Links, dumped

A grab-bag of delicious miscellania.

It’s Saturday, which means: time for a linkdump post! I’m back from my book-tour across the US, Canada and the UK, finishing up in Berlin — and I’m jetlagged in the backyard hammock, waiting for my laundry to come out of the machine and plowing through a long backlog of interesting links. Let’s goooooooo!

It’s Pride month, and Pat Robertson kicked it off with a bang by…kicking off. What better way to start Pride than with a piece of fanfic by Wil Wheaton about Robertson’s arrival in Hell?

https://wilwheaton.net/2023/06/the-wait/

Once you’ve had your fill of schadenfreude, get your Pride/Trekkie (or, if you prefer, Trekker) gear on with Wil’s Acting Ensign Pride collection:

https://shopstands.com/collections/wil-wheaton

Seguing smoothly into science fiction by way of Trek, let’s turn to Ted Chiang, a titan of the field, who is also a wicked-sharp critic of AI hype. Ted’s been at this since at least 2017, when he identified tech CEOs’ fears of AI as a form of transference of their fear of corporations, which are, after all, autonomous artificial life-forms that are rapidly devouring the human race:

https://www.buzzfeednews.com/article/tedchiang/the-real-danger-to-civilization-isnt-ai-its-runaway

When it comes to inventing catchy, devastating metaphors for AI, this is Ted’s busy season. “AI is a blurry JPEG of the web”:

https://www.newyorker.com/tech/annals-of-technology/chatgpt-is-a-blurry-jpeg-of-the-web

It’s also “the new McKinsey & Co”:

https://www.newyorker.com/science/annals-of-artificial-intelligence/will-ai-become-the-new-mckinsey

And now, in the Financial Times, Ted sits down for lunch with Madhumita Murgia to talk about the linguistic game we play when we describe a statistical inference tool as “artificial intelligence,” given that it is neither “artificial,” nor “intelligent”:

https://www.ft.com/content/c1f6d948-3dde-405f-924c-09cc0dcf8c84

Start with whether machines “learn”: “machine learning” is just adjusting weights in a statistical model. When you teach a child something, you’re not adjusting…