Can someone do an executive summary or tl,dr please,
I honestly tried to read it but found it impenetrable.
I honestly tried to read it but found it impenetrable.
Also she reminds that there are always live world and live people behind any computer or mathematical model, and all models are incomplete by definition.
Most of development is about lossy processes.
All of the original hacker ethics should be changed; revised. She posits an example and attempts to break down the strategy used.
Unless of course you think women aren't clever or skillful...
> The mention of Margaret Hamilton in this passage is one of maybe three instances in the entire book in which a woman appears who is not introduced as the relative or romantic interest of a man. And even in this rare instance, Levy’s framing trivializes Hamilton, her work, and her right to the facility. She was “a beginner programmer” who was “officially sanctioned” but also just “showed up.” And she “complained” about it, leading to repercussions and reprimands. Levy is all but calling her a nag.
I don't know what other way to characterize that as a focused topic (tacit misogyny). It was not further discussed. I think you (along with a bunch of other people debating some nonsense about feminism) are having some weird kneejerk because you choose to interpret that part of the talk differently. The meaning was clear to me.
She's upset that some guys appeared immature back in the day towards a female programmer, and attempts to deconstruct the hacker manifesto and suggest a replacement that can be summarized as: "Be aware of your actions"....
Along the way she posits that because technology can't capture the analog infiniteness of our infinite universe due to it's digital nature that "Technology is forgetting". She uses examples like: loss in converting audio to digital, and compression loss of uneeded information to support this theory....
Thank you for your summary.
This article pushes for an ethics and feelings based redistribution of programming effort. That's bad. Because resources remain finite, we won't lose less data, we can only shuffle around what we lose. What we need to make this decision, is not feelings or vague ethical codes. We need hard data, especially in an age of big data and machine learning where the detailed pieces involved in making a deep statistical analysis may well be out of the realm of human comprehension.
For example, this article targets the evil gender binary. If only we would think more carefully about our choices. Meanwhile, clinics are scratching their heads trying to figure out how to map rates of ovarian cancer to "demisexuals", or how a local rise in "non-binary asexuals" might affect rates of testicular cancer, and what should be done about funding for screenings.
We lose data because we come from an era where space was limited, and cycles were counted. Sure we made some dumb mistakes like 2 digit years, but 2 digit years still work in a broad array of cases so we still use them all over the place today. They are sometimes good to use, sometimes bad, sometimes they're superfluous and unused anyway.
By all means rethink what fields should be compressed or expanded based upon business needs. But do it based on data and business use cases, not on feelings and someone's personal bias- even if that person promises their ethics are better than the old ones.
We need to be willing to explore the assumptions, known or unknown, that we carry with us when we create software.
Software doesn't exist in a vacuum. It is part of a rich, ever changing context of culture, social systems, and all the messiness of being human.
Each human action is the expression of a complex set of viewpoints, and technology is not perfectly neutral. I think, occasionally, some (not all) hackerish types are less interested in exploring this side of things and think they can avoid it by sticking with software. The essay was trying to remind people that you can't truly avoid expressing viewpoints with your actions, even in software.
Hear, hear.
I have two other longstanding favorite examinations-of-assumptions pieces: "Falsehoods Programmers Believe About Names"[0], and "Five Geek Social Fallacies"[1]
[0] https://www.kalzumeus.com/2010/06/17/falsehoods-programmers-...
This is a great case in point! Simply classing people as male or female already loses data that's therapeutically relevant. The important thing in determining whether someone's at risk of ovarian or testicular cancer isn't whether they're male or female - it's whether they have ovaries or testes. Some people have both, some people have neither and some people do not have the set you'd expect from their gender. Assuming that "Male" or "Female" accurately describes this is exactly the kind of "forgetting" discussed in the article, and people lose out on appropriate healthcare as a result.
I don't think this particular combination is possible, for the record.