Social Finance Faces Sexual Harassment Claims | Hacker News Reader

Social Finance Faces Sexual Harassment Claims

nytimes.com

Wouldn't it be helpful to look at these in isolation?

Corporations routinely have these disagreements and dissatisfactions regardless of the sector.

"Another Silicon Valley Startup" versus just an article about SoFi?

Implying a pandemic of sexual harassment would seemingly indict corporate America as a whole, and it would be disingenuous to go sector by sector if the intention was to reveal the news.

Looking at these in isolation might give some the mistaken impression that these instances of workplace sexism and harassment are isolated incidents. When viewed as a whole, it's clearly a problem for software engineering (as people in the field have been claiming for years). In fact, I'd be willing to bet that we'll soon see comments full of anecdotes from people who have never seen sexism or this kind of harassment in their workplaces claiming that there is no problem. Or implying that this is somehow not all bad.

For sure this is an issue in many fields, but software engineering seems to be the only one in which people proudly proclaim there is no problem, despite the increasing number of reports to the contrary.

> I'd be willing to bet that we'll soon see comments full of anecdotes from people who have never seen sexism or this kind of harassment in their workplaces claiming that there is no problem.

I think this happens because people generally believe that a anecdote confirming the null hypothesis serves as evidence for that hypothesis. It's one of the best examples of something that scientists, engineers, and so-called "logical" thinkers screw up on a day-to-day basis.

In other words, suppose I claim that some days a subset of the population can see the earth's sky as green, rather than blue. My null hypothesis in this case is that the sky is blue and always will be for all people at all times. Finding several anecdotes from people who have seen the sky blue can never confirm my null hypothesis. They may have simply never seen the sky green.

In statistics, we can sort of work around this problem with p-tests or confidence intervals. In interactions with normal humans, I like to take the personal approach of always putting a little more weight in anecdotes that push against the null hypothesis. Just because they're contrarian, it doesn't mean their argument is more valid, but when you encounter something "outside of the norm" it's worth evaluating whether your sense of "normal" is more biased than you might think.

Erm, what? Encountering normalcy is evidence for things being normal. It might be weak evidence - after all, the "sometimes some people see the sky green" also predicts a lot of sky-looks-blue. But it's still evidence, you can't just throw it out because you've labeled it the "null hypothesis".

I'm not saying you throw it out. Read more carefully, don't put words in my mouth please.

> Finding several anecdotes from people who have seen the sky blue can never confirm my null hypothesis

were my words exactly. May I ask what issue you take with this wording? In your counter, you misinterpreted this and claim that I throw evidence out. My actual claim is such anecdotes actually do not serve as well as evidence.

As you said, you cannot throw out such evidence, and I agree. You seem to have misunderstood what I meant.

More importantly, you then fall prey to the exact logical fallacy I'm discussing while trying to counter me:

> Encountering normalcy is evidence for things being normal

False. False. False. False. This is legit the encapsulation of what makes this a fallacy. Consider the following thought experiment:

Suppose I give you a black box, and I ask you to prove to me that this machine works perfectly. You sit down and watch the machine, and you can verify that it is working perfectly right now. It is now logically impossible to prove the machine works perfectly at all times, however, because you lack any evidence the machine does not operate normally. You could watch the machine all day, and all night, for eternity, till the stars die in the sky. At any point while watching it, would you claim that you now have evidence the machine always operates normally? How do you know I haven't programmed it to break the instant you turn away from it? Or the instant you stop observing it? There's no way to know for sure...so do you have any evidence it's performing perfectly?

Anecdotal evidence is very similar. Many anecdotes re-affirming that all is working as planned don't tell me anything because that is the "null hypothesis". I take issue with your wording "because you labeled it the null hypothesis". I didn't label one or the other maliciously or even intentionally. The definition of the null hypothesis is (in my experience, I'm not a mathematician by trade) the scenario which is the "default" or "normal" or "expected". This fits both the scenario I gave and the analogy I make.

