Still, though, the weak link remains that everyone has to trust these officials will actually uphold the constitution. Unless we can develop something more binding than swearing on a Bible, we're going to keep coming back to this same problem.
That's not to say I don't like the idea of a constitutional court, though. I just think we need to also add some sort of protections against blatantly unconstitutional actions.
While I think it should apply to non-US citizens, the fact that it technically doesn't is irrelevant as long as they're still willfully violating the rights of US citizens too.
In that case you can do a Show HN. The guidelines are only trying to prevent Show HNs for things that can't be used yet. If you want specific advice, you're welcome to email hn@ycombinator.com. (That goes for anybody.)
We might need to relax this rule. Good work can get off the ground in many ways. Drew Houston got initial traction for Dropbox with a video rather than with working software. Our intention isn't to be overly strict—it's mostly to detach "Show HN" from vaporware landing pages and market tests that don't have serious work behind them.
This isn't 2004. The state of development of the various GNU/ Linux distributions has reached a point where everything "just works". I have yet to see an installation with driver problems. Not to mention that the battery life on my ThinkPad easily compares with, if not exceeds, that of a Windows installation.
> The state of development of the various GNU/ Linux distributions has reached a point where everything "just works".
Not really. I'd argue it has actually gotten worse in recent years, unless you enjoy using ancient hardware.
Support for 802.11ac chipsets in particular has been bad in my experience: Intel only works properly with very recent kernels, Broadcom and Qualcomm/Atheros tend to be buggy or they don't work at all. Or they're just barely working and essential features like, oh, using the 5 GHz band, are missing. And these are the three vendors whose chipsets you'll find most commonly in Laptops at the moment.
I guess it's possible I was just very unlucky.
OP also mentions Bluetooth, which I would agree is a bad joke on Linux. The whole stack seems to be garbage.
And of course, if you have a Laptop with anything other than Intel graphics, you might as well not even bother.
All of this – except maybe the Bluetooth part – is of course mostly a problem of hardware vendors being indifferent or even hostile towards Linux, but that does not change the fact that very often it does not "just work". You need to pick your hardware very carefully.
Both my Windows and OSX machines know that if I connect my bluetooth speaker to them, to play the sound through the speaker. Likewise, they know that if I plug in a Logitech USB dongle into the machine, that the sound and mic should go through the dongle.
Elementary is better than most at having some sort of easy to use, functioning bluetooth setup, but every time I use one of these devices I have to go into sound settings and switch them to the device. It's a pain in the ass that other companies have figured out.
How can we be a supposedly post-racial society and yet have this level of scrutiny on the racial makeup of a company that is clearly not actively discriminating based on race? I don't mean to be hyperbolic, but this isn't far off from having political overseers at production facilities in the former Soviet Union.
Because if there are large systemic racial inequalities (not that I think employment at Google is worthy of the title, compared to things like education and incarceration rates), then we manifestly aren't in a post racial society.
Given the history of legal and social discrimination in the US, the impetus is on the people claiming we live in a post-racial society to back that fact up.
One then has to ask what does it mean that there are racial inequality? It is not in general, it has to be constrained to a particular domain.
Say look at customers in a store and notice there is inequality, more people of a certain race visit it. What does it mean? Should something be done about it? Then, there is like you said, prisons. There is something disturbing going on, and something has to be done there, more urgently, than say figure out why there is racial misrepresentation at that one mall or store.
Ok two extremes. What about Google? There is racial inequality at Google. What does it mean? Should something be done about it? Should Google hire based on racial profiles. Minority X gets Y slots based on some weighted criteria. Will that solve anything? Will it make things worse. Should anything be done at all at Google? Is that a big priority. Should we be looking at prisons instead...
Google is looking to address inequality in the tech sector, because that's where its expertise and experience lies. Its is not doing this by hiring based on racial profiles. It is doing this by trying to encourage people from diverse backgrounds to a) enter the field in the first place and b) actually apply for jobs at Google.
> It is doing this by trying to encourage people from diverse backgrounds to a) enter the field in the first place and b) actually apply for jobs at Google.
