Is it fair to judge a web site by their comments section? I'm sure "The Guardian" or even Hacker News get pretty nasty comments, too.
You could demand censorship, but maybe some people simply are against it.
1,202 karma · joined January 29, 2014
Obama already used data science in his campaigns, and Hillary spent more money than Trump afaik. Advertising and user targeting are not new inventions.
For sure men are unhappy with their companies. Otherwise nobody would ever switch jobs.
Also it should be considered that women have more career options than men. Since they spread out over more professions (including fulltime mum), it is to be expected that they are not 50% of people in all professions.
As for male criminal citizens, they should be sent to jail. In any case, as I mentioned before, they are already citizens, so the state has a special obligation towards them.
The point is also not to consider every immigrant a criminal just because some of them are, but to deal with life in one's country. If for example you could devise a test that would tell with 100% certainty if an immigrant will become a good, law-abiding citizen, a lot of immigration discussions would become a lot easier.
Btw suppose your suggestion would be followed, and male citizens would be deported because they are such a high risk for crime. Who would do the deporting? The world feminist army? Or should men just pack up and leave by themselves, admitting their own tendency to become criminals?
Guess it depends on how you define terrorist attacks...
The discussion is not about what should be done, only about Sweden's claim that there is no problem. If they say "yes there are criminals, but only because they are poor", they are dodging the issue.
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edit: Hacker News doesn't let me post more comments. So here is the comment I wrote, but I'll probably refrain from further ones:
"poor swedes could be deported and rich immigrants could take their place"
This is already happening in a way - it is called gentrification (not replacement with rich immigrants, but in general rich people will cluster together).
But Swedes formed a "state" and endowed some people with citizenship, but also giving them responsibility for their own people. So their responsibility should be to their own people first. Of course you can argue that forming such a state is immoral, but I think there are some practical arguments in favor of it.
As history has shown, states are very well capable of deporting significant fractions of their citizens, though. But presumably atm Swedes rate the ensurance to not be deported higher than the inconvenience of living with poor people.
The gender angle: yes, that is a popular argument in Germany, "but the refugees are only criminal because they are all men". But it should be possible to take that into account statistically. And even if the higher proportion of males would be the only issue, it still wouldn't change the fact that immigrants are causing problems. After all, they have a higher proportion of males.
For example, if you have 100 "native" Germans and 10 refugees, and there were 3 German criminals and 1 refugee criminal, 10% of refugees would be criminals, but only 3% of Germans, even though more Germans than refugees would be criminals.
The only benefit I can see is learning more about the human physique. But does that alone justify the scale and investment, or could that be had in cheaper ways?
Another test could be if there are stretches of time when the account gives the impression, that is length of tweet chains without any white men.
I have explained various flaws of my little analysis, but you prefer to ignore them and claim I have provided evidence for your opinion. Yet you work as a statistician :-(
I give up for now, unless you come up with a proper measurement suggestion.
For example, should this picture count? It is not somebody working at Google, just a stock image of somebody working in the food industry: https://twitter.com/lifeatgoogle/status/813410799725215744
And how should pictures like this be counted: https://twitter.com/lifeatgoogle/status/800818789122129926 or this https://twitter.com/lifeatgoogle/status/812002215267139584
Maybe from the last two you can also see why perhaps simply counting people is not the best metric - a single group photo could distort everything.
You mention you work in statistics, so tell me how you would approach the problem?
Also maybe I didn't express it clearly enough, I didn't look at the whole timeline, only the media timeline: https://twitter.com/lifeatgoogle/media (which is media they posted, pics and videos).
I also didn't claim I can tell bias simply by looking, I said it was my impression they don't want to hire white men anymore. If I was convinced I could tell simply by looking, I wouldn't agree to do an analysis.
As I said - I am sure they still hire white men, but that particular account (and some of their other publications) give the impression they are not interested in that anymore.
And they claim to represent Google's demographic, not the demographics of the general population, so contrary to what you say my numbers do show bias against white men. Not as extreme as I perceived two months ago, but still.
If your company is 70% men and you only report about what women are doing, it is revisionist.
Imagine if all stories about WWII would only be about female soldiers. The impression would be women fought and died for our freedom, all the sacrifices of men would be forgotten. That is revisionism.
