4 ms·

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 interest

by 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.

facepalm 10y ago
My claim about them not presenting any white males was from another time - do you recall by any chance when it was? As I explained, the sample size I used now was small, and a few pics can have made a big difference. I think when I made the claim there were different pictures, that is why I said more data should be looked at (to reduce random variation). I probably wouldn't have made the claim about the current timeline. 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?
- tomlock 10y ago
  >You assume now that metric is conclusive because it fits your conviction. No, you're now walking back your claims because the one metric you have quantified doesn't fit your conviction. At the time you claimed that by simply looking at the feed you could tell it was biased. You initially made the claim that the lifeatgoogle twitter was related evidence to your claim that google wasn't interested in hiring men anymore. I'm not silly enough to claim that a brief perusal of a twitter account can be extrapolated into a claim about a company's hiring strategy. Thanks to your quantification, we have some evidence to suggest the lifeatgoogle twitter is fairly representative of population demographics along gender and racial lines, at least in the US. I don't see the data as conclusive of anything more than that.
  - facepalm 10y ago
    I have found our original discussion, it was 57 days ago. So let's do another analysis of their timeline two months ago (December+November, for example). But this time, you tell me how to categorize their tweets. 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 https://twitter.com/lifeatgoogle/status/813410799725215744 And how should pictures like this be counted: https://twitter.com/lifeatgoogle/status/800818789122129926 https://twitter.com/lifeatgoogle/status/800818789122129926 or this https://twitter.com/lifeatgoogle/status/812002215267139584 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 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.
    - tomlock 10y ago
      >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. Really? What evidence do you have to back up your impression? Why do they give you that impression? >You mention you work in statistics, so tell me how you would approach the problem? I'd measure first and then debate my conclusions based on that measurement - and in an area I hadn't measured - I wouldn't spout my impressions or claims - they wouldn't be useful. Like this thing, which you said one day, not fifty-seven days, ago: >Huh - that Twitter feed obviously is tilted towards only showing women and PoCs as engineers. The twitter feed isn't about only women, or only PoCs. You did the measurement yourself. You seem to still be holding onto your impressions with contrary quantified evidence in front of you. Where's the stuff that supports you?

by tomlock 10y ago

facepalm 10y ago

My claim about them not presenting any white males was from another time - do you recall by any chance when it was? As I explained, the sample size I used now was small, and a few pics can have made a big difference. I think when I made the claim there were different pictures, that is why I said more data should be looked at (to reduce random variation). I probably wouldn't have made the claim about the current timeline. 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?

tomlock 10y ago
>You assume now that metric is conclusive because it fits your conviction. No, you're now walking back your claims because the one metric you have quantified doesn't fit your conviction. At the time you claimed that by simply looking at the feed you could tell it was biased. You initially made the claim that the lifeatgoogle twitter was related evidence to your claim that google wasn't interested in hiring men anymore. I'm not silly enough to claim that a brief perusal of a twitter account can be extrapolated into a claim about a company's hiring strategy. Thanks to your quantification, we have some evidence to suggest the lifeatgoogle twitter is fairly representative of population demographics along gender and racial lines, at least in the US. I don't see the data as conclusive of anything more than that.
- facepalm 10y ago
  I have found our original discussion, it was 57 days ago. So let's do another analysis of their timeline two months ago (December+November, for example). But this time, you tell me how to categorize their tweets. 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 https://twitter.com/lifeatgoogle/status/813410799725215744 And how should pictures like this be counted: https://twitter.com/lifeatgoogle/status/800818789122129926 https://twitter.com/lifeatgoogle/status/800818789122129926 or this https://twitter.com/lifeatgoogle/status/812002215267139584 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 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.
  - tomlock 10y ago
    >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. Really? What evidence do you have to back up your impression? Why do they give you that impression? >You mention you work in statistics, so tell me how you would approach the problem? I'd measure first and then debate my conclusions based on that measurement - and in an area I hadn't measured - I wouldn't spout my impressions or claims - they wouldn't be useful. Like this thing, which you said one day, not fifty-seven days, ago: >Huh - that Twitter feed obviously is tilted towards only showing women and PoCs as engineers. The twitter feed isn't about only women, or only PoCs. You did the measurement yourself. You seem to still be holding onto your impressions with contrary quantified evidence in front of you. Where's the stuff that supports you?