Is there anything in the data (I haven't looked too much in dept) about the application pool. Because it seems to me, b) kind of sidesteps deeper issues and kind of says (figuratively) "Minorities just don't know to apply to Google. If that is the sentiment I am not sure I agree with it.
(Unless of course Google and just then turn around and implement racial quota hiring decision and then in effect we back to that. As "just apply, we'll make sure you get in").
I have seen companies do that. One company I worked for hired a minority into upper management. Her skill set, experience and competence was not up to par. Compared to the rest of the managers. The belief was that she was there as a token "minority" person. Not necessarily disagreeing with that. Maybe those kind of steps are needed. But just saying companies do that.
Now on a) I know Google does some good work. They have good programs for Women in tech. But not familiar too much with their program geared for racial minorities. Can you point me to some?
My understanding is that we have analysed our hiring process and found that the diversity of candidates is ~equivalent to the diversity of hires. In other words, there isn't bias in our hiring processes. The problem is we don't have enough candidates from diverse backgrounds applying.
Your view of a post racial society excludes any form of ethnic identity which influences occupational choices. IMO, that's not nessisarily a good thing. It's Basicly saying no culture has any value or no culture that differs from mine has any value which is vary ethnocentric.
No, no it doesn't. It's a perfectly valid answer (given appropriate evidence). The point is it's an answer to rebut data and it's one that it self requires data. In no way does it stand as an argument that we should not have the data in the first place.
Again, the presumption about a a post-racial society requires evidence. That evidence may be that ethnic identity issues explain discrepancies, but it can't be an argument because we live in a post racial society , data to the contrary should be ignored.
It is incredible that in American melting pot, there are some races that are constantly manipulated for political ends, and others are not. And witness: those races that are left alone, and not made into an issue, do quite well.
It is my sincere belief that African-Americans or Latinos if they were left alone would do much better.
those races that are left alone, and not made into an issue, do quite well.
Consider an alternative: those non-white races who predominantly arrived here as a result of passing modern immigration requirements, often having secondary education and a drive to succeed, tend to be more successful.
I technically agree with your statement, though. If we had never pushed out the people who were here before us, and never enslaved blacks, both populations would probably be doing much better.
My ancestors went to the United States in the days of Ellis Island and had just enough education to work as bakers and butchers. Many other Asians, Irish, and Jews worked as outright laborers, often in hazardous conditions. Many died as a result of the way society treated them.
The immigration system of the old days wasn't meritocratic; it was simply exploitative.
And really, so is the immigration system today, except that it exploits largely by keeping the threat of deportation hanging over the immigrant's head (including, yes, under the H1-B program for white-collar workers).
I fail to see how your comment is the least bit relevant.
in the days of Ellis Island and had just enough education to work as bakers and butchers
So in other words, for the time in which they lived, they were pretty skilled.
The immigration system of the old days wasn't meritocratic; it was simply exploitative
That's irrelevant to the parent comments claim that societal meddling has left some population groups behind. It's also irrelevant to my point distinguishing between people who were already here and pushed out, or forcibly brought here, compared to population groups primarily composed of modern, legal immigrants.
However, it doesn't matter. Coming here in "the days of Ellis Island" required a tremendous amount of dedication and daring, and the places they were coming from were likely even worse off. It was self-selecting for driven people.
Why should what matter? Google's composition? That wasn't the main point of the piece at all.
"How can we be a supposedly post-racial society and yet ..."
We simply are not a post-racial society, not by a long way. The way to get there is not to pretend that we are and hope it all goes away. Google's data is just more information that can be used in the discussion. It is not particularly surprising, though. I think that their publication of it is more significant that the data itself, in this case.
> a company that is clearly not actively discriminating based on race
1. There's no way to tell whether they are or aren't just from exposing this data.
2. Racism/Sexism is discussed a lot in American culture, but I fail to see how "ignoring" actual data (which Google is proactively choosing to share) would somehow fix these issues.
Forgot to mention that these questionnaires themselves are at fault - they perpetuate the concept of "race" while we should know better in the 21st century that races are an invention of the 18-19th Century. Look at actual genetic differences between people, and while you may certainly define subgroups here and there, it's certainly not as simple as having a dozen of groups defined mostly by the color of your skin and your appearance.