Again, I'm not saying I'm "throwing out" such evidence. In actual human interactions, we cannot swing the pendulum entirely the other direction and simply ignore and throw any evidence that confirms the "normal" either. In such a case, we would be making the exact same logical error except in reverse. I'm just trying to point to a general guideline based upon statistics and our usage of the null hypothesis within it.

Mathematical ideas do not map perfectly to worldly ones, but they serve as useful tools and models. In this case, I use my model to remind myself to consider anecdotes that are "abnormal" or "beyond the norm" as more important evidence since these "abnormal" events are the very things I want to be able to recognize.

A more rough "human" example might be: Say you give your cancer test results to five random doctors, and 4 of them say you're okay as expected, but one says you have cancer. My point is that the fifth doctor's evidence is more "important" (in a human, not mathematical way) to me than the other four. He could have found something they all missed.

I think we actually agree - if competing theories both expect a lot of "normal" to happen, you make much smaller updates on "normal" than on "abnormal". What I take issue with in particular is:

>I think this happens because people generally believe that a anecdote confirming the null hypothesis serves as evidence for that hypothesis.

It is evidence. It's not much evidence, and it's evidence you should expect from "unusual things sometimes happen"-type hypotheses, but it is evidence.

Maybe the phrasing I want is something like "People generally believe that anecdotes consistent with multiple theories help distinguish them". Dunno. Probably a lot of this is just Bayesian vs Frequentist worldviews talking past each other.

>It is now logically impossible to prove the machine works perfectly at all times

It's logically impossible to prove anything at 100% certainty. The best you can do is gather more observations and make incremental updates each time. I can give you what my belief is that my next observation will say that everything is fine (if I don't know anything else, it's Laplace's Rule of Succession - if I observe it 100 times at it all works, my confidence level for the next time is 101/102).

Ahhh, the raven paradox. [0] It is a major problem for inductive logic. Too bad so few are aware of it.

[0] https://en.wikipedia.org/wiki/Raven_paradox

I actually thing the increasing reports are due to the situation improving in that there is more training and institutional support for complaints. More people are complaining about less egregious behavior because they're more sure that their voice will be heard.

> When viewed as a whole, it's clearly a problem for software engineering (as people in the field have been claiming for years).

So then we should have an article quantifying that with a fancy NYTimes data visualization, instead of just forming a perception based on what is truly just a handful of articles.

I think they're trying to claim it's a pandemic in Silicon Valley culture, rather than a pandemic in business culture universally.

While I haven't seen many hard statistics on the matter, the cultural interpretation is definitely that SV has a hard time with women and minorities. Highly prominent examples in the news like Uber don't improve this image. Also the conversation around Google (regardless of your "stance") has been filled with vitriol lately.

While I'm still questioning where I stand amidst the Google stuff lately, it's pretty clear that there are some really screwed up people in this industry that legitimately think women can't do as well in this job (not saying Google was an example of this, it's just that story brought a lot of the roaches out from under the fridge).

Going by Google searches, it looks like the NYtimes has been writing a lot of stories about sexual harassment in SV. Some have been pretty click-baity opinion pieces, but overall I think their coverage has been quite good.

So my point is, this may not actually be a "pandemic" but SV is where this stuff is being talked about in context to. So it makes sense to frame the conversation as "Why is SV where all these stories are coming from anyways?"

(You could always just say that the "Fake Nytimes is just looking for clicks again" but I find that argument misses the forest for the trees.)

Pretty sure there are some really screwed up people in all industries. The first thing you need to control for is the male/female ratio.

If industry A has a 50/50 ratio and industry B 80/20, women in industry B will experience 4 times as much sexual harassment per person, even if the men in both industries are exactly as screwed up.

That makes some kind of sense but I'm not sure why it matters. If an 80/20 ratio magnifies the harassment problem by 4x (and, by the way, there's no guarantee the response is linear), then harassment will help reinforce the 80/20 ratio. And, anyways, either way: that's just a lot more sexual harassment.

Understanding problems always matter when trying to solve them.

If you think the problem is that industry B men are especially creepy, you'll try one set of solutions. If you think it's due to demography numbers, you try other ways.

