans which will generate additional profit. They've given themselves customers that other people are denying.

      This doesn't look like being careful or taking preventative measures against misuse. Instead it reeks of not liking the results and not caring to address the underlying causes of those results. Giving loans to bad lending risks isn't going to magically make them responsible or more likely to pay back their loans. If black people, Methodists, or white people from WV happen to fall into that category more often than other groups, then you need to actually look at what is contributing to that result if you actually want to fix the problem.

    5. Re:More idiocy by swillden · · Score: 1, Flamebait

      What if, just maybe, beyond skin color, there are genetic differences between the races in how people value life, truth, and their propensity to violence. This is where people want to bury their heads in the sand. It's time we get honest and accept these truths.

      Oh, bullshit. There's nothing "head burying" about wanting to treat people fairly. Even assuming the racial differences you posit exist (assuming race actually exists as a coherent and well-defined thing, which is debatable [1]), the racial differences are utterly swamped by individual differences, so it makes no sense whatsoever to make assumptions about individuals based on racial characteristics. Supposing, to take one example, African Americans score lower on IQ tests because they're not as smart, on average, as white Americans, rather than because the tests are culturally-biased. Does that mean Thomas Sowell is dumb?

      The same applies across the board. Outside of the specific characteristics that we use to categorize people into races, all of the various potential statistical differences between groups are utterly dominated by individual differences.

      And even if that weren't true. So what? Wouldn't you rather live in a world where every individual has an equal opportunity regardless of the elements of themselves that they can't change or control? For that matter, wouldn't you rather live in a world where society even attempts to make reasonable accommodation for individual differences, and even arguable deficiencies?

      I sure as hell would.

      So this is absolutely the right thing to do. Algorithmic decisionmaking is a fantastically useful and powerful tool that we're applying to improve human lives. Scrutinizing those algorithmic decisions to search for evidence of bias and then figuring out how to offset, mitigate or manage that bias is the right thing to do -- and that's true even if the bias has some legitimate statistical basis. And it's especially true if it does not, but we'll never know if we don't look.

      [1] One of the most interesting studies of recent years about race came to the rather surprising conclusion that going to prison makes you black. A longitudinal study of racial self-identification and social identification found that many people who self-identified as non-black before being sent to prison self-identified as black after going to prison. Further, those self-identifications correlated strongly with third-party identifications by census workers, social workers and others who were asked to racially categorize people. People who are consistently non-black before imprisonment come out of prison as black. This is powerful evidence that a significant element of what we call "race" is a purely social construct.

      --
      Note to ACs: I usually delete AC replies without reading them. If you want to talk to me, log in.
    6. Re:More idiocy by Mal-2 · · Score: 2

      It is racist to only test black people for sickle cell. The condition is common to areas outside Africa where malaria is still prevalent, you know.

      --
      How is the Riemann zeta function like Trump rallies? Both have an endless number of trivial zeros.
    7. Re:More idiocy by swb · · Score: 2

      The credit scoring industry is always eager to find one more factor they can include in calculating credit risk and they seem fond of high-correlation variables unrelated to actual loan performance, like driving record. I'm mostly convinced this is just to find a way to charge a premium to good credit risks.

      But there is only so much money good credit risks will borrow (which is partly why they're good credit risks, it's a kind of self-selective behavior) and lenders would like to loan more money in order to make more money. So they start looking for alternative credit scoring variables they can correlate to good loan risks, independent of past or no credit history.

      So you wind up with variables that turn out to be reasonable predictors of credit performance that are race-blind but wind up to coincidentally highly correlated with race, like zipcode. Happen to live in a majority black neighborhood? Based on broad economic measures, blacks probably are worse credit risks just because they're overall poorer, so just sharing the neighborhood makes you disadvantaged by a "blind" variable like zipcode, even if you're not black. If you are, it is indistinguishable from racial discrimination.

      Don't get me wrong, I don't disagree with your larger point. The problem really seems to be that "innovators" wind up using variables that seem neutral but are actually heavily biased. They should probably check for high levels of racial correlation when developing their algorithms and toss those that wind up correlating on race, or at least do so if it means preventing access to something.

    8. Re:More idiocy by John+Jorsett · · Score: 1

      Here's one response I would expect: the choice of what data used as inputs is itself discriminatory. Everyone knows that fewer or more [insert race here] people do [insert behavior here], and by you choosing that behavior as an input, you're automatically discriminating against that race.