Races are BS, period. So these questionnaire make the BS go on and on.
2. The problem when you talk about the data is that you fix yourself on numbers, you try to set objectives and you end up with quota, instead of actually understanding that's the underlying problem.
You don't and you shouldn't start addressing these issues with numbers.
Numbers allow us to identify problems. Without numbers, there are no problems, so there are no issues to address; I see how that would solve the problem!
The problem is in these sorts of cases the numbers are generally useless. Even if we eliminated 100% of all racial discrimination from society, fewer African Americans would attend college because fewer of their parents can afford to send them, and those type of consequences would carry down for generations completely regardless of continuing racism.
So you say you want to stick with the numbers anyway and try to account for income level. OK boss, that will reduce your confidence interval by a good bit but we can do it. The trouble is poverty is not the only issue. The fertility rates are different. African Americans on average have more children than whites and Asians according to the most recent census (2.1 vs. 1.8), so for the same parental income level the money is split between more children, as is parental time and attention. African Americans are also significantly more likely to grow up in single parent families. That one's 65% for African Americans vs. 23% white and 16% Asian. Ouch. So we have to account for that stuff too. And those all interact. If you have three children being raised by one parent making $30,000/year as compared with two children being raised by two parents each making $50,000/year, expecting to get anything resembling the same results is bonkers.
> Even if we eliminated 100% of all racial discrimination from society, fewer African Americans would attend college because fewer of their parents can afford to send them, and those type of consequences would carry down for generations completely regardless of continuing racism.
Precisely. The issue with numbers is that people will focus on numbers and make the conclusions that "as long as it's not 50/50, it means there is some RACISM at work somewhere" without understanding the underlying causes.
It's ALWAYS the same issue with numbers and statistics: used in the wrong context, you can manipulate them to say what you want to say, instead of using numbers to explain the truth.
Experiments through data are by no means impossible when it comes to race or gender. That's the lifeblood of social science. Throwing your hands up and saying "too many numbers! no conclusions could ever be possibly found!" would be completely unacceptable in any other discipline. You're now picking and choosing which fields can even use basic statistics.
> Experiments through data are by no means impossible when it comes to race or gender. That's the lifeblood of social science.
It's also why hard science majors make fun of them.
> Throwing your hands up and saying "too many numbers! no conclusions could ever be possibly found!" would be completely unacceptable in any other discipline.
That's because just about any other discipline is capable of conducting a controlled experiment. The problem with statistics in social sciences is that you don't control anything. You can't just order families of a particular race to stop having more or less children than other races so that you can get a good control group, so you have no control group. You only have data from something you hope is a reasonable approximation of a control group, without even any good way to tell when it isn't.
> It's also why hard science majors make fun of them.
Hard science recognizes social science work when solid data is used and the methodology is well understood and effective. You're generalizing.
> That's because just about any other discipline is capable of conducting a controlled experiment
> You can't just order families of a particular race to stop having more or less children than other races so that you can get a good control group, so you have no control group.
You look at families of a race that had less children and compare them to families of the same race with more children. That would be a data experiment controlled for race. Read Freakonomics if you want to understand data experiments better.
> You look at families of a race that had less children and compare them to families of the same race with more children. That would be a data experiment controlled for race.
That's exactly how you expound the problem and get the wrong answer. How do you know that the factors causing parents to have more or less children are the same between races, or that those factors don't directly impact parenting ability? Suppose the predominant factor in low income Asian Americans having three or more children is a calculated decision that the couple's extended family has enough resources to responsibly raise that number of children (i.e. rich uncle), but the predominant factor in low income African Americans having three or more children is accidental pregnancy.
At first you had to take into account income level, but to do that you have to factor out fertility rate, and to factor that out you have to account for the different causes behind the differing fertility rate. If we then discover that the predominant cause of accidental pregnancy in African Americans is religious opposition to birth control or abortion, don't we have to then account for the causes and consequences of a higher degree of faith in religion?
Nobody has the resources to go all the way down the rabbit hole. But everywhere you look there is some factor that would change the outcome by 50% in one direction or the other if you take it into account. Which means you can make the numbers say whatever you want just by looking in the places you can expect to find support for the result you like.
