While correlation is not causation, correlation is sufficient in computer learning systems.
Also, computer learning should be resistant against manipulation through fake input data, and this is achievable by prioritizing inputs that are difficult to falsify.
Determining ethnic background is more immune to tampering and falsification than determining one's socioeconomic situation.
Why what was considered perfectly normal ten years ago causes outrage of offense now? People didn't become offensive pricks. It's the standard of what is considered offensive that's slipping. So instead of "Why do you WANT to be an offensive prick?" I'll ask "why do you WANT to be a primadonna who actively seeks out new things to be offended about and rebrands perfectly normal stuff as offensive?"
A good system will be immune to manipulation. It will ask questions people are less likely to lie to, get data that is easily verified, mistrust data that can be falsified. It can't assume all applicants will tell the truth all the time - many will try to game it, to get their way, through guessing what the system expects.
Effect: things like stability of personal income or experience level, job stability, or health are way less verifiable than stuff like race, gender, age, and account balance.
Absolutely not easy. Any attempt to prove it will be met with violent protests, death threats, smear campaign, disciplinary action, lawsuits, and possibly acts of direct violence. Essentially, if your research proves any kind of inequality, either tweak the data until that vanishes, or bury it and make the world forget. Any attempt to publish will be a suicide in the profession.
And don't worry if you falsify your data to remove the inequality. If someone tries to challenge you, all you need is to complain about them on progressive sites and they will be silenced.
Yup. Statistically speaking, a black person earning $200k/year is more likely to - end up in prison for drug trade. - get shot by a cop (even if they are entirely innocent) - sue the bank for discrimination when bank collects overdue debt - get involved in dangerous activities like political protests (anti-discrimination), be arrested or injured as result.
Simply put, all things being equal, choosing the white is safer - a more economically sound decision. And yes, it sucks, it's unfair, it's not the black person's fault, but it's just true.
The audit will find cases of incompetence or laziness. It would be very hard for it to find cases of actual subversion, especially if the admin has enough time to hide all the evidence off-site. Never mind his "booby traps" blowing up upon discovery by the auditor, and blaming the auditor for breaking the system.
I also wish more people who read Psychology 101 book also read Statistics 101 book.
Then they might learn that bias is sometimes a fact of the nature completely apart from perception. That not all random processes follow the gauss curve and if you estimate them correctly, this is not merely your subjective perception.
Bias: deviation of the expected value of a statistical estimate from the quantity it estimates,
You have a bag with 10 red and 20 blue marbles. You choose a marble and write it down, then return to the bag.
But it's your subjective prejudice to expect the blue marbles will come up more frequently, right? Everyone knows they will show up in equal proportions, you racist!
The problem is when the bias exists in reality, not in perception or opinions.
The correlation between socioeconomic status and risk of defaulting on a loan is clear, and it would be silly to question it.
The disparity between socioeconomic status of different races is a huge issue, not just a fact, a fact that is loudly announced in a voice full of outrage. This means a clear correlation here too.
So why, when you have "A implies B" and "B implies C" suddenly everyone starts looking for excuses to claim "A implies C" is wrong?
Probably incorrect use of "inherent", in the common meaning, "pervasive".
It's not "inherent" as in "nothing ever can change that, it's an irrevocable part". It's prevalent. Take an individual, you may find a fantastic person. Take an average over the population though, and you see "the average is bad." It is. Don't deny it - the correlation is strong, and while correlation is not causation, in risk assessment correlation is sufficient to deliver accurate results.
I'm not going into detail what social, political, economical and genetic factors may or may not contribute to the correlation. It's a can of worms no professional dares to approach fully objectively. But the correlation between racial and economic status is a fact, and correlation between economic status and risk is a fact. So why would a machine learning device ignore a strong factual trend, just because its existence is offensive?
If the correlation was merely *perceived* as you say, then this is correct.
But the risk usually is real.
You won't find scientific sources for these claims because in the current climate such a research is a public suicide for the researcher, but that doesn't change the reality. And you can't expect an AI system to ignore the elephant in the room.
"An admin needs to be able to generate and revoke passwords, not know them."
"Doesn't need" or "Shouldn't" versus "Can't".
If you have control over the process of setting the passwords, you can have the passwords. You shouldn't and you're not supposed to need to, but who's to stop you, and who will ever know?
The other anon is right: in the real world, unless your employer is NSA or something of comparable caliber, as an admin you have access to everything - whatever you don't have access to, you can obtain, without the employer's knowledge.
The only defenses against rogue admins companies really have is to have more loyal admins, and not to piss admins off. Plus threat of lawsuit if the admin fails to cover his traces after going rogue. Essentially, you can only try to reduce damage after the attack, you can't prevent the attack.
And to have anything "better", you have to spend so much on security, that unless security is your *product*, you'll be creating losses.
I'm an embedded systems developer. I need to trim systemd of every single functionality the target device is not going to need, removing them from the build of the customized systemd binary, to free up system resources for the actual device control application.
Redhat: A short document with all the "what" and none of "why" or "why would I need this" followed by an unending list of "get a job done and remain none the wiser."
Archlinux: not even that, just head first into voodoo programming.
The Linux.com starts promising... and then ends. It's the right approach but waaay too short and shallow.
Slashdot Mirror
While correlation is not causation, correlation is sufficient in computer learning systems.
Also, computer learning should be resistant against manipulation through fake input data, and this is achievable by prioritizing inputs that are difficult to falsify.
Determining ethnic background is more immune to tampering and falsification than determining one's socioeconomic situation.
Interesting.
I'm trying to imagine the response if he was white though.
Why what was considered perfectly normal ten years ago causes outrage of offense now?
People didn't become offensive pricks. It's the standard of what is considered offensive that's slipping.