    9. Re:More idiocy by Anonymous Coward · · Score: 1

      Please explain how an algorithm can be biased if you leave out ethnicity from the input data

      Easy. Any fact that contradicts The Narrative is raaaaacist.

    10. Re:More idiocy by GameboyRMH · · Score: 2

      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...

      --
      "When information is power, privacy is freedom" - Jah-Wren Ryel
    11. Re:More idiocy by Khashishi · · Score: 2

      Well, in US labor law there's something called disparate impact. There is a grey area here and the ultimate answer will come from a social compromise, not from philosophy.

    12. Re:More idiocy by JoeDuncan · · Score: 1

      Disagree

      If someone feeds me a "chocolate" chip cookie made with dog shit; it's the *recipe* that *I* want held accountable!!!

    13. Re:More idiocy by Actually,+I+do+RTFA · · Score: 1

      You don't think that algorithms can use other proxies for race, age and gender? And that pattern identification algorithms aren't exceptionally good at finding those proxies?

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      Your ad here. Ask me how!
    14. Re:More idiocy by Whorhay · · Score: 5, Informative

      I read an article about this kind of problem awhile back, only the algorithm being discussed was used by court systems to project the risk of a person becoming a repeat offender. A major problem with the system was that it was being used in ways that didn't match its intended use. But there were also real problems with the training data that was used. Historic racism for example distorts crime statistics for as long as they are viewed as relevant. Even today you have programs like 'Stop and Frisk' which perpetuate racist policing and all the resulting prosecutions from that continue to weigh the statistics down.

      None of that should be surprising, and I'm not really against using algorithms for helping to make decisions. But those algorithms should not be black boxes, especially whenever they are used by government or institutions backed by government. And there should always be a route for an individual to obtain a breakdown of the algorithms analysis pertaining to them so that it can be contested when flawed.

    15. Re:More idiocy by AmiMoJo · · Score: 1

      You don't need to know race to be racist. It can often be inferred from other things like address or occupation or name.

      It can also happen with feedback loops. Chief of police has a limited budget and sees that a predominantly black area has a 5% higher crime rate, so decides to divert more resources there. Because there are more police the the crime detection rate goes up, and now there is 15% higher crime on paper, with more black people being arrested. The cops get the feeling that those people are more likely to be criminals, start doing crack downs and harsher treatment as a result. It's deliberately racist, but ends up affecting mostly black people.

      --
      const int one = 65536; (Silvermoon, Texture.cs)
      SJW, n: "Someone I don't like, and by the way I'm a fuckwit" - AC
    16. Re:More idiocy by AdamStarks · · Score: 1

      I like how I literally answered the question (how an algorithm can be effectively biased even if it's not obvious from the inputs, and without taking any sides on whether New York is doing a good or bad thing), and got modded down to Troll.

    17. Re:More idiocy by karmatic · · Score: 1

      Algorithms don't discriminate if you remove the kind of data (race, age, etc.) that would allow them to make categorizations or judgments based on that data.

      That's just it, they still do, and that's what pisses people off.

      You can train an algorithm for example to try to detect the likelihood of criminality (as is the case for sentencing recommendation tools). You can try to take race out of the data, but it's still going to be there. If you don't give it race, it will start using names. Remove the names, and it can weight things like lack of college or economic condition more. You can deny it that, and it will weight zip code more. Remove that from the training data, and it will weight familial status higher. Remove that, and you have age of first offense. Remove all of those, and it will weight certain crimes higher.

      At the end of the day, if you have a system designed to predict criminality, it's going to be racist, because there are underlying differences in the behaviour of individuals (as a class) of different demographic groups. You can try to stop those biases, but it will simply mean that the training process (which is designed to explain data) is forced to use proxies for those differences, instead of those specific differences. In other words, if black people commit more crimes (which they do, as a class), and you try to train a crime prediction algorithm on data with any predictive use, it's going to end up trying to assign that increased criminality to whatever attributes it can correlate - trying to do its job of accounting for the data.

      It's no different than trying to do a "Marfan syndrome" predictor. The disease disproportionately affects tall people. If you remove height from the data you feed it, it's just going to try to achieve the same output to explain the data. It will look at what sets tall people apart from the rest of the population, and use that to explain the variability.

      If for some reason the best correlation is that tall people are more likely to be skiiers, it will weight skiing as a risk factor for Marfans. It will still get the tall people, but now it will be less accurate and will hit people it shouldn't.

    18. Re:More idiocy by karmatic · · Score: 1

      " the racial differences are utterly swamped by individual differences, so it makes no sense whatsoever to make assumptions about individuals based on racial characteristics."

