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Gender@Google
“Google’s Ideological Echo Chamber,” the memo written by Google’s now-fired software engineer James Damore, addresses a taboo topic in modern American life — namely, sex differences that relate to the abilities and occupational choices of men and women.
Damore’s critique of diversity and inclusion, which he supports in the abstract, hit the tech industry hard for this very simple reason: firms like Google and Facebook have tech workforces dominated by white and Asian men. As Damore observes, Google has spent millions on programs to recruit and hire more women and non-Asian minorities, with little to show for its efforts. He urges Google: “Stop restricting programs and classes to certain genders and races,” and to “de-moralize diversity.” In his view, this reverse discrimination drives Google’s rigid, ideological conformity, lowers overall production, and undercuts professional morale.
Damore’s memo did not sit well with the Google CEO Sundar Pichai, who quickly fired Damore for “advancing harmful gender stereotypes in our workplace.” According to Pichai, “To suggest a group of our colleagues have traits that make them less biologically suited to that work is offensive and not OK.”
Damore’s memo should come as no surprise. Just three months ago, a smaller flap, reported here in the Wall Street Journal, resulted from accusations of gender bias at Facebook. My article, Gender@Facebook, took a view broadly consistent with Damore’s by pointing to a wealth of evidence that suggested that biological differences could account for the differences in employment patterns. According to a detailed study by psychologists Richard Lynn and Satoshi Kanazawa, “at the ages of 7 and 11 years girls have an IQ advantage of approximately 1 IQ point, but at the age of 16 years this changes in the same boys and girls to an IQ advantage of 1.8 IQ points for boys.” More specifically, they present numbers that for general IQ show a mean of 101.461 for boys with a standard deviation of 15.235, and a mean of 99.681 for girls with a standard deviation 14.085.
There are two different ways to view this kind of evidence. Pichai dismissed the idea of group-wide differences in ability as an improper gender stereotype. But on this point, Damore surely has the better of the argument. As he noted at the outset of his memo, “When addressing the gap in representation in the population, we need to look at population level differences in distributions.” Hence it is necessary to draw, as he did, two bell-shaped curves that correspond to population-level data. The result for mathematical and spatial abilities among men and women will show two overlapping curves with different medians and (a point that Damore does not discuss) different variances as well. For the high-stress demands of tech engineers, the relevant portion of both distributions is the upper (or right) tail. Properly assembled, the data shows how any given person stands against the pool. That upper tail for tech work will be, on the available data, dominated by men. These findings lend support to a biological explanation for some of the observed differences in success rates. It should not be assumed, of course, that only these differences matter, as other factors influence productivity and success.
Indeed, recent data show that in all graduate programs women outnumber men by more than a 4-3 ratio, but that field differences matter. Thus men get about 75 percent of the advanced degrees in Engineering, Mathematics and Computer Sciences, while women get slightly more than half the degrees in biological and agricultural sciences. No simple theory of discrimination can begin to account for this data. It is largely student selection that tends to drive the outcomes. But these raw numbers in quantitative areas matter far more for the tech jobs in Google than for work in management and sales. The observed distributions thus help explain the gender imbalance in tech jobs.
At this juncture, it is critical to stress that no accurate statistical distribution should ever be dismissed or deprecated as a stereotype. But the label stereotype would properly attach to a proposition that said that every man is better than every woman at tech jobs. As Damore neatly illustrates in the bottom of his two graphs, the graphical representation of that false proposition collapses the underlying distribution of tech skills into two vertical lines, one at the median for male workers and the other for females. Huge amounts of information are necessarily lost when a two-dimensional space (mean and variance) is reduced to a single dimension (mean).
The difference between these two graphical representations highlights a deep ambiguity in the claim, “men are better at tech than women.” If it were taken to mean that all men are better than all women, it is an absurd and unforgivable stereotype. But, correctly construed in relation to the full distribution, that proposition means that it is possible to put together a one-to-one correspondence by which, perhaps with rare exceptions, the top male will have higher scores than the top female, and so on down the line. So understood, there is an enormous overlap between the two distributions, with the result that the women in the upper tail on the female distribution are superior to the many men who lie to their left.
This statistical formulation shows that the observed gender ratios at Google and Facebook need not be a matter of discrimination, although that lopsided ratio, standing alone, cannot exclude the possibility that some such discrimination takes place. By the same token, if the number of female workers holding these tech jobs were to far exceed the number predicted by accurate statistical information, it would likely indicate some institutional discrimination in favor of women candidates (barring alternative explanations). That is surely the case at both Google and Facebook with their strenuous and explicit efforts to increase female representation in the tech ranks. Indeed, if management at both companies thought that there were no differences in tech abilities in the male and female applicant pools, they would not bother with extensive—and, apparently, still unsuccessful—efforts to increase the fraction of women in their tech workforce.
