For black CEOs in Silicon Valley, humiliation is a part of doing business

I've recently been reading/watching some videos and writings by Robin Diangelo on systemic racism - here's a great starting point: https://www.youtube.com/watch?v=h7mzj0cVL0Q. She also wrote the book "White Fragility".

Thinking about that, I'm just wondering how different it would be if one of those people who mistook the employee for the CEO instead turned to the CEO and said "I'm sorry, please excuse me for the instance of racism I just perpetrated against you, I promise it won't happen again." I realize how outlandish that may sound writing that out, but I'd propose that the fact that it does sound outlandish is the main problem. Everyone in the US was raised in an environment that inculcated certain racial ideas, subconsciously or not. We can't address them if we're so embarrassed by their existence as to pretend they don't exist.

While I completely agree that the stories in this article are hugely problematic and represent issues that need to be solved, I think books like "White Fragility" are not helpful in solving them. This is due to a focus on group identity, and describing "White" as if it's a monolithic group of people, all with the same culture, emotions, and reactions.

Another interesting aspect I identified while reading the book was it's description of the emotions that one can expect to see when confronting white people about race issues: the description could have been used to describe any human being you will ever meet when you accuse/blame them for something that they did not personally do. It really does read like a horoscope in that sense.

I find it ironic that people on HN, who are typically super data driven, get on board with works like "White Fragility". Diangelo is one of many academics from the humanities departments who are incredibly pseudo-scientific. Data is incredibly scarce, measurements and studies even less so. Statistical knowledge isn't present in the vast majority of these folks. Typically, the "scientific method" is reading and writing essays/novels. When you don't attempt to quantify a problem, you can't propose solutions and then measure their results. You instead just keep yourself busy finding ever more ways to describe the water to the drowning person.

Meanwhile, a central point of the book is one that should be self evident. Talking about racism makes white people[1] uncomfortable. I know this to be true from experience. And we can't make progress as a society until we own that discomfort and are willing to have frank conversations about racism.

I don't see how you need "statistical power" to recognize this or adopt this strategy.

Also, this:

> ccuse/blame them for something that they did not personally do

That's not what the discomfort is about. Of course none of us are _personally_ responsible for the systemic racism in the US. But if we can't even talk about it without getting uncomfortable, how are we going to fix it?

1: If this doesn't apply to you, great, I wasn't talking about you [2]

2: Except if this topic makes you annoyed enough to disagree then yes, I probably am talking about you.

I am all for having frank conversations, but I think the topic needs to be broader than "racism". It needs to be "systematic inequality of treatment". Or even better, "systematic violations of basic human rights". Then we can focus on why our society, which is supposed to be based on everybody having the same basic human rights, is not achieving that in practice, and how to fix it. Focusing on one particular group of people whose rights are being violated only distracts from that overall objective.

Back in the 1960s, yes, that was a reasonable approach, and we took it. In your coding analogy, we believed there was a specific bug and started applying patches to address it.

But we've been doing that for more than half a century now and it hasn't helped. So now maybe we should consider whether the actual bug might be something else, requiring different patches to fix.