      That's an oft-quoted and rather misleading retort to observations of population differences.

      As an example, suppose we have two populations - A and B. Population A has a mean height of 5.5 feet, with a standard deviation of 6 inches. Population B has a mean height of 5 feet, with a standard deviation of 4 inches. In this hypothetical scenario, distribution is normal, and the best basketball players are 7 feet tall or taller.

      With a scenario like that, there is more difference within the populations than between them. That doesn't change the fact that 0.13% of population A are over 7 feet, while population B is a small fraction of that.

      Likewise, suppose we have two populations - one with a mean IQ of 100, and one population with a mean IQ of 85. Both have a standard deviation of 15.

      If 85 is around the point at which people are economically productive, and 130 is the point at which people are able to drive forward technological progress and growth, there will be a huge difference in the outcome of the two populations.

      For the population with a mean IQ of 100, 16% of the population will be below the economic productivity threshold, and 2.3% will be responsible for driving the society forward. For the population with a mean IQ of 85, 50% of the population will be below the productivity threshold, and 0.13% will help drive society forward. One can build a functional, stable modern society, and the other cannot.

      The problem is that while we should treat people as individuals, we should also build societal institutions to serve populations. Algorithms designed to learn from data are going to have some of these biases.

      AI is likely going to make a lot of the discrimination worse, because it has access to much better predictors than skin colour. If (for example) black people as a class are more likely to commit crimes, but identification of who is black is difficult, the predictive value of judging by skin colour can still be relatively low (since we don't know who is black and who isn't). AI, on the other hand, can use proxies to get at the underlying data, which will have the effect of amplifying the effect of these biases.

      A quick example of a situation like this is the "white" crime rate. Before Hispanics were broken out separately, the white to black offender ratio (even for crimes like murder, which have low selective enforcement) reflected negatively on the black community. As crime statistics have started to identify hispanics as hispanic instead of white, the white crime rate has dropped, increasing the black-white offender disparity.

      If there are traits that correlate better with race than skin tone (or even combinations of traits), we can end up with situations where a black individual is rated at a much higher risk of "potential offending", even if we completely remove race from the data itself. We see this now with software used in sentencing - it doesn't matter if we have skin colour data. The training will try to explain the higher rate of offending, and will use whatever traits it can to do so.

    19. Re:More idiocy by bingoUV · · Score: 1

      the best basketball players are 7 feet tall or taller

      This is a good proxy. Why ?
      1. Height actually helps basketball playing. Presumably because game designers chose to keep the baskets high - though the advantages by height in acquiring control of ball cannot be denied.
      2. Many people measuring one person's height will come to the same conclusions. So height means something - even though it varies in evening, morning, while thirsty etc.

      If 85 is around the point at which people are economically productive, and 130 is the point at which

      This is a bad proxy. Why ?
      1. Measured IQ does not help in being economically productive, intelligence might.
      2. There are various types of intelligence, we barely know all types. Presumably different types of intelligence help one be economically productive in different types of professions, but more data is needed.
      3. IQ will be measured for different people differently - so in itself the number means nothing. Notably, for races, just adapting the IQ test to the upbringing of the subject improved the measured IQ of non-Caucasian races drastically.

      --
      Bingo Dictionary - Pragmatist, n. A myopic idealist.
    20. Re:More idiocy by bickerdyke · · Score: 1

      Please explain how an algorithm can be biased if you leave out ethnicity from the input data,

      That's simple. Because replacing race in input data with some proxy for the same data is not leaving that data out. Not quite the opposite, but if you still can derive race from them. The problem is that any valid data point could become such a proxy.

      --
      bickerdyke
    21. Re:More idiocy by swillden · · Score: 1

      Meh. It's a rather obvious (to anyone who's studied statistics) fact that small differences in means of normally-distributed populations create large differences in the proportion of populations far from the mean. Small differences in variance do the same.

      But that's only relevant when you're looking for people who are far from the mean. In professional basketball, you're looking for people who are 600 standard deviations from the mean in basketball ability (assuming the NBA really has the best 500 players in the population of 200M adults, they represent the top 0.00025% of the population, which is 632 standard deviations from the mean). In most situations, 600-sigma is not the goal.

      That's an interesting example, though, because it's one where the distributions clearly end up favoring one race, yet no one complains (other than racists). If you were to create a well-performing professional basketball scouting algorithm it's vanishingly unlikely that the algorithm would take much note of a race parameter, even if one were explicitly provided. Why? Because height is a much stronger indicator than race, and actual basketball performance is the best indicator of all, and we have lots of basketball performance statistics.

