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Published · transcript-backed

Mentions personal use of Ted Chiang.

6 Feb 2026 Latent Space The First Mechanistic Interpretability Frontier Lab — Myra Deng & Mark Bissell of Goodfire AI

“You were very excited because I read Ted Chiang over the holidays and I was very inspired by this short story called Understand, which apparently is, like, pretty old.”

— Shawn Wang

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Speaker
Shawn Wang
Attribution
Verified speaker
Claim type
recommendation
Recorded
6 Feb 2026
Publisher
Latent Space

Transcript context

…Well, it’s just, it’s the problem of induction, right? All of ML is based on induction. And it’s impossible to say, I have a physics model. You might have a physics model that works all the time, except when there is a character wearing a blue shirt and green shoes. And, like, you can’t disprove that that’s the case unless you test every particular situation your model might be in. Yeah. So we know that the laws of physics apply no matter. Where you are, what scenario it is. But from a model’s perspective, maybe something that’s out of distribution. It just never needed to learn that the same laws of physics apply there. Yeah. You were very excited because I read Ted Chiang over the holidays and I was very inspired by this short story called Understand, which apparently is, like, pretty old. You must be familiar with it. To me, it was like, it’s this fictional story. It’s like the inverse of Flowers for Algernon, where you had someone, like, get really smart, but then also try to outsmart the tester. And the story just read, like, the chain of thought of a superintelligence, right? Where they’re like, oh, I realize I’m being tested. Therefore, and then, okay, what’s the consequence of being tested? Oh, they’re testing me. And if I score well, they will use me for things that I don’t want to do. Therefore, I will score badly. And, like, but not too badly that they will raise alarms. So model sandbagging is a thing that people have explored. But I just think, like, Ted Chiang’s work just in general seems to be something that inspires you. I just wanted to prompt you to talk about it. I think, so Ted Chiang has two, is a sci-fi author who writes amazing short stories. His other claim to fame is Stories of Our Lives, which became the movie Arrival. Exactly, yeah. So two books of short stories that I’m aware of. He also actually has a great just online blog post. I think he’s the one who coined the term of LLMs as, like, a blurry JPEG of the internet. I should fact check that, but it’s a good post. But I think almost every one of his short stories has some lesson to bear. I’m thinking about AI and thinking about AI research. So, you know, you’ve been talking about alien intelligence, right, in this AI human communication translation problem. That’s, you know, exactly sort of what’s going on in Arrival and Story of Your Life. And just the fact that other beings will think and operate and communicate in ways that are not just challenging for us to understand, but just fundamentally different in ways that we might not even be able to expect. And then the one that’s just. Super relevant for interpretability is the other short book of short stories he has is called Exhalation. And that is literally about a robot doing interpretability on its own mind. Oh, OK. So I just think that that, you know, you don’t even have to squint to make the analogies there.…

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