Yeah and communist society is about who has the best connections to the people in the party who decide who gets what. And socialist societies are about not making too much money because you'll lose the subsidies.
Communism is not the only alternative. It still implies an economy and endless human work to sustain it. Capitalism is automating everything and if this continues we'll either end up in a post scarcity society like Star Trek or some dystopian hell where corporations create artificial economies just to maintain their power and wealth.
Strawman...
The alternative to purely profit driven society is not a communist society. It's social democratic where values of freedom rights and wellfare actually matters and are not just axes to grind on.
The US internal anti socialist propoganda is so strong that it makes people believe that this middle ground doesn't exist.
For private insurance in Europe you have to sign disclosure documents for all your doctors and medical history, at least in all 5 countries I have insight in. It's perfectly legal and standard.
Same happens in brick and mortar stores. Im germany a drug store chain had a decade lomg partnership with an organic products / plant milk producer who did a lot to buold the market, and when the market actually got more mainstream and profitbale, they kicked them out and replaced them their new house line of organic products.
You are right but it's the scale that is worrying.
Tech is accessible everywhere. What it does is set certain expectations for users in different countries. In india, most people won't pay for apps and they are not profitable to run many services which big companies do for free.
Maybe it's good in the short term. For consumers, certainly but I wonder if tech will become stagnated like other industries with monopolistic control.
That's not Western, but American. In Europe much weaker painkillers are prescribed due to risk of addiction, and in places like germany a lot of placebo (= overpriced homeopatic bullshit)
That's a bold assumption. Such algorithms are developed wwith training sets, not just by employees randomly clicking around. They wrote that 189 algorithms were submitted, there were surely a few developed by non-racist, diverse people.
It's the methods being used to select, populate, label, and validate the training set that are the problem.
Basically, your team is composed of white dudes who don't see the problem with a ML training set consisting largely of pictures of white dudes.
To prevent this they'd have needed to A) Employ a black person, and B) Listen to said employee's feedback, in order to recognize the problem.
Edit: Also worth pointing out, just using a representative population sampling would still show racial bias, essentially weighting accuracy with respect to population percent. You'd probably need to have equal samplings of pictures of people from all races/genders/disabilities if you wanted equal accuracy across the board. That also includes picture quality and range of picture quality. Doubling up images, or using corporate headshot white dudes and grainy selfie People of Color could still cause issues.
Same logic applies to labelling. That minimum wage contracting firm used to decide who's who in the photos may exhibit racial bias, by virtue of the fact that most people do. If their accuracy in labelling is racially biased then so too will the algorithms that it's based on.
Why do you need A to do B? Obviously any competent ML practitioner can notice a biased training set. Discriminating against people based on an assumption that race determines ability is just racism.
Are you asking why you can't listen to an employee that doesn't exist?
But more to your point, if these oh-so-competent ML practitioners were doing their jobs right, we wouldn't be having this discussion.
The whole reason diversity is championed in hiring is precisely because a single individual's perspective can only see so far. And if you have a monoculture team who has experienced very similar life circumstances, you end up with the kind of narrow perspective that leads to more racist soap dispensers.
I think I agree with your specific point concerning facial recognition, but not your general point about un-diverse teams being incapable of delivering a good product for a diverse audience. This is because I have recently worked with a team that spent considerable effort on accessibility issues despite none of the team having any disability.
I'm glad that you were able to deliver a product that helped with accessibility, but part of the considerable effort it took was just in trying to understand what someone else's perspective is. It's less efficient than simply having a member of the team with real lived experience that can answer common-sense questions that your team agonized over answering.
And not to say this happened in your case, but even with that considerable effort, it's still very easy to end up with blind spots in your product that a more diverse team would have caught.
It's the same as hiring for any other level of experience for more routine technical skills. If your team has no experience in this area, they'd need to expend a much greater degree of effort to answer questions that someone who is experienced would already have known the answer to.
I agree. I just have low expectations as far as diversity in tech goes (so, one black person and/or one woman on the team would still be a milestone many of these companies have yet to reach), but you make a good point: hiring only one person of color or one woman would still be very problematic.
Not a number per se, but ideally the racial and gender ratios of the team would reflect the total population of the area (country? Metropolitan area?) in which the company resides, with the standard caveats that random sampling would give a range of different combinations. So that'd be, a multinomial distribution with the probabilities that each race is chosen set at the demographic percentage of the total population.