At this point, it becomes possible to explain the cultural breakdown inside Google. If Google used the same rough hiring standards for its male and female applicants, the differences in performance should be of less importance. But once it is known to all that a diversity program draws its workers from two different pools, the social dynamic changes. Now, the male employees (and the female employees whose hiring precedes these efforts) do not know which new female hires made it into the job on a gender-neutral basis and which did not. The point matters in an industry where merit determines personal advancement, because no strong worker of either sex wants to be caught with weaker coworkers on a joint project. It is easy to see, even if impossible to justify, the backbiting and disrespect towards female employees whose overall contribution to the project is believed by male workers to be lower than their own. And so it is the very existence of the supposed diversity program that generates many of the social tensions that are reported by other male and female employees alike.
The situation gets only worse when the issue is examined in dynamic terms. As economists Edward Lazear and Sherwin Rosen wrote years ago, job promotion resembles a tournament format like those used in chess and tennis. With each successive round, the weaker players are weeded out until only the stronger ones remain. Any initial gaps between the men and women in tech jobs therefore will only increase with each successive round. The explanation is mathematical. In oversimplified style, imagine that the men are evenly distributed from 10 to 20 and the women from 5 to 15. When the first cut is complete, the surviving men will rank between 20 and 15 and the surviving women between 15 and 10, so that the overlap disappears. The gaps only increase thereafter with each successive cut.
This underlying trend is a problem for Google and Facebook with their sensitivities to gender imbalances. But how best to respond? Unfortunately, there is no simple solution. One possibility is to use somewhat different promotional standards. Another is to promote women into roles where the technical skills matter less. Yet another is to invest more resources, as Google and Facebook have done, to narrow the gap. Unfortunately, the one strategy that will not work in the long run is to heap verbal abuse against foolhardy dissidents like James Damore who failed to grasp the ironic power of the old maxim, “the greater the truth, the greater the libel.” Damore’s memo provoked such a hostile response because it rang true.
Published in Law, Technology
An anecdotal point. A family friend has a brilliant daughter with a genius IQ. She has a BS/MS in Computer Science from Carnegie Mellon. Graduated at the top of her class. She worked as a software developer for two years in Silicon Valley. She walked away because, despite the pay, it was boring and stifling and uncreative. She’s now designing her own line of couture and trying to establish herself as a designer. Intellect has nothing to do with how successful anyone is in tech: it takes a special kind of person to take the grinding work, the crushing hours, and having your life sucked right out of your neck by the tech corporate vampires.
Only in advanced countries. In less advantaged countries the ratios of STEM degrees (including advanced STEM degrees) is roughly proportional to the underlying population.
Thus one could argue that non-STEM degrees are a luxury only affordable in the Western world.
“Absurd”, yes. Statistically illiterate, yes. But “unforgivable”? What makes a “stereotype” (‘a set idea that people have about what someone or something is like, especially an idea that is wrong’) “unforgivable”?
What’s disturbing about the issue isn’t the issue. A kid made a reasonable point and was fired for it. Google is one of the most powerful influential companies on earth and they are obviously being run by totalitarians of a modernest bent. That is really scary. And we can’t do anything about it. The kid might sue the DOJ might use anti Trust to harass them, both would be good, but any attempt to regulate them will backfire as such efforts always do.
Good anecdote! Success in any field is a much more complicated phenomenon than just “do you have the brains and the interest to do it?” As feminists rightly point out , one must have, as a baseline, sufficient opportunity (educational and vocational), sufficient encouragement and support. Fine, but one also needs some sort of additional motivation. The need to earn a living is a big one (and the ambition to make it a really good living is another) but the sort of sheer competitiveness that leads one to keep working at boring tasks for insane hours, sacrificing all the other things one might be doing instead, like hanging out with your friends or finding a mate, just in order to win? Not to mention the ability to be motivated by such meager rewards as promotion, raise, bragging rights? This is a huge advantage.
It’s not hard to come up with an evolutionary explanation for why women might, on average, be less interested in acquiring wealth and/or winning for its own sake. This does not mean that any given woman will not have whatever it takes to be the best computer whatsis at Google, as Damore himself earnestly declared in his memo. It is, instead, an alternative explanation for the unequal representation of men and women in a given arena.
One could argue—Damore does—that alterations in the workplace that accommodate women might be worth making.