      So, an analysis like the one NYC is proposing of the basketball scouting algorithm results would show a marked bias in favor of black players, and a marked negative bias against asian and latino players. It would appear -- at first blush -- to be a racist algorithm, even if race were not provided. But as long as the analysis doesn't stop there, it's fine. Because a little deeper look will show that the algorithm is attempting to identify extreme outliers, where we absolutely expect that small differences in distribution of relevant abilities/characteristics in populations will result in large disparities in representation of those populations.

      But if only extreme outliers make their mortgage payments on time, we have bigger problems than algorithmic bias. Further, analysis of algorithmic bias will, I expect, often offer strong clues to how to solve social inequality. If, for example, a mortgage-approval algorithm that is not provided with racial information is still racially biased (say, against blacks) when evaluating blacks and whites that have the same economic status, then we have an opportunity to dig a little deeper into why there is a difference. Perhaps it's spurious and the algorithm is just rejecting applications from a part of town with a high black population, because many people in that part of town have low or inconsistent incomes and the reliable earners from the same area are being tarred unfairly with the unreliability of their neighbors. That sort of thing often arises from poor training practices (and most training practices are poor), and those should be identified and fixed.

      The high likelihood that many of the algorithms are bad, in the sense that they produce inaccurately biased outputs, is reason enough for a little oversight, at least until there is sufficient competition to drive bad algorithms out.

      But maybe it's real, and derives from deeper issues. Maybe because their communities are poor, black borrowers don't have the same financial resources to help them out when hit the occasional rough patch. If my kids can't make their mortgage payment one month because the car broke down, they know I can and will help out (to a limit; I expect them to gradually build more financial stability than that -- and I will give them financial advice which is another form of financial resource). But, what about the young black man whose dad is a doctor and has exactly the same sort of financial backstop that my kids do? The fact that such things are less common in black communities than white communities doesn't mean the individuals who do have those additional resources should be penalized. So... perhaps the algorithm is being inaccurately biased because it doesn't have enough data.

      Or -- even better -- perhaps rathe

      --
      Note to ACs: I usually delete AC replies without reading them. If you want to talk to me, log in.
    22. Re:More idiocy by CanHasDIY · · Score: 1

      OK, so maybe that was a bad example, but the point remains valid - genetics, including the genes that manage racial features, are important to consider in medical practice.

      --
      An enigma, wrapped in a riddle, shrouded in bacon and cheese
    23. Re:More idiocy by ZorroXXX · · Score: 1

      Where the hell did you get individual probabilities from?

      Just because the average sick leave at Company X is y days per year, you cannot in any credible way predict that Mr Smith, working for Company X, will have exactly y sick days next year. If you believe that you can extrapolate probabilities for an individual out of said person's group memberships (be it employment, sex or race) you have a serious misunderstanding of how statistics work.

      --
      When you are sure of something, you probably are wrong (search for "Unskilled and Unaware of It").
  6. Re:Now hold Trump accountable for TREASON by Hal_Porter · · Score: 1, Insightful

    Yeah, it was outrageous when Trump was caught on an open mike promising Medvedev 'more flexibility' after the election. Collusion and treason!

    Oh wait, that was Obama

    --
    echo -e 'global _start\n _start:\n mov eax, 2\n int 80h\n jmp _start' > a.asm; nasm a.asm -f elf; ld a.o -o a;
  7. Re:Now hold Trump accountable for TREASON by jfdavis668 · · Score: 1

    You do realize you can only commit treason in times of war. Unless congress declares war on Russia, you are not going to get far.

  8. Re:Now hold Trump accountable for TREASON by ArmoredDragon · · Score: 1

    I don't know about him, but my portfolio (one small-cap growth ETF, one large-cap growth ETF, one eurozone large-cap growth ETF, one high dividend ETF, and a few stocks) gained 35%-40% over the year 2017.

  9. So, let's study the problem and see if an effect by XXongo · · Score: 1

    Can people figure out how it discriminates against certain race or gender?

    The proposal here is to do a study to understand that, yes.

    You did notice that this article was about studying the problem to see if there is algorithmic discrimination, right?

    However, let me also point out that since the example discussed in the text was about DNA testing, I would point out that race and gender are encoded in DNA, so "does not have race/gender input" is not applicable here.

    In other cases, however, yes, it turns out that there can be race and gender encoded into input data even if it is not explicitly listed as "enter race and gender here." You could look at the articles cited earlier, such as https://www.theatlantic.com/bu... or even look at the Yale Law review article about the book on the subject http://michiganlawreview.org/w...