In other words, ideally the racial and gender distribution of a team would be as inconsequential and unbiased as blood type or handedness, in that the aggregate demographic ratios on your teams would at least match that of the residential population in your area, and ideally that of your broader geographic location.
I'm not doing a good job explaining this clearly, but the simple answer is: more than one. No one wants to be the token hire.
> In other words, ideally the racial and gender distribution of a team would be as inconsequential and unbiased as blood type or handedness, in that the aggregate demographic ratios on your teams would at least match that of the residential population in your area, and ideally that of your broader geographic location.
Ok, I don't know about race, but for gender look up the "gender equality paradox". In countries with greater equality rights for women they show less of an interest in STEM subjects.
Like I say I don't know of any similar studies done for race, but it would indicate that you shouldn't necessarily expect outcomes that "would match that of the residential population in your area, and ideally that of your broader geographic location".
In my opinion we should be pushing for equality of opportunity, not equality of outcome (you appear to want the latter).
That's why I sprinkled the word "ideally" so liberally throughout that comment, as that was the premise of your question. To actually reflect the population, you'd have to somehow address centuries of institutionalized disenfranchisement, de facto segregation, educational barriers, racially-moticated policing and disproportionate conviction rates (highlighted by the OP). That's a lot to put on a hiring manager who isn't even sure that racism is an actual, tangible thing.
Realistically, the most that hiring managers (save for huge FAANG institutions) can do is thoroughly ensure that their team isn't inadvertently (or blatantly) racist/sexist in their hiring process and on the job, and to post the job in enough places that a diverse applicant pool will see the posting.
With that said, hand-waving away that there are few to no women or African Americans/Latinos/Native Americans/etc. on the team with an overzealous application of the Equality Paradox is a pretty dangerous mindset to get into. It's essentially passing the buck, and is eerily reminiscent of the claims made by 1950's Southern US Politicians that Blacks were the ones who were self-segregating because they wanted to, not the other way around.
What I'm saying is, the ideal 50/50 gender ratio/representative race may be unrealistic for a myriad of reasons, but if you're a 50-person start-up with 2 women, one of whom is HR, and no black people, I'd take a good, hard look at the company culture that's being fostered, and particularly whether turnover for women and People of Color at your company is worse than average.
> Realistically, the what most hiring managers (save for huge FAANG institutions) can do is thoroughly ensure that their team isn't inadvertently (or blatantly) racist/sexist in their hiring process and on the job, and to post the job in enough places that a diverse applicant pool will see the posting.
I have been involved in hiring people before. There was absolutely nothing racist or sexist in the way we hire. Fact was we go two applicants. Neither were women or minority status. Fact is that the industry is full of white men (even here in Europe).
We should be hiring on ability to do the job and nothing else.
So, a quick note that my comments regarding racial representation are somewhat US-centric. I'd expect a company in Europe to be a much higher % white because your population is.
> We should be hiring on ability to do the job and nothing else.
This is exactly my point! Yet there is quite a lot of inadvertent, or even blatant, racism and sexism that happens during the hiring process and on the job.
Because programming ability isn't determined by melanin concentration in the skin, or by what pronouns you use, and hence shouldn't show selection bias in hiring, save for a biased selection process.
In the same way that handedness has no bearing on programming ability. If your firm were staffed entirely by left-handed folk, it should rightfully raise questions about how that happened.
You seem overly defensive about your hiring process, and unsatisfied with any answer that asserts men and women are equal. Ironic, no?
the hyperbole is not really helpful or substantive, its not about the algorithm its about how the product wouldnt have shipped when individual contributors, their manager, the director, the executive team, the board, and their vendors all noticed that it didnt work very well when the demo failed because they were not white males testing it on themselves and their colleagues and photos of their friends
Several countries have shown the capability of destroying satellites, not to speak of spy satellites and gps, and the fact that the spaceshuttle and its military sibling was designed to scoop up satellites and bring them back to earth.
If this is the same research that always gets cited, then it more accurately shows that boy and girl monkeys played with the wheeled toys an equal amount, but the girls played with the doll toys more.
That still shows a gender imbalance, but I find it interesting that it always seems to be used to imply that girls don't like trucks, rather than boys don't like dolls as much.
(A similar rhetorical trick is used when talking about favorite colours. Apparently lots of people's kids just love pink and this tells them it's all genetic, yet if you survey women their favourite color is the same as men, blue. They just collectively prefer pink more than men relatively speaking)
The preference for dolls is likely related to the role of females in childcare. Males are more the explorers and hunters. Women never explored nor hunted very much.
