Complete text of the email sent by Googler to his colleagues:
Google’s Ideological Echo Chamber
How bias clouds our thinking about diversity and inclusion
[AUTHOR NAME INTENTIONALLY WITHHELD]
Feel free to comment (they aren’t disabled, the doc may just be overloaded).
For longer form discussions see g/pc-harmful-discuss
Reply to public response and misrepresentation 1
Google’s biases 2
Possible non-bias causes of the gender gap in tech 3
Personality differences 4
Men’s higher drive for status 5
Non-discriminatory ways to reduce the gender gap 5
The harm of Google’s biases 6
Why we’re blind 7
Reply to public response and misrepresentation
I value diversity and inclusion, am not denying that sexism exists, and don’t endorse using stereotypes. When addressing the gap in representation in the population, we need to look at population level differences in distributions. If we can’t have an honest discussion about this, then we can never truly solve the problem.
Psychological safety is built on mutual respect and acceptance, but unfortunately our culture of shaming and misrepresentation is disrespectful and unaccepting of anyone outside its echo chamber.
Despite what the public response seems to have been, I’ve gotten many personal messages from fellow Googlers expressing their gratitude for bringing up these very important issues which they agree with but would never have the courage to say or defend because of our shaming culture and the possibility of being fired. This needs to change.
Google’s political bias has equated the freedom from offense with psychological safety, but shaming into silence is the antithesis of psychological safety.
This silencing has created an ideological echo chamber where some ideas are too sacred to be honestly discussed.
The lack of discussion fosters the most extreme and authoritarian elements of this ideology.
Extreme: all disparities in representation are due to oppression
Authoritarian: we should discriminate to correct for this oppression
Differences in distributions of traits between men and women may in part explain why we don’t have 50% representation of women in tech and leadership.
Discrimination to reach equal representation is unfair, divisive, and bad for business.
People generally have good intentions, but we all have biases which are invisible to us. Thankfully, open and honest discussion with those who disagree can highlight our blind spots and help us grow, which is why I wrote this document. Google has several biases and honest discussion about these biases is being silenced by the dominant ideology. What follows is by no means the complete story, but it’s a perspective that desperately needs to be told at Google.
At Google, we talk so much about unconscious bias as it applies to race and gender, but we rarely discuss our moral biases. Political orientation is actually a result of deep moral preferences and thus biases. Considering that the overwhelming majority of the social sciences, media, and Google lean left, we should critically examine these prejudices:
Compassion for the weak
Respect for the strong/authority
Disparities are due to injustices
Disparities are natural and just
Humans are inherently cooperative
Humans are inherently competitive
Change is good (unstable)
Change is dangerous (stable)
Neither side is 100% correct and both viewpoints are necessary for a functioning society or, in this case, company. A company too far to the right may be slow to react, overly hierarchical, and untrusting of others. In contrast, a company too far to the left will constantly be changing (deprecating much loved services), over diversify its interests (ignoring or being ashamed of its core business), and overly trust its employees and competitors.
Only facts and reason can shed light on these biases, but when it comes to diversity and inclusion, Google’s left bias has created a politically correct monoculture that maintains its hold by shaming dissenters into silence. This silence removes any checks against encroaching extremist and authoritarian policies. For the rest of this document, I’ll concentrate on the extreme stance that all differences in outcome are due to differential treatment and the authoritarian element that’s required to actually discriminate to create equal representation.
Possible non-bias causes of the gender gap in tech
At Google, we’re regularly told that implicit (unconscious) and explicit biases are holding women back in tech and leadership. Of course, men and women experience bias, tech, and the workplace differently and we should be cognizant of this, but it’s far from the whole story.
On average, men and women biologically differ in many ways. These differences aren’t just socially constructed because:
They’re universal across human cultures
They often have clear biological causes and links to prenatal testosterone
Biological males that were castrated at birth and raised as females often still identify and act like males
The underlying traits are highly heritable
They’re exactly what we would predict from an evolutionary psychologyperspective
Note, I’m not saying that all men differ from all women in the following ways or that these differences are “just.” I’m simply stating that the distribution of preferences and abilities of men and women differ in part due to biological causes and that these differences may explain why we don’t see equal representation of women in tech and leadership. Many of these differences are small and there’s significant overlap between men and women, so you can’t say anything about an individual given these population level distributions.
Women, on average, have more:
Openness directed towards feelings and aesthetics rather than ideas.
Women generally also have a stronger interest in people rather than things, relative to men (also interpreted as empathizing vs. systemizing).
These two differences in part explain why women relatively prefer jobs in social or artistic areas. More men may like coding because it requires systemizing and even within SWEs, comparatively more women work on front end, which deals with both people and aesthetics.
Extraversion expressed as gregariousness rather than assertiveness.
