Scary but Artificial intelligence...😊😊

Ordering a Pizza in 2021
CALLER:
Is this Pizza Delight?
GOOGLE:
No sir, it's Google Pizza.
CALLER:
I must have dialed a wrong number. Sorry.
GOOGLE:
No sir, Google bought Pizza Delight last month.

Today we’re going to talk statistics and semantics. I’m going to do so via the medium of one of Twitter’s favourite stats 1.7% (aka “intersex is as common as red heads.”). The statistic comes from Fausto-Sterling’s work, which you can see a review of

To understand the statistic, we have to drill down into what the meaning of the word intersex is. Most people think of hermaphrodites. Let’s stress at the beginning there has been no example ever of a human being with both sets of working reproductive organs.

There is a very tiny percentage of people who are born with both testicular and ovarian tissue (what Fausto-Sterling calls “true hermaphrodites”). And when I say tiny, we’re talking intersex tiny, as in 0.0117/1,000 live births, or one in 1,000,000. These are very complex cases.

So, how do we arrive at 1.7%? What Fausto-Sterling does is apply a wider scope. Instead, she argues that intersex is anything that doesn’t fit into a platonic ideal. The platonic ideal, in this case, being a phenotypically perfect XX female and a phenotypically perfect XY male.

This means that intersex, used in the context of the 1.7% statistic, includes people for whom there is no sexual ambiguity. Take for example Klinefelter syndrome (XXY males). As Fausto-Sterling acknowledges, many males can go their whole life and not realise they are XXY.

Last up in Privacy Tech for #enigma2021, @xchatty speaking about "IMPLEMENTING DIFFERENTIAL PRIVACY FOR THE 2020

Differential privacy was invented in 2006. Seems like a long time but it's not a long time since a fundamental scientific invention. It took longer than that between the invention of public key cryptography and even the first version of SSL.

But even in 2020, we still can't meet user expectations.
* Data users expect consistent data releases
* Some people call synthetic data "fake data" like
"fake news"
* It's not clear what "quality assurance" and "data exploration" means in a DP framework

We just did the 2020 US census
* required to collect it by the constitution
* but required to maintain privacy by law

But that's hard! What if there were 10 people on the block and all the same sex and age? If you posted something like that, then you would know what everyone's sex and age was on the block.

@zkat__ I'm in the position that I actually find npm / yarn the best ecosystem. Whenever I use something else I always end up stubbing my toe into something thats missing / feels wrong.

Ex. Cargo seems to neither have a concept of devDependencies nor peerDependencies.

I also can't understand why it wouldn't have an "add" command to add a new dependency. And I'm no fan of Toml, json is greate (easy to parse and build tooling around), and the better option in my opinion would be json5.

C / C++ seems to just not have language package managers. The linux / bsd crowd seem to have decided that the system package manager also should be the language package manager. Which might have been fine if every Linux distro used the same system package manager.

Instead we end up with a N x M problem. Where we have a bunch of different operating systems and they all support multiple system package managers. So there's no easy way of distributing, referencing and updating C / C++ packages.

It is also my opinion that the compiler / runtime should be a package dependency. I don't like Rust's split between rustup and cargo (they should have been one tool). Similarly it would be better if you added Node as a dependency to package.json, that way we wouldn't need NVM.