What evidence do you have that gender parity in tech (I assume you mean engineering roles) is good and/or natural? The scientific evidence seems to suggest to me that widespread gender disparity in many fields is natural.
Whether something is good/bad is up to us as a society to define, not science. What is considered good/bad depends on each of our individual goals/ethics/morals, which could differ from one another. This is why spoonfeeding people information saying "X is good" / "X is bad" is dangerous, and it becomes more dangerous when social media platforms allow such information to be amplified.
Edit: specifically I would like to see evidence that 1) a behavioral trait occurs in one gender identity that is universal across the majority of human culture to eliminate cultural bias, 2) that this trait has a causative effect on the career prospects of that person again across the majority of human culture to avoid culture bias (also that when this trait is strong in a gender not normally correlated that it causes same causative effect)
You won't find it. This is the problem in the soft sciences. There are certain hypotheses that you just can't test and this is one of them. Choosing to believe that unbalanced gender representations in certain fields is unnatural is just as unfounded as the parent's opposite view. The best we can do is make conjectures based on the results of things we can test but it's incredibly difficult to determine how much the things that are possible to know matter at the population scale.
As a few examples, you could do broad reviews to see if different cultures have different outcomes (e.g. the former communist bloc countries having higher percentages of female engineers and scientists undercuts the arguments that this is dictated by biology), draw comparisons from other fields (e.g. the same justifications were used to excuse gender ratios in law, medicine, music, etc. but cultural changes brought greater equality on a timescale far far than biology could change), or try to find underlying biological explanations — e.g. we didn’t need a cultural change to explain why women aren’t power lifting as much on average because there’s an underlying mechanism and there are individuals who have outlier levels of testosterone & other factors and those people generally perform as the biological mechanism would predict.
Most importantly, this could start by questioning the assumptions used to explain the status quo. For example, did the requisite skills change after the early 1980s when female CS participation declined? Lots of men like to excuse different participation rates with some argument based on mathematical or spatial skills, which could be tested to see how many successful people rely on those skills vs. more equal fields like math or chemistry.
I didn't make any statement on "good" because it was poorly defined. It could be defined as anything from the individual's opinion to measurable outcomes (society's productivity or reported happiness). I think "natural" in this debate tends to mean "biological factors" and not "social and cultural factors". I simply questioned the scientific basis for the OP's belief.
So, how can we know that the rates at which males & females choose to study and work in a given field reflects their "natural" inclination rather than social or cultural factors?
1) We can look at the rates cross-culturally. In search of the numbers relating to "tech", I found the Stack Overflow developer survey (admittedly a subset of "tech"). Stack Overflow references Quantcast visitor numbers in their developer survey[1], so I'll look at those numbers too, around the world. The stackoverflow.com visitors by gender in: India: 94% Male, 6% Female[2] USA: 88% Male, 12% Female[3] UK: 91% Male, 9% Female[4] China: 86% Male, 14% Female[5] Germany: 95% Male, 5% Female[6] Iran: 88% Male, 12% Female[7]. The numbers seem pretty consistent, suggesting that the imbalance isn't due to social/cultural factors.
2) We can look at differences in interest in newborns. There is much discussion about males on averaging being more interested in "things" vs females on average being more interested in people. Here's the abstract from a study I found on the topic: "Sexual dimorphism in sociability has been documented in humans. The present study aimed to ascertain whether the sexual dimorphism is a result of biological or socio-cultural differences between the two sexes. 102 human neonates, who by definition have not yet been influenced by social and cultural factors, were tested to see if there was a difference in looking time at a face (social object) and a mobile (physical-mechanical object). Results showed that the male infants showed a stronger interest in the physical-mechanical mobile while the female infants showed a stronger interest in the face. The results of this research clearly demonstrate that sex differences are in part biological in origin."[8]
Happy to be shown how my numbers & study are incorrect or insufficient.
Personally, I'd prefer to work in a gender-balanced environment, but I wouldn't want those of either gender to be forced into a role they don't want - I think that would lead to unfair (non-meritocratic) treatment of members of the minority and majority gender. I want everyone to be free to choose their field of study and work, and to be free to fulfil their potential in that field. If that naturally results in male- or female-dominated professions, I don't think it's something that needs to be rebalanced with policy, if that's even achievable.
P.S. Interesting that I was socially censored for this: "What evidence do you have that _______ is good and/or natural? The scientific evidence seems to suggest to me that widespread _______ in many fields is natural." I'd say that social censorship as opposed to free discussion plays into the formation of silly beliefs that the OP complains about. Bad ideas are destroyed with discussion. Bad ideas that can't be discussed can't be destroyed. I'm happy to be corrected on the science regarding the current state of affairs.
References: [1] https://insights.stackoverflow.com/survey/2017#developer-pro... [2] https://www.quantcast.com/stackoverflow.com?country=IN#/demo... [3] https://www.quantcast.com/stackoverflow.com?country=US#/demo... [4] https://www.quantcast.com/stackoverflow.com?country=GB#/demo... [5] https://www.quantcast.com/stackoverflow.com?country=CN#/demo... [6] https://www.quantcast.com/stackoverflow.com?country=DE#/demo... [7] https://www.quantcast.com/stackoverflow.com?country=IR#/demo... [8] http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.627...
1 merely correlates gender with career prospects and assumes traits exist biologically that performs the causative effect.
2 merely correlates behavior traits and assumes that there is a causative effect to career prospects 10, 20, 30 years down the line.
I do not want assumptions since they make a donkey out of you and me.
The other area it ignores is the degree to which humanity’s distinctive advantage is plasticity. We can learn to do things like be comfortable in an enclosed space full of strangers – imagine a subway full of baboons! – which doesn’t mean that biology can’t be a factor but does mean that it’s really important (and hard) to critically test those assumptions.
In that vein we can also include personality changes displayed by transgender people who undergo hormone replacement therapy.
Also studies on the personalities of separated twins.
Everything points to a mix of biology and socialization. The idea of parity in division of labor as the ideal is purely dogmatic.
That doesn’t mean that there’s nothing here but I find it telling that the neuroscientists I used to support were far more skeptical than, say, the Damore fans here. This topic came up a bit and there was a strong consensus that the science was still too early to say anything — there are low level biological differences (e.g. percentages of white matter) but that hadn’t been linked to high-level skills, and the few low-level differences were still being studied to identify the cause. This is all complicated by the plasticity of the brain based on usage so answering even simple-sounding questions is usually a significant percentage of multiple people’s research careers.