  10. Re: Now hold Trump accountable for TREASON by Zero__Kelvin · · Score: 1

    Who the he'll told you that? Even if it were true it is 2017. We are literally always at war.

    --
    Guns don't kill people; Physics kills people! - John Lithgow as Dick Solomon on Third Rock From The Sun
  11. "Weapons of Math Destruction by Gramie2 · · Score: 3, Informative

    A very good book that discusses the problems behind the blind implementation of algorithms is Weapons of Math Destruction by Cathy O’Neil.

  12. Re:Democrats are treasonous and love bump stocks by cayenne8 · · Score: 1, Offtopic

    ee subject & demand that your government BANS BUMP STOCKS IMMEDIATELY. Banning bump stocks is the ONLY way to prevent future mass shootings like the Las Vegas shooting.

    Hmm....I guess you're right, as that there had not been a single mass shooting to date prior to the Vegas shooting that seemed to involve bump stocks.

    Hmm...I guess we'd better ban fingers and belt loops and sticks that can emulate that bump stock too.....

    Strange, we'd not heard of many crimes involving the bump stocks prior to this, even though they have been around for years and year now....hmmm.

    Im not a fan of them so much myself, but aside from the special sniper case set up in the Vegas shooting, in general bump fire stocks aren't reliable enough to use in a crime situation or even home defense.

    If I were a criminal (you know the ones that DON'T follow the law by definition)....I'd go the route of modifying my gun to truly be full auto....much more effective and reliable.

    The Vatican doesn't want bump stocks banned & is spending millions of dollars to LOBBY AGAINST banning bump stocks.

    That being said....this connection to the Vatican is a new one on me....

    I'd love to sign up to your newsletter on that one....

    ;)

    As far as conspiracy theories go....and there do seem to be some strange facts around this case for sure...the main thing I see as been at all a suspicious coincidence, was that for the first time in ages, some pro gun legislation was about to go through for votes....including the SHARE act, which I think included one or more of the hearing protection acts that would have relaxed the hoops to jump through to buy and own a suppressor (silencer).....and of course that all got tabled after the nut in Vegas did what he did.

    OH well.....like is sure interesting.....

    --
    Light travels faster than sound. This is why some people appear bright until you hear them speak.........
  13. Re:Easy by Anonymous Coward · · Score: 1

    I thought IQ discriminates mostly against blacks who tend to vote liberal. In fact, we can't even use IQ tests for things like employment anymore because the blacks just can't compete.
    IQ tests. Perfectly valid if they put conservatives in a bad light. Discriminatory, racist, pseudoscience, useless, completely subjective, etc. when they tell us things we'd rather not hear.
    But whatever suits your narrative.

  14. "racially biased" by Anonymous Coward · · Score: 1

    I read that as: statistically honest

    1. Re:"racially biased" by ZorroXXX · · Score: 1
      --
      When you are sure of something, you probably are wrong (search for "Unskilled and Unaware of It").
  15. Re:Now hold Trump accountable for TREASON by Hal_Porter · · Score: 1, Offtopic

    There are things Trump can legally do for his Russian buddies, now that he's President, that he couldn't do before. He seems to have colluded with them before.

    Citation needed.

    --
    echo -e 'global _start\n _start:\n mov eax, 2\n int 80h\n jmp _start' > a.asm; nasm a.asm -f elf; ld a.o -o a;
  16. wrong solution by supernova87a · · Score: 3, Interesting

    Well, the issue I foresee in this effort is that while the algorithms will be perfectly fine, it's the policies created to make up for well functioning algorithms that will be the problem.

    Because what policymakers will quickly find is that having equal algorithmic treatment or having equal standards for all does not lead to the outcomes they want, as people of different demographics, backgrounds, capabilities do not take up services or have success against different programs in the same way.

    This is the problem with policy always -- a tendency to believe (at least in recent liberal democracy) that people are all drawn from the same starting set and have equal propensities for doing / being / acting / achieving / using certain things. And when policymakers find that to be the unavoidable truth, democratic pressure forces them to find ways around this truth and distort the outcomes.

    No algorithm will get around that.

    1. Re:wrong solution by AmiMoJo · · Score: 1

      On the one hand it's wrong for liberals to demand acknowledgement of people's different circumstances. Everyone should be treated the same, for fairness.

      On the other hand, liberals think everyone is the same and behaves the same way, and try to enact policies based on this assumption. People are different and that must be acknowledged.