I read a book in German (specifically on how to lie with statistics), don't know which ones to recommend in English. There is the obvious one with the name "how to lie with statistics", but it is very old. Otoh, available for free (but I haven't read it).
Feynman, too, don't forget about Feynman. http://www.ar-tiste.com/feynman-on-honesty.html
Thinking, Fast and Slow was a lot about bias, but not sure if it really gets the point across effectively.
Seeing how you interpret my comments, maybe starting with statistics is actually backwards. Perhaps start with language and communication first? Sorry if my comment sounds mean, but it really seems a bit crazy how you try to bend my comments into something outrageous.
Everybody can learn about certain signs. If the person asking already knew them all, why did they ask? Then their question was vacuous, not my reply. Just because a question has an obvious answer, the answer is vacuous? What is going on in your mind? What are you driving at?
Have you ever read one of those books about how to lie with statistics? You really, really should.
But if you want: I am a trained mathematician, so I am trained in identifying the root assumptions of problems.
I am aware of the typical ways to lie with statistics. There are books about that, everybody can and SHOULD read those. For example choosing certain time intervals, making charts not start from zero to inflate a trend, picking the aspect that best supports your claim (for example, either use relative growth or absolute growth when describing an issue - one more murder in a town can mean "crime incidents increased by one" or "crime incidents increased by 100%"). Playing with proportions, like drawing circles for comparisons and using diameter (instead of area) to correspond to the values you want to show. And so on - there are many possibilities, and they are all being used.
So, for example, if I see a chart depicting some trend over a period of time, my immediate instinct is to ask "what would it look like if the chart would start one year earlier?".
Also, I think fake news might have become a topic these days because people also get their information from social media. They often know about aspects that an article doesn't mention, so they are more often able to identify articles as fake news.
Overall, there is just one thing you have to do: try remain skeptic at all times. "Bend over backwards" as Feynman put it to disprove your own assumptions.
Nothing of that is specific to me, and it is not complicated. You just have to be willing to challenge your assumptions.
For starters, I would recommend reading those books on how to lie with statistics, and your essential Feynman. And get your news from multiple sources and compare them.
The issue is that because of bias against men, few people even realize that they are talking about completely fabricated assumptions in this thread.
And again: there are not even that many women who could tell such stories. I'd say 1 in 20 software developers at companies I worked for were female. So it is not a case of me not being told things by women on a significant scale. The women didn't tell me such stories because those women don't exist to begin with.
And again - I only used one simple metric, which already shows bias (it doesn't represent the actual demographics of Google employees). You assume now that metric is conclusive because it fits your conviction. By looking into more aspects the picture would be more clear.
And where do I not give latitude to other people?
Yes, it reflects demographics of the US, but not demographics of tech or demographics of Google employees. So the account definitely doesn't reflect life at Google in an unbiased way.
Also, I tried to err on the side of counting too many whites. For example I counted this screenshot from an animation movie as two whites: https://twitter.com/lifeatgoogle/status/824649101069455361 I counted the blurry people in the background of this office: https://twitter.com/lifeatgoogle/status/817466019526610947 but I only counted 2 PoCs here despite the further pictures with more https://twitter.com/lifeatgoogle/status/822528000646381568 I also missed a lot of pictures because I didn't realize the retweets wouldn't be in the "media list".
I just made it up on the fly for a quick, simple metric. It would be better to decide beforehand what counts, for example if the person should be the item of a news story, should be presented as an engineer, stuff like that. And a longer time. I think I had 150 people, so the animation picture alone accounted for more than 1% of the final count of white people. As I said, some office shots greatly raised the white people count, counting only people who were subject of major stories would have lowered the percentage a lot.
Maybe you are jumping to conclusions because they confirm your beliefs?
It is still biased against white men (if it is supposed to reflect the actual distribution of Google employees), but not as extreme as last time. I really would like to find the date of my last comment about it. Also perhaps simply more data is needed - a single picture with several people could shift the results here, because I checked only pics from 2.5 months.
Also better methodology needed, this was just a quick shot looking into one simple metric.
In any case, as I mentioned in another comment, a collection of stories is not a good way to gauge the problem. You need to put it into context - number of women in total, and also, what happens to men. Stories like this suggest that only women ever have bad experiences at companies. But you can find lots of male reports of being unhappy at a company, too. Why isn't that reason for men to quit in droves? Presumably the Uber-woman is happy with her new job at Stripe, too.