Also, higher agreeableness.
This leads to women generally having a harder time negotiating salary, asking for raises, speaking up, and leading. Note that these are just average differences and there’s overlap between men and women, but this is seen solely as a women’s issue. This leads to exclusory programs like Stretch and swaths of men without support.
Neuroticism (higher anxiety, lower stress tolerance).
This may contribute to the higher levels of anxiety women report on Googlegeist and to the lower number of women in high stress jobs.
Note that contrary to what a social constructionist would argue, research suggests that “greater nation-level gender equality leads to psychological dissimilarity in men’s and women’s personality traits. Because as “society becomes more prosperous and more egalitarian, innate dispositional differences between men and women have more space to develop and the gap that exists between men and women in their personality traits becomes wider.” We need to stop assuming that gender gaps imply sexism.
Men’s higher drive for status
We always ask why we don’t see women in top leadership positions, but we never ask why we see so many men in these jobs. These positions often require long, stressful hours that may not be worth it if you want a balanced and fulfilling life.
Status is the primary metric that men are judged on, pushing many men into these higher paying, less satisfying jobs for the status that they entail. Note, the same forces that lead men into high pay/high stress jobs in tech and leadership cause men to take undesirable and dangerous jobs like coal mining, garbage collection, and firefighting, and suffer 93% of work-related deaths.
Non-discriminatory ways to reduce the gender gap
Below I’ll go over some of the differences in distribution of traits between men and women that I outlined in the previous section and suggest ways to address them to increase women’s representation in tech without resorting to discrimination. Google is already making strides in many of these areas, but I think it’s still instructive to list them:
Women on average show a higher interest in people and men in things
We can make software engineering more people-oriented with pair programming and more collaboration. Unfortunately, there may be a limit to how people-oriented certain roles at Google can be and we shouldn’t deceive ourselves or students into thinking otherwise (some of our programs to get female students into coding might be doing this).
Women on average are more cooperative
Allow those exhibiting cooperative behavior to thrive. Recent updates to Perf may be doing this to an extent, but maybe there’s more we can do.
This doesn’t mean that we should remove all competitiveness from Google. Competitiveness and self reliance can be valuable traits and we shouldn’t necessarily disadvantage those that have them, like what’s been done in education.
Women on average are more prone to anxiety
Make tech and leadership less stressful. Google already partly does this with its many stress reduction courses and benefits.
Women on average look for more work-life balance while men have a higher drive for status on average
Unfortunately, as long as tech and leadership remain high status, lucrative careers, men may disproportionately want to be in them. Allowing and truly endorsing (as part of our culture) part time work though can keep more women in tech.
The male gender role is currently inflexible
Feminism has made great progress in freeing women from the female gender role, but men are still very much tied to the male gender role. If we, as a society, allow men to be more “feminine,” then the gender gap will shrink, although probably because men will leave tech and leadership for traditionally “feminine” roles.
Philosophically, I don’t think we should do arbitrary social engineering of tech just to make it appealing to equal portions of both men and women. For each of these changes, we need principled reasons for why it helps Google; that is, we should be optimizing for Google—with Google’s diversity being a component of that. For example, currently those willing to work extra hours or take extra stress will inevitably get ahead and if we try to change that too much, it may have disastrous consequences. Also, when considering the costs and benefits, we should keep in mind that Google’s funding is finite so its allocation is more zero-sum than is generally acknowledged.
The harm of Google’s biases
I strongly believe in gender and racial diversity, and I think we should strive for more. However, to achieve a more equal gender and race representation, Google has created several discriminatory practices:
Programs, mentoring, and classes only for people with a certain gender or race
A high priority queue and special treatment for “diversity” candidates
Hiring practices which can effectively lower the bar for “diversity” candidates by decreasing the false negative rate
Reconsidering any set of people if it’s not “diverse” enough, but not showing that same scrutiny in the reverse direction (clear confirmation bias)
Setting org level OKRs for increased representation which can incentivize illegal discrimination
These practices are based on false assumptions generated by our biases and can actually increase race and gender tensions. We’re told by senior leadership that what we’re doing is both the morally and economically correct thing to do, but without evidence this is just veiled left ideology that can irreparably harm Google.
Why we’re blind
We all have biases and use motivated reasoning to dismiss ideas that run counter to our internal values. Just as some on the Right deny science that runs counter to the “God > humans > environment” hierarchy (e.g., evolution and climate change), the Left tends to deny science concerning biological differences between people (e.g., IQ and sex differences). Thankfully, climate scientists and evolutionary biologists generally aren’t on the right. Unfortunately, the overwhelming majority of humanities and social sciences lean left (about 95%), which creates enormous confirmation bias, changes what’s being studied, and maintains myths like social constructionism and the gender wage gap. Google’s left leaning makes us blind to this bias and uncritical of its results, which we’re using to justify highly politicized programs.