      Both of those things can't be true.

      --
      const int one = 65536; (Silvermoon, Texture.cs)
      SJW, n: "Someone I don't like, and by the way I'm a fuckwit" - AC
  17. Re:Now hold Trump accountable for TREASON by phantomfive · · Score: 3, Insightful

    I don't care if Trump goes to jail, but as an American, I don't consider Russia our enemy. From a practical standpoint, we stand to gain more by working with Russia than working against them.

    --
    "First they came for the slanderers and i said nothing."
  18. Re:Democrats are treasonous and love bump stocks by ArmoredDragon · · Score: 1

    He was using AR15s, so I'm not sure why he didn't just buy a 3MR trigger. Sure, he'd fire a tad slower, but he'd fire a lot more accurately.

  19. It's not that simple by rsilvergun · · Score: 1

    If it was we wouldn't be having this conversation. Facebook can already guess your race, age and even sexuality based on the data they have about you even if you didn't tell them any of that. America is more segregated today then it was in the 50s, and that's not by choice, it's by design. This is what people mean by 'institutionalized racism'. It means racism is carefully built into the institutions rather than enshrined in law.

    So Blacks can't get loans or buy decent houses. Gays can't take advantage of marriage tax advantages or health care advantages, and women face a large pay gap. But at no point are there any laws in place to make all this happen, it's all done organically. And if anyone complains you just point to your data set and say 'We don't collect race, gender or sexuality'.

    --
    Hi! I make Firefox Plug-ins. Check 'em out @ https://addons.mozilla.org/en-US/firefox/addon/youtube-mp3-podcaster/
  20. Re:Now hold Trump accountable for TREASON by x0ra · · Score: 1

    Maybe a good start would be not to sell Russia US' uranium... oh, no, wait, Clinton did that.

  21. Re:Now hold Trump accountable for TREASON by Magnus+Pym · · Score: 1

    Would you have been saying the same thing if it had been China or India, not Russia, whose intelligence agency aided Trump?

  22. And for POSIX systems ... by fahrbot-bot · · Score: 1

    ... they will creat accountability algorithms.

    --
    It must have been something you assimilated. . . .
  23. I spent the whole day... by LordHighExecutioner · · Score: 1

    ...fighting with a FFT-based algorithm that causes plenty of troubles. After reading TFA I started wondering if my algorithm does not work as expected just because it is just discriminating me. I will ask mr. Vacca about...

  24. Re:Democrats are treasonous and love bump stocks by olsmeister · · Score: 1

    When you're a homicidal maniac spraying bullets into a crowd, accuracy is secondary to rate of fire. Come on dude, this is mass shooting 101.

  25. What if the algorithm is provably right? by John+Jorsett · · Score: 1

    If a model of, say, the likelihood of recidivism or the probability of loan default results in disparate results for different races, yet can be shown to be accurate in terms of ability to predict, is that discriminatory? I can see that happening with A.I. systems where the datasets are fed in and the black box then spits out results that, while accurate, are completely opaque as to how the results are obtained. Is congruence with observed reality a defense against charges of racism?

    1. Re:What if the algorithm is provably right? by Baron_Yam · · Score: 1

      >If a model of, say, the likelihood of recidivism or the probability of loan default results in disparate results for different races, yet can be shown to be accurate in terms of ability to predict, is that discriminatory?

      Yes. Because as an intelligent human, you know there are likely other factors at play for which racial identity is a weak proxy, and you should be using those factors rather than skin colour. So you can get a result that applies to that individual rather than a more or less arbitrary group they can be assigned to.

      An 'AI' black box won't even see that possibility, and some human will take the output like it is from an all-knowing Oracle because doing so removes responsibility for the decision from their shoulders, and then you'll get discrimination.

    2. Re:What if the algorithm is provably right? by Khashishi · · Score: 1

      I think that racism, sexism, other-ism... needs to be understood as a social compromise. Life isn't fair, but artificial institutions should be as close to fair as practical to promote happiness. It's undeniable that men are on average stronger and faster than women. So, it makes sense to have separate categories for women in sporting events. This isn't to say that we need to give everyone a chance to feel special, but the fact is that women are a huge class of people with unique powers. With that being said, being a women shouldn't disqualify someone from competing in a men's sport (although men are disqualified from a women's sport). Why is that? Because the whole point of the women's category is to give them a lower competitive level. The men's sport is therefore more glorified. So, if a woman is good enough to compete in a men's category, she should be allowed to. To say that this woman cannot compete because the average woman is not competitive is discrimatory. It should be based on her individual ability.

