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Comment by belorn | Hacker News Reader

People who work in CS are known to work with scientific methods. "What if" is simply not enough.

To be termed scientific, a method of inquiry must be based on empirical and measurable evidence subject to specific principles of reasoning.

We, that is people who work in the field of computer science, need to demand more than guesses and beliefs when dealing with "solutions" to gender inequality. If someone has an ideas on how to improve the community and industry, those ideas need to be first tested and validated using the scientific method. Testing in Social studies are not a new concept, so we already got the tools we need.

If "woman in CS" programs can help to get women with intellect and passion into CS, it should be testable. Do that first, and then argue for it use when there is data backing it up.

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"People who work in CS are known to work with scientific methods. "What if" is simply not enough."

That's hilarious. Try to remember this next time you put a print statement in the code or adjust some constant until it's right.

The problem here is that we have no way of either experimenting meaningfully or testing most of the things we'd like to know. We can describe tiny parts of reality and assume that some correlation is in fact causation, but without actually doing something it's impossible to conclusively prove what effect will any one action have.

That's nothing new - and it's not that unseen in programming, either. I think that "waiting for a proof" in this case is just an excuse; we need to get the best approximations, of course, but in the end we just need to find the courage to go and implement a solution without a certainty that it will be the best or even good.

In other words, when your service is on fire because thousands of users want to access it simultaneously (good for you) the first thing to do is to bring it back by any means necessary, including tools like intuition and wild guesses, and formalize the process afterwards.

In order to be testable there need to be a statistically significant number of women in CS programs so I assume from your comment that you arguing for them.

Or are you saying that these programs need to scientifically prove their value before existing in order to exist?

>Or are you saying that these programs need to scientifically prove their value before existing in order to exist?

Your wording is disingenuous. It is possible to run a case study and study on a limited scale a program that would be deployed at a much larger scale.

Your statement implies the idea is tautologically false, which it is not.

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