Also, I guess I really like to understand the world...

But, again, the response to an increased proportion again isn't necessarily linear. That's an assumption you're making, but not questioning. It's easy to think of reasons why the response might be superlinear: for instance, the more sexual harassment exists, the more comfortable other men might get with stepping up to and crossing that line; similarly, the more men you have, the more trouble women might have reporting. And these things all feed back on each other.

(I think it's hard to come up with ways in which the response would be sublinear).

So it's easy to come up with straightforward scenarios in which you get both: the increase expected from demography, and a cohort of extra-creepy men sheltered by that demography.

> If industry A has a 50/50 ratio and industry B 80/20, women in industry B will experience 4 times as much sexual harassment per person.

Right, 4x of nearly 0 is still nearly 0. 4x of a problematic number is 4x as problematic. So your implicit argument, "even if men in both industries are exactly as screwed up" is a pivot point here.

Sexual harassment is illegal, unfair and unacceptable. Pretend for a moment (and I am pretending, I do not agree with this line of thinking) we agree with the biological essentialists and "men" are just more likely to go into software engineering. Given such a precondition, they actually have an obligation to be less "screwed up" than their counterparts in other more evenly distributed groups just to provide the same (legally and ethically mandated) standard of work to women.

So I don't see how your line of thinking is informative. Either SV doesn't meet the same standard as everyone else and needs to improve. OR, SV is naturally obligated to have a higher standard than everyone else just to be in compliance with the law and basic ethical requirements. Either way, we deserve censure as an industry.

If we genuinely believe in an industry based on merit and ethics, then either condition compels improved standards and expectations of conduct. So the outcome is the same, no matter what.

This doesn't really make sense, at least from how I've read your comment, once details come into play though. What does being 'less screwed up' actually look like at an individual level? Beyond not physically/verbally molesting my co-workers and not deceiving/resisting HR if there's an investigation into another co-worker's behavior I can only so much.

Exactly. If the boss is the one doing the harassing there's almost nothing you can do. I suppose you could be a witness for the harassment lawsuit. Actually attempting to police your boss is likely to just get you fired.

Well, you could start by supporting women and their opportunity in the field. You could corroborate and help report cases of sexual harassment. You could help predominantly male offices self-police on inappropriate workplace behavior (less talking about dicks, for example).

You can help establish salary baselines so women can identify unfair behavior.

Those are somewhat passive. If you want to be a net positive instead of just not a net negative in this equation, offering mentoring services to women in your field who may have had less opportunity than you is a good idea. Many organizations are eager to offer those opportunities but short of trustworthy professionals willing to donate time.

There is of course other simple things business owners can do. For example, not considering nursing rooms a luxury. Making time in people's schedules for child care (which affects many more women in the west than men, but still benefits men). There's also benefit leveling. For example, leveling paternity and maternity leave means that women are less "special" in these benefit packages, which helps prevent unfair punishment to them.

There really is quite a lot people can do.

A lot of these are good suggestions but they seem more like management level decisions than decisions that fall on the broader category of 'everyone in SV' which is what it seemed like you were discussing when you talked about SV bearing the responsibility.

Corroborating cases of sexual harassment is definitely something everyone can and should do but that's hardly a passive activity with the same being true for self-policing. On the other hand, things like mentoring require a non-trivial amount of labor that seems unfair to call morally obligatory and everything you listed under the business owner section isn't really possible for non-owners.

That's not to say everything is fine the way it is obviously, but lumping everyone together implies an equal capacity for action when most of the highest impact actions you mentioned require authority that the majority of employees don't have.

The majority of my suggestions are for the rank and file.

But, lots of engineering types end up with direct or indirect power in management.

The ones with direct power probably seized it with the support of their company's mechanized infantry.

golfclap

You're assuming it's engineering, but many of these articles are about VC and finance firms. The news just globs them all together under the banner of "Silicon Valley".

People won't generally click on a story about a waitress being sexually harassed, but they will if it's a story about some Silicon Valley company. That's about it.

Are these types of cases based on contingency?

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