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Well I don't have that much time, so for now I only looked at pictures with people in them they have posted since December 1. Simply counting people yields 29%

Well I don't have that much time, so for now I only looked at pictures with people in them they have posted since December 1. Simply counting people yields 29% white women, 19% women of color, 21% men of color, 30% white men. Not a very exact science, though - I left out groups above a certain size (for example picture from Anti-Trump demonstration or MLKday), and in some cases I couldn't recognize the people. Many white men come from office shots where they linger in the background, whereas there are many tweets explicitly featuring female or black engineers. It seems by only looking at their "media timeline" I also missed photos like this one: https://twitter.com/Every28HoursPla/status/831666887717031936 https://twitter.com/Every28HoursPla/status/83166688771703193... (which they retweeted). I'll try to find time for a better "analysis", ideally including texts. Compared to last time there seem to be now more posts boasting technology at Google. For example there were several about Tensor Flow, all featuring the same white guy (I counted him for every instance). I couldn't find the time when I last posted about lifeatgoogle, would have liked to look at their tweets from around then. For comparison employee stats from 2014: http://mashable.com/2014/05/28/google-employee-demographics/#zdocqLkt78qJ http://mashable.com/2014/05/28/google-employee-demographics/... - 70% male, 91% white or asian.

tomlock 10y ago
So what's your conclusion?
- facepalm 10y ago
  This time around there were more white men, I think - in part because of some specials like Tensor Flow, or a picture from an actual office. 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.
  - tomlock 10y ago
    You're again, falling victim to confirmation bias by rejecting the best quantification you've provided yet. Lets examine the data you've provided - 29% white women, 19% women of color, 21% men of color, 30% white men. This data is entirely in line with the demographics of the US. About 50/50 on gender and 60% white. In fact, given google's global hiring reach, these figures are actually biased towards white people - while about spot on for gender. This entirely contradicts the point you were originally pointing to this twitter feed as confirmation of.
    - jaduncan 10y ago
      If anything, this thread has just made me newly impressed with Google's approach to inclusion. It's also really, really obvious that the person you are responding to isn't able to reconcile seeing PoC and women with their own world view.
      - facepalm 10y ago
        Huh wtf - what does seeing women and PoCs have to do with a "world view"? You think I am not aware that women and PoCs exist?
        tomlock 10y ago
        Based on your quantification, there's now more evidence for the claim that you perceive an unbiased sample of people to be biased towards minorities and women, than there is evidence against that claim. It seems like you're struggling to reconcile this bias with the quantification of it.
- facepalm 10y ago
  HN won't give me a reply button further down, and I want to go to bed, so I am replying here: 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 https://twitter.com/lifeatgoogle/status/824649101069455361 I counted the blurry people in the background of this office: https://twitter.com/lifeatgoogle/status/817466019526610947 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 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?
  - tomlock 10y ago
    Actually I had no idea what the demographic percentages of the US were before I looked them up. Your original point was that you thought Google wasn't interested in hiring male engineers anymore. The current demographics of Google are irrelevant to Google's hiring strategy. Why would they be? You're not only displaying confirmation bias in the way you are trying to undermine the clearest quantification you have access to, but you're also avoiding your original statement. You initially presented the lifeatgoogle twitter feed as evidence, and you had no quantifiable evidence that it was biased. Now that you do have a quantification, you're walking back the importance of that evidence. Perhaps you're doing this so you can maintain your poorly quantified view? If only you gave as much latitude to other people.
    - 10y ago

tomlock 10y ago

So what's your conclusion?

facepalm 10y ago
This time around there were more white men, I think - in part because of some specials like Tensor Flow, or a picture from an actual office. 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.
- tomlock 10y ago
  You're again, falling victim to confirmation bias by rejecting the best quantification you've provided yet. Lets examine the data you've provided - 29% white women, 19% women of color, 21% men of color, 30% white men. This data is entirely in line with the demographics of the US. About 50/50 on gender and 60% white. In fact, given google's global hiring reach, these figures are actually biased towards white people - while about spot on for gender. This entirely contradicts the point you were originally pointing to this twitter feed as confirmation of.
  - jaduncan 10y ago
    If anything, this thread has just made me newly impressed with Google's approach to inclusion. It's also really, really obvious that the person you are responding to isn't able to reconcile seeing PoC and women with their own world view.
    - facepalm 10y ago
      Huh wtf - what does seeing women and PoCs have to do with a "world view"? You think I am not aware that women and PoCs exist?
      - tomlock 10y ago
        Based on your quantification, there's now more evidence for the claim that you perceive an unbiased sample of people to be biased towards minorities and women, than there is evidence against that claim. It seems like you're struggling to reconcile this bias with the quantification of it.
facepalm 10y ago
HN won't give me a reply button further down, and I want to go to bed, so I am replying here: 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 https://twitter.com/lifeatgoogle/status/824649101069455361 I counted the blurry people in the background of this office: https://twitter.com/lifeatgoogle/status/817466019526610947 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 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?
- tomlock 10y ago
  Actually I had no idea what the demographic percentages of the US were before I looked them up. Your original point was that you thought Google wasn't interested in hiring male engineers anymore. The current demographics of Google are irrelevant to Google's hiring strategy. Why would they be? You're not only displaying confirmation bias in the way you are trying to undermine the clearest quantification you have access to, but you're also avoiding your original statement. You initially presented the lifeatgoogle twitter feed as evidence, and you had no quantifiable evidence that it was biased. Now that you do have a quantification, you're walking back the importance of that evidence. Perhaps you're doing this so you can maintain your poorly quantified view? If only you gave as much latitude to other people.
  - 10y ago