      It is discriminatory to use a demographic category as a proxy for a correlated quantity, EVEN IF there is causality. If black people are on average poorer than white people, it is discriminatory to deny a loan to every black person (or even reduce the score for every black person) because a particular black person could be wealthy. Basically, it is laziness (and bigotry) to use the person's race as a shortcut for the particular financial indicators rather than the indicators themselves, just like it is laziness to use a person's sex as a shortcut for their athletic ability.

      For artificial intelligence, there's a certain number of input parameters and output parameters. It's easier to train a system with just a small number of input parameters (such as race and sex) but you'll just get these broad generalizations which are highly discriminatory. Given enough work, it should be possible to use statistics and linear algebra to pull out the actual factors that determine the outcome. And at that point, we can look at why these factors may be correlated with the broad demographic groups such as race. Likely, there is a way to address this.

  26. Re: Now hold Trump accountable for TREASON by Anonymous Coward · · Score: 1

    interesting. So I'm guessing trump is the reason?

  27. Re:So Max-Scene Waters is a Republican now? by HornWumpus · · Score: 1

    Like I say, the Ds have lost control of their lunatic fringe. Which is what makes this post plausible.

    As the lunatic Ds run out of energy, Rs will fill the gap. Just as Ds pretend to be clansmen to push their agenda, Rs pretend to be neoStalinists/Antifa. Which doesn't mean that real clansmen and commies don't exist, just that they aren't THAT stupid...granting some are, like you say Waters.

    --
    John McAfee 'It was like that time I hired that Bangkok prostitute; to do my taxes, while I fucked my accountant'
  28. Re:Democrats are treasonous and love bump stocks by cayenne8 · · Score: 2

    When you're a homicidal maniac spraying bullets into a crowd, accuracy is secondary to rate of fire. Come on dude, this is mass shooting 101.

    Oh, I agree.

    Thing is...a bump fire stock, by nature of how it works....isn't really that great or reliable if you are trying to move around with your gun.

    If you are set up in a sniper area like he was, with multiple weapons fitted with them, to allow cooling and not having to reload as often and being somewhat able to stand stationary while using them, then they are dangerous as we saw.

    However, you really can't be moving, walking or running trying to use one in a crowd....they just don't work that well, again, by nature of how they work.

    So, aside from set ups like the LV shooter used, they generally aren't that effective for general use.....converting to FULL AUTO would be the best way to go, and of course, that is already ILLEGAL.

    And a bump stock doesn't increate rate of fire THAT much. There was a demonstration not long back, that showed:

    A regular semi-auto AR15 could be shot about 5 rounds per second.

    A bump stock AR15 could fire about 7.5 rounds per second.

    A Full Auto fired about 15 rounds per second.

    So....combined with their problems, that's why you've not seen much prior crime committed with a bump stock...and likely banning them won't prevent much either. It will primarily ONLY keep law abiding citizens from having a bit of fun at the gun range.

    --
    Light travels faster than sound. This is why some people appear bright until you hear them speak.........
  29. Re:Now hold Trump accountable for TREASON by JackieBrown · · Score: 1

    Yeah - mine too. I'm kicking myself for pulling out a bunch of funds of my IRA

  30. Maybe pre-AI was racist? by galabar · · Score: 1

    AI doesn't know to "look the other way." When people are in charge, they can take a subtle hint (give more to this group, don't mention this group if they commit a crime, etc.). We just need to inject a Social Justice Warrior loop into these AIs.

  31. Re:Now hold Trump accountable for TREASON by Hognoxious · · Score: 1

    I'm not sure they see it the same way.

    --
    Confucius say, "Find worm in apple - bad. Find half a worm - worse."
  32. Re:Now hold Trump accountable for TREASON by phantomfive · · Score: 1

    Oh? How do you think Russians see it?

    --
    "First they came for the slanderers and i said nothing."
  33. Re:Now hold Trump accountable for TREASON by Hognoxious · · Score: 1

    They see everyone as their enemy, and most of the time they're seeing double.

    --
    Confucius say, "Find worm in apple - bad. Find half a worm - worse."
  34. Re:Now hold Trump accountable for TREASON by phantomfive · · Score: 1

    Nah. They see (correctly) that the US is the most powerful country by far, and that the US is also somewhat schizophrenic, with actions that don't make sense and aren't consistent. They are trying to adjust themselves around that reality as best they can.