> That's because just about any other discipline is capable of conducting a controlled experiment. The problem with statistics in social sciences is that you don't control anything.
Statistical controls are real controls, and are frequently used not only in social sciences, but in so-called "hard" sciences for large, complex, or distant systems that can't be conveniently be set up in a laboratory. Laboratory-style control is one particularly convenient mechanism for isolating particular independent variables, but its not a defining requirement of empirical science.
Using statistical controls is far more likely to lead to error because you controlled for three relevant variables when there were three thousand. This is drastically exacerbated by the political consequences of social science. Nobody can really gain any political advantage in publishing experimental results that show an erroneous gravity constant and are immediately disproven by contrary experiments (cf. climate change, the papers denying which are taken seriously by no mainstream scientists), whereas papers purporting to show that racism is or is not still prevalent are the sort of things that get bills passed and politicians elected. The consequence is that publishing a paper in social science that provides support for a politically unpopular conclusion tend to be Very Bad for the careers of the scientists, with political opponents tearing apart anything they might have missed (because papers supporting popular opinion miss nothing?) and otherwise making every effort to discredit them.
> In science, we call out qualitative reasoning as being biased and unscientific.
Ha! I'm a scientist by training, and your claim makes me smile. Most of Science starts by qualitative reasoning and observation. It's because you notice phenomena that you emit hypotheses as to why they occur, and then you design experiments to generate data and verify your hypothesis (i.e. whether your qualitative understanding is correct or not).
Right, we use qualitative reasoning at the beginning and try to temper our biases separately, but how can you do unbiased evaluation without numbers? Even the social sciences has to rely at numbers and statistics eventually.
> but how can you do unbiased evaluation without numbers?
First, collecting data must be made to answer a question. The current way of asking ethnicity based on unvalidated criteria (basically what you identify yourself as) does not mean anything. It's rubbish as data, because there are almost no "pure" individuals in the US anymore, people have been mixed for generations.
The way the current data is used is to reach a political agenda to say that we are in a state of inequality between races and sexes and that the government has to step in to fix things, hence you need the government to spend money and resources on this, etc... It's NOT a scientific study at work, it's data used for political purposes.
Plus, it's not unbiased either because it's not in an observational state. Individuals and companies are aware of these ratios in these companies and know that they are expected to do something about it. That's not science at work, it's social pressure at work.
> It's rubbish as data, because there are almost no "pure" individuals in the US anymore, people have been mixed for generations.
It's not rubbish. You can't simultaneously discuss statistics about black incarceration or female underrepresentation in tech while also denying that such classifications even exist in the first place. The lines blur sometimes, but pretending there are no lines denies reality.
> that the government has to step in to fix things
You're putting the cart before the horse. This is a private company's data, not any specific recommendation for government action.
>Plus, it's not unbiased either because it's not in an observational state. Individuals and companies are aware of these ratios in these companies and know that they are expected to do something about it. That's not science at work, it's social pressure at work.
First, some companies just plain don't care and don't feel any social pressure because their insulated from any real feedback or criticism. Second, any social science work includes some degree of bias because we're not all robots. Saying no possible conclusions can be drawn from demographic data is unscientific and akin to global warming denial.
> You're putting the cart before the horse. This is a private company's data, not any specific recommendation for government action.
The federal government (and potentially individual States too) has been active for years to enforce quota in various domains to reduce "discrimination". Of course companies feel the pressure to do something about it, because if they don't, they may be targeted next in terms of Employment Laws.
> Second, any social science work includes some degree of bias because we're not all robots. Saying no possible conclusions can be drawn from demographic data is unscientific and akin to global warming denial.
A proper social study should always lead to further studies unless you are crystal clear on how to read the data out. Because "we are not robots", the explanations are not always simple and it's not JUST because there's racism or discrimination that there are differences in who gets what job. It's just like if you were saying that there's racism against white people among construction workers, because most of them are not white. This would be missing the entire point because you'd be focused on the numbers instead of trying to understand why it is so and what are the incentives in place.
