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

3

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 psychology perspective 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. ________________________ ___________________________ _________________________

3