Arguably Apple not focusing on women's health for the longest time could have also been mitigated by more female product people as well.
Taking the example to the logical extreme I doubt the bug would have hit production if the entire development team was dark-skinned.
This one is funny/sad: https://gizmodo.com/why-cant-this-soap-dispenser-identify-da...
More history: https://priceonomics.com/how-photography-was-optimized-for-w...
Not a product, but musicians and gender: https://www.theguardian.com/women-in-leadership/2013/oct/14/...
We build to our biases, and groups of people integrate their own collective bias into all their decisions. It would be difficult to argue otherwise, I think.
[1] http://leevinsel.com/blog/2013/12/30/why-carmakers-always-in...
"Why Diverse Teams Are Smarter" - HBR [1]
"Diversity and Work Group Performance" - Stanford [2]
"New Research: Diversity + Inclusion = Better Decision Making At Work" - Forbes [3]
There's a drumbeat of this stuff, both old and new, that comes out constantly.
[1] https://hbr.org/2016/11/why-diverse-teams-are-smarter
[2] https://www.gsb.stanford.edu/insights/diversity-work-group-p...
[3] https://www.forbes.com/sites/eriklarson/2017/09/21/new-resea...
I’m certain that there is a legitimate reason for the effect, but people are right to be skepical without any exploration of the cause. Are diverse teams more likely to disagree? Do they exhibit complementary recall of facts? Different modes of creativity?
I think a more complete explanation of causality would result in a much more concerted effort to increase diversity and a lot less resistance. As it is, it feels like the diversity ‘lobby’ is actually trying to create controversy instead of proving value.
When these people push for diversity they often mean "have every skin tone represented in your team photos". While this feels nice and would certainly repel any accusations of not being "diverse enough" it is the wrong kind of diversity. Now here is my "common sense" argument:
What people actually want is a diversity of opinions. This you can imagine having a positive effect on performance as each member of a team would have a slightly different take on things that may allow the group to discover a better solution. This would explain why the diversity of skin tone type approach somewhat works, as different races usually have different experiences, which usually means more diversity of thought when compared to a completely homogeneous group.
The obvious drawback to diversity of thought is that it's harder to quantify and optimize for. Anyone can look at a team photo and tell if a race is over/underrepresented because we have evolved incredibly advanced pattern recognition abilities. You can't easily tell what someone's opinions are without talking to them for a little while. Management already has trouble hiring qualified candidates since they don't know what qualified candidates look like, so adding diverse thinking to the list of criteria just exacerbates the hiring problem. Plus if you actually could select thought diverse candidates you run the risk of not including all races, opening yourself up to accusations of bias that can be devastating in today's politically charged climate.
Social science can't accurately model single humans well, let alone groups of humans as they attempt to solve problems. Even my analysis that we really ought to be concerned with diversity of thought is based on intuition rather than experimentation. It's a hard problem domain, and the solutions may not be intuitive.
The reason that social science can't model (aka overfit) many phenomena, is that it involves strictly nonlinear data where cultures and humans are involved.
Do some reading. Educate yourself. You may change your vantage.
Right, they currently can't accurately model the phenomena and thus their models have little to no predictive power. We are in agreement then. Also, it seems to me that social sciences tend to produce models that are underfit rather than overfit.
So why then do we accept conclusions from scientists who have weak models with little predictive power? This is what my comment above was talking about.
>This is pure, uneducated rubbish.
It's definitely not uneducated and I don't think it's entirely rubbish either.
More importantly, they don't get into causality. Most diversity studies show correlation.
The problem is - as companies get very big and stable, they can start to worry about diversity, and have such hiring programs.
Early on, nobody has time to worry about anything but just getting the best people they can at the time, possibly in a panic.
So, looking for diversity is often a case of sampling the winners.
I'm not so cynical about diversity, but I am about the voices promoting it, who are often heavily biased.
Diversity is polarizing topic, and like with all such things ... it's hard to get good data points.