    --
    "First they came for the slanderers and i said nothing."
  35. Re:Now hold Trump accountable for TREASON by Gryle · · Score: 1

    The Russian people, in general, don't have a particularly hopeful view of the future and historically seem to prefer stability over autonomy, provided the living conditions aren't too bad. To borrow an internet meme, the history of Russia can be summed up in a single sentence "And then things got worse." Russia has had two major governmental collapses in the last century,* one of which the US was openly attempting. Russians see the US, and democracy in general, as an instigator of chaos. There's an excellent article in the Atlantic this month if you've got 30 minutes to read it

    *Granted, there are African nations that have two government collapses before lunch, but Africa is its own basket of problems.

    --
    Only two things are infinite, the universe and human stupidity, and I'm not entirely sure about the universe - Einstein
  36. Re:Now hold Trump accountable for TREASON by david_thornley · · Score: 1

    To be more specific, my available evidence (which is limited) suggests to me that Trump colluded with Russia. Part of this is meta-evidence, including people lying when they should have had no need to, which a court can't consider but I can.

    --
    "When you have eliminated the unacceptable, whatever is left, however improbable, must be the truthiness" - Holmes
  37. Re:Now hold Trump accountable for TREASON by david_thornley · · Score: 1

    The US sent troops to Vladivostok, IIRC, during the Russian Civil War. It had at least a small hand in the first collapse (arguably, two collapses in a year).

    --
    "When you have eliminated the unacceptable, whatever is left, however improbable, must be the truthiness" - Holmes
  38. Re:Now hold Trump accountable for TREASON by phantomfive · · Score: 1

    You are right, that is a good article. Americans see Russia from their own self-centered view, but Russians are mainly concerned about themselves and their own problems.

    --
    "First they came for the slanderers and i said nothing."
  39. Re:Now hold Trump accountable for TREASON by Gryle · · Score: 1

    While Allied intervention exacerbated existing problems, it's a stretch to say that it had a hand in the collapse (assuming you use the phrase "had a small hand in" to mean "was a partial cause of"). Russia had serious domestic problems and the brutality of WWI didn't help. One could arguably blame Germany for sending Lenin back, but by the time he arrived on the scene, the whole edifice of state was teetering anyway. Edward Crankshaw's "Shadow of the Winter Palace" is a good summation of the conditions that led to revolution.

    --
    Only two things are infinite, the universe and human stupidity, and I'm not entirely sure about the universe - Einstein
  40. Re:Now hold Trump accountable for TREASON by Gryle · · Score: 1

    I also recommend "In Search of Putin's Russia", if you've got the time. Another thing we tend to forget in the West is the effect the downfall of the Soviet Union had on the Russian national psyche. Communism may not have been very popular, but it was stability and there was a certain amount of prestige in being a citizen of a superpower. Imagine the US collapses one day, the economy tanks, and the Reconquista that Mexico's academia dreams of happens. What would that be like for the US, to suddenly find itself with distrustful nations at its border? Then imagine these newly independent nations of Texas, California, Arizona, what have you, start getting buddy-buddy with, say, China or Iran. How would the US react to something like that? This is a (very) rough approximation of the Russian situation following the collapse of the Soviet Union. Putin's demonstrating, very publicly, that Russia can and will square off against the US and that it's not some broken shell of a nation. Please note that I'm not excusing Putin or the Russian actions in Crimea. I'm just pointing out that he's hardly the mustache-twirling Snidely Whiplash that television news has made him out to be.

    --
    Only two things are infinite, the universe and human stupidity, and I'm not entirely sure about the universe - Einstein
  41. Re:Now hold Trump accountable for TREASON by david_thornley · · Score: 1

    While what you said is true, when we're talking about the feelings of the Russian people we need to know how they perceive things. At at least one time, they mostly believed that the US invaded their country during their civil war.

    On a side note, it's interesting to look at the role of Germany in making the Soviet Union the post-WWII threat it was. No other country was anywhere near as useful in helping the Soviet Communists..

    --
    "When you have eliminated the unacceptable, whatever is left, however improbable, must be the truthiness" - Holmes
  42. Re:Now hold Trump accountable for TREASON by Gryle · · Score: 1

    That's fair; I'll concede the point about Allied intervention. As to the Soviet-Nazi relationship, most counterfactual scenarios I can think of have them coming to blows at some point. Still, Hitler handed Stalin probably the greatest propaganda victory Ol' Joe could have hoped for.

    --
    Only two things are infinite, the universe and human stupidity, and I'm not entirely sure about the universe - Einstein