That is, when an employer is faced with a dramatic imbalance between male and female workers (or black and white/asian workers, or whatever) there are any number of explanations that could be and should be proposed and investigated. It might be a matter of biased hiring practices, or a hostile work environment. It could also be that there are not enough qualified female (or black, or whatever) applicants emerging out of the universities. Perhaps the hours required are incompatible with family life, something that many men also find burdensome, and this can be adjusted. More family-friendly expectations could improve the lives of male as well as female workers and thereby improve the overall productivity of the company as well as—- incidentally—increasing the percentage of female programmers. If, however, the ratio of male to female computer geeks never reaches 1:1, so be it.
I am often asked (in tones of deep suspicion) why there aren’t more female game wardens. Surely the wild imbalance (50:1) is the result of sexism in hiring and retention practices? I have to explain that no, in fact our agency actively seeks out female applicants and tries hard to support and encourage them. We draw, however, from what is already a small pool—most women (most people, if it comes to that) are mysteriously uninterested in law enforcement as a career, and the few that are tend to be drawn to municipal agencies where there is more back-up, more predictability in terms of scheduling, and far less sheer solitude. Given that wardens have to be prepared to live in remote camps far from even small-scale civilization, to drag dead moose out of the woods, walk for miles over rough terrain searching for lost persons, sit in cold fields all night to catch night hunters, fight said night hunters if they don’t feel like being arrested, ride snowmobiles through blizzards… well, it’s a rare (tho’ awesome) woman who really wants to be a game warden. I don’t think it’s a coincidence that, at the moment, none of our female wardens has children. (Just about all the male ones do).
Some of these factors can be tweaked a little—anyone who needs an extra ‘come-along’ winch installed to help with the moose-hauling can have one, for example. But ultimately, the job is what it is. And it needs to be done.
When used as a shorthand, it’s not even particularly wrong. “Men make better firefighters than women” isn’t absolutely correct: some women make excellent firefighters. But if that statement is uttered in informal conversation, it’s a reasonable representation of reality and thus entirely forgivable.
Damore was careful (and correct) not to toss out “men make better Google computer geeks than women.” His was a thoughtful argument, one that a reasonable person could engage. They did not engage. They didn’t make a better argument. They just did what they could to silence him. It’s embarrassing.
I absolutely want to weigh in to this conversation (so HI! School started! I’m back!)
First, Mr. Epstein – when I first started reading here, you were very unreasonable about our newly elected president and I came away with a very bitter view of you, however the last few months, you have demonstrated why so many people here respect you. I have appreciated nearly every single post you have made outside those surrounding the election. Thank you for your contributions here and your participation. It really is an honor.
When this story first broke, I read Mr. Damore’s memo and came away absolutely agreeing with it. I liked his proposition on ideas for recruiting and retaining women – changing the work environment. I have participated in similar initiatives when it came to recruiting and retaining young people into DoD work. I am a woman who was involved in software engineering in a stressful environment.
I don’t know what my IQ is/was (it changes… and having babies makes you stupid [I exaggerate]), but I scored a 1300/1600 on the 2001 SAT with a 660/640 verbal/math split. I have been told this puts me somewhere around the +1.5-2 SD IQ range, so not stupid. I wanted to be a housewife and mother (read, epic lack of ambition), so going to college was primarily an exercise in wanting to absorb information and exercise my brain (much like my participation at Ricochet!). I didn’t want to go to a fancy college, I wanted my full ride scholarship, and I wanted to pursue something that I enjoyed that I could dovetail into something that made enough money to survive and pay my bills. After all, if the goal is motherhood, the only person I’d be supporting on my income alone was ME. And I really didn’t need much. Feminism failed me.
This is the attitude that brought me to my place of hire who claimed a policy of work-life balance (this is a lie and only to get you in the door). In practice, this company demanded overtime as evidence of productivity. Mid-level managers are the death of good intentions. I refused to play that game, wanting to find a suitable husband. I did find one, eventually, married and had a baby… tried to get part time work at the company (they claimed they offered) but was pushed to a program notorious for its unreasonable demand of overtime in a company already known for its overtime demands (70-80 hour work weeks for people in that program). Part time would have been 40 hour work weeks. I quit.
Now, I watch my kids, sew, and occasionally do a contract project in VBA. I like this better. Working in engineering felt like a slow death.
Mr. Damore made some incredibly excellent points and I wish they had taken him at his word and given him some serious consideration.
I think there are way too many factors involved for us to ever be able to reach any valid conclusions about why people make the choices they do. Our aim as a society should be to keep all of the doors open and not worry about who chooses what.
Exactly.