In addition to the Left’s affinity for those it sees as weak, humans are generally biased towards protecting females. As mentioned before, this likely evolved because males are biologically disposable and because women are generally more cooperative and agreeable than men. We have extensive government and Google programs, fields of study, and legal and social norms to protect women, but when a man complains about a gender issue issue affecting men, he’s labelled as a misogynist and a whiner. Nearly every difference between men and women is interpreted as a form of women’s oppression. As with many things in life, gender differences are often a case of “grass being greener on the other side”; unfortunately, taxpayer and Google money is being spent to water only one side of the lawn.
This same compassion for those seen as weak creates political correctness, which constrains discourse and is complacent to the extremely sensitive PC-authoritarians that use violence and shaming to advance their cause. While Google hasn’t harbored the violent leftist protests that we’re seeing at universities, the frequent shaming in TGIF and in our culture has created the same silent, psychologically unsafe environment.
I hope it’s clear that I’m not saying that diversity is bad, that Google or society is 100% fair, that we shouldn’t try to correct for existing biases, or that minorities have the same experience of those in the majority. My larger point is that we have an intolerance for ideas and evidence that don’t fit a certain ideology. I’m also not saying that we should restrict people to certain gender roles; I’m advocating for quite the opposite: treat people as individuals, not as just another member of their group (tribalism).
My concrete suggestions are to:
As soon as we start to moralize an issue, we stop thinking about it in terms of costs and benefits, dismiss anyone that disagrees as immoral, and harshly punish those we see as villains to protect the “victims.”
Stop alienating conservatives.
Viewpoint diversity is arguably the most important type of diversity and political orientation is one of the most fundamental and significant ways in which people view things differently.
In highly progressive environments, conservatives are a minority that feel like they need to stay in the closet to avoid open hostility. We should empower those with different ideologies to be able to express themselves.
Alienating conservatives is both non-inclusive and generally bad business because conservatives tend to be higher in conscientiousness, which is required for much of the drudgery and maintenance work characteristic of a mature company.
Confront Google’s biases.
I’ve mostly concentrated on how our biases cloud our thinking about diversity and inclusion, but our moral biases are farther reaching than that.
I would start by breaking down Googlegeist scores by political orientation and personality to give a fuller picture into how our biases are affecting our culture.
Stop restricting programs and classes to certain genders or races.
These discriminatory practices are both unfair and divisive. Instead focus on some of the non-discriminatory practices I outlined.
Have an open and honest discussion about the costs and benefits of our diversity programs.
Discriminating just to increase the representation of women in tech is as misguided and biased as mandating increases for women’s representation in the homeless, work-related and violent deaths, prisons, and school dropouts.
There’s currently very little transparency into the extent of our diversity programs which keeps it immune to criticism from those outside its ideological echo chamber.
These programs are highly politicized which further alienates non-progressives.
I realize that some of our programs may be precautions against government accusations of discrimination, but that can easily backfire since they incentivize illegal discrimination.
Focus on psychological safety, not just race/gender diversity.
We should focus on psychological safety, which has shown positive effects and should (hopefully) not lead to unfair discrimination.
We need psychological safety and shared values to gain the benefits of diversity.
Having representative viewpoints is important for those designing and testing our products, but the benefits are less clear for those more removed from UX.
I’ve heard several calls for increased empathy on diversity issues. While I strongly support trying to understand how and why people think the way they do, relying on affective empathy—feeling another’s pain—causes us to focus on anecdotes, favor individuals similar to us, and harbor other irrational and dangerous biases. Being emotionally unengaged helps us better reason about the facts.
Our focus on microaggressions and other unintentional transgressions increases our sensitivity, which is not universally positive: sensitivity increases both our tendency to take offence and our self censorship, leading to authoritarian policies. Speaking up without the fear of being harshly judged is central to psychological safety, but these practices can remove that safety by judging unintentional transgressions.
Microaggression training incorrectly and dangerously equates speech with violence and isn’t backed by evidence.
Be open about the science of human nature.
Once we acknowledge that not all differences are socially constructed or due to discrimination, we open our eyes to a more accurate view of the human condition which is necessary if we actually want to solve problems.
Reconsider making Unconscious Bias training mandatory for promo committees.
We haven’t been able to measure any effect of our Unconscious Bias training and it has the potential for overcorrecting or backlash, especially if made mandatory.
Some of the suggested methods of the current training (v2.3) are likely useful, but the political bias of the presentation is clear from the factual inaccuracies and the examples shown.
Spend more time on the many other types of biases besides stereotypes. Stereotypes are much more accurate and responsive to new information than the training suggests (I’m not advocating for using stereotypes, I’m just pointing out the factual inaccuracy of what’s said in the training).