So instead of "Why do you WANT to be an offensive prick?" I'll ask "why do you WANT to be a primadonna who actively seeks out new things to be offended about and rebrands perfectly normal stuff as offensive?"
A good system will be immune to manipulation. It will ask questions people are less likely to lie to, get data that is easily verified, mistrust data that can be falsified. It can't assume all applicants will tell the truth all the time - many will try to game it, to get their way, through guessing what the system expects.
Effect: things like stability of personal income or experience level, job stability, or health are way less verifiable than stuff like race, gender, age, and account balance.
Absolutely not easy. Any attempt to prove it will be met with violent protests, death threats, smear campaign, disciplinary action, lawsuits, and possibly acts of direct violence. Essentially, if your research proves any kind of inequality, either tweak the data until that vanishes, or bury it and make the world forget. Any attempt to publish will be a suicide in the profession.
And don't worry if you falsify your data to remove the inequality. If someone tries to challenge you, all you need is to complain about them on progressive sites and they will be silenced.
Yup. Statistically speaking, a black person earning $200k/year is more likely to
- end up in prison for drug trade.
- get shot by a cop (even if they are entirely innocent)
- sue the bank for discrimination when bank collects overdue debt
- get involved in dangerous activities like political protests (anti-discrimination), be arrested or injured as result.
Simply put, all things being equal, choosing the white is safer - a more economically sound decision. And yes, it sucks, it's unfair, it's not the black person's fault, but it's just true.
The audit will find cases of incompetence or laziness. It would be very hard for it to find cases of actual subversion, especially if the admin has enough time to hide all the evidence off-site. Never mind his "booby traps" blowing up upon discovery by the auditor, and blaming the auditor for breaking the system.
Then you keep tweaking the data until the biases vanish. And the data becomes useless.
Oh, but this is the whole point of outrage. The average, perfectly objective statistical sample is racist.
I also wish more people who read Psychology 101 book also read Statistics 101 book.
Then they might learn that bias is sometimes a fact of the nature completely apart from perception. That not all random processes follow the gauss curve and if you estimate them correctly, this is not merely your subjective perception.
Bias: deviation of the expected value of a statistical estimate from the quantity it estimates,
You have a bag with 10 red and 20 blue marbles. You choose a marble and write it down, then return to the bag.
But it's your subjective prejudice to expect the blue marbles will come up more frequently, right? Everyone knows they will show up in equal proportions, you racist!
The problem is when the bias exists in reality, not in perception or opinions.
The correlation between socioeconomic status and risk of defaulting on a loan is clear, and it would be silly to question it.
The disparity between socioeconomic status of different races is a huge issue, not just a fact, a fact that is loudly announced in a voice full of outrage. This means a clear correlation here too.
So why, when you have "A implies B" and "B implies C" suddenly everyone starts looking for excuses to claim "A implies C" is wrong?
Researchers, who go looking for bias are ridiculed, booed, and then fired.
If a clear racial bias appears in your research results, you'd better bury them deep and never show anyone lest you're marked a nazi.
Probably incorrect use of "inherent", in the common meaning, "pervasive".
It's not "inherent" as in "nothing ever can change that, it's an irrevocable part". It's prevalent. Take an individual, you may find a fantastic person. Take an average over the population though, and you see "the average is bad." It is. Don't deny it - the correlation is strong, and while correlation is not causation, in risk assessment correlation is sufficient to deliver accurate results.
I'm not going into detail what social, political, economical and genetic factors may or may not contribute to the correlation. It's a can of worms no professional dares to approach fully objectively. But the correlation between racial and economic status is a fact, and correlation between economic status and risk is a fact. So why would a machine learning device ignore a strong factual trend, just because its existence is offensive?
If the correlation was merely *perceived* as you say, then this is correct.
But the risk usually is real.
You won't find scientific sources for these claims because in the current climate such a research is a public suicide for the researcher, but that doesn't change the reality. And you can't expect an AI system to ignore the elephant in the room.
"An admin needs to be able to generate and revoke passwords, not know them."
"Doesn't need" or "Shouldn't" versus "Can't".
If you have control over the process of setting the passwords, you can have the passwords. You shouldn't and you're not supposed to need to, but who's to stop you, and who will ever know?
How did you know IT didn't keep a keylogger on any of the PCs that accessed it?
The other anon is right: in the real world, unless your employer is NSA or something of comparable caliber, as an admin you have access to everything - whatever you don't have access to, you can obtain, without the employer's knowledge.
The only defenses against rogue admins companies really have is to have more loyal admins, and not to piss admins off. Plus threat of lawsuit if the admin fails to cover his traces after going rogue. Essentially, you can only try to reduce damage after the attack, you can't prevent the attack.
And to have anything "better", you have to spend so much on security, that unless security is your *product*, you'll be creating losses.
OP is a dirty unwashed troll, and you, sir have been trolled.
You know which browser draws batteries even less than Edge?
Lynx.
The Lennart Blog linked in the introduction seems really promising.
I'm an embedded systems developer. I need to trim systemd of every single functionality the target device is not going to need, removing them from the build of the customized systemd binary, to free up system resources for the actual device control application.
Any manpage to help me with that?
Redhat: A short document with all the "what" and none of "why" or "why would I need this" followed by an unending list of "get a job done and remain none the wiser."
Archlinux: not even that, just head first into voodoo programming.
The Linux.com starts promising... and then ends. It's the right approach but waaay too short and shallow.
Manpages: alphabetical list of commands/files/parameters.
FAQs: How to get things done and remain none the wiser.
> I don't want to use an archaic distro like Slackware, or a niche distro like Devuan, or a weird one like Gentoo. So recently I've been using NetBSD
That gave me a chuckle.
You mean you didn't want to choose between archaic, niche or weird, so you found one that is all three at once? :)