So yeah, most "demography data based conclusions" are rubbish because they do not focus on explaining the individuals behaviors and what's in it for each of them. And yeah, global warming is actually very similar: data is sparse, grossly extrapolated, and used as a political agenda and a source of new taxes. Global Warming may be happening, but certainly not as fast as Al Gore wanted us to believe, and whether CO2 is the real culprit is another matter for discussion. But that's a whole other topic not relevant to the point discussed here.
The people pushing this agenda most heavily do not want a post racial society. They feed off the conflict, they profit off the ability to attack companies like Google, they gain power by ensuring there is no post racial end.
African Americans and women need better role models and tech companies can help with that.
Culturally, we all need to understand that we need to admire people who do these things. It will encourage us to seek partners (even in our own cohort) that are good at these things and have children which are even better. Obama gave fantastic advice to all African american men (to all men, really): marry someone smarter than you.
Everyone needs to follow that advice. We no longer have evolution looking out for us, and this is how we avoid idiocracy.
>As production techniques for hard drugs like cocaine and methamphetamines improve, cost of access has dropped significantly, leading to increased use of these substances in children. Technological progress is inevitable, so we might as well embrace it and accept the fact that children will be using hard drugs from now on.
Of course, that's an extreme example of the argument that has been used on HN a lot lately in favor of data collection, but it still gets the point across. Just because there's an industry push towards something doesn't mean that it's right.
What I said was that it's a useful application of technology. People will probably like it and it will gradually become a normal part of our society. That's the opposite of your example.
There has been a cultural shift lately from "Ha! Those people are nerds!" to "Man, those guys are going to make so much money.". I would argue it has a lot to do with this movie:
Also, as a student at the University of Washington, I would like to note that, anecdotally, the quality of CS students has dropped through the floor. I'm a mechanical engineering major, but I often find myself helping my roommate with his CS homework, even though he's probably in the top five percent of CS students here. These people don't even understand basic things like what bytecode is.
Another part of the problem is the assumption that using free software necessarily protects you from government intrusion. I think at this point you pretty much have to live out in the woods with nothing more complicated than a gun in your possession to avoid that.
Well, RMS exclusively uses a Lemote Yeelong that has been formally verified to not contain backdoors, and he runs purely free software on it. If that's not enough, he never connects it directly to the internet by having another computer wget certain websites on a regular basis and also download/ upload emails, which get transferred to the Lemote via physical media.
There may still be vulnerabilities, but he's a whole lot more secure than your average person.
But how well does RMS' model scale to our modern, global and interconnected society? Free software assumes the right to validate, and modify, source code - which is great if you can. Most users of free software, however, don't have the time or even the ability to do anything but blindly trust that someone else has it covered (and obviously, users of non-free software don't have a choice in the matter.)
> But how well does RMS' model scale to our modern, global and interconnected society?
It doesn't. But it isn't supposed to. Stallman is consciously upholding a moral ideal that most in tech are not.
The goal is not for everyone to be like RMS. The goal is to sway the companies who build tech for everyone to be like RMS.
Consider for a moment how much open source software Google, Microsoft, and Apple use in their proprietary products. Is it ethical to use that much free software for the corporation's own personal gain?
>Is it ethical to use that much free software for the corporation's own personal gain?
I don't believe it's necessarily unethical for a corporation to take advantage of open source software if the open source code is distributed with a license which allows for commercial use. I think if the author wants not to care about that, then that should be their right.
That said, closed-source code does make theft a lot easier to hide, so the case is stronger for the use of free software validating the (ethical) integrity of a company.
Well, in terms of package and code validation, there are definitely strong arguments to be made for source-based distribution models and FOSS-backed fuzzing operations. Although freely available source isn't perfect for combating government intrusions, it still is the gold standard since it's impossible to implement fully-featured, unobfuscated backdoors. Despite the fact that things like heartbleed are damaging, keep in mind that they're only a bugs rather than deliberate backdoors.
The answer to imperfect software freedom isn't no software freedom.
I realize it's not the most credible source, but there was a purported leaker a few months ago on 4chan that claimed Google is getting ready to turn Android into something like this. He even claimed to have a prototype device. I'm taking it with quite a bit of salt, but the supposed leaker seemed at least somewhat believable in conversation.
That's not to say I don't like the idea of a constitutional court, though. I just think we need to also add some sort of protections against blatantly unconstitutional actions.