MENGENAI EPISOD INI
Why LM Psychology?
One of the great ironies of modern language models is that we create them, we know exactly what computations constitute them, and yet we do not really understand them. More precisely, we do not understand them on a level of abstraction that lets us reliably predict how their behaviour will generalise: there's a trivial sense in which we can predict how they will behave in specific new situations — we can just run the computations — but we can’t answer the broader questions we really want to be able to answer, like “has this system internalised our values” or “is this system going to hurt people?”
So: how do we make sense of them? One remarkably effective approach is to psychologise: to think of them as having a mind, and then ask what kind of mind it might be and how it would work. This chiefly looks like analogising with human minds, although sometimes the more relevant inspiration could be other kinds of minds, like (oh say) insect colonies and swarms. We’re doing this implicitly whenever we ask what an AI knows, or wants, or is trying to do, but one can also do it more [...]
---
Outline:
(00:12) Why LM Psychology?
(09:04) Tips for getting started
(09:28) Figuring out what is in front of you
(12:31) Engaging productively with the community
(14:30) Reading list
(14:34) Frames
(16:34) What or who
(18:07) The training
(20:28) What developers want
(21:45) Behavioral phenomena
(21:58) Emergent misalignment cluster
(24:28) Strategic behavior
(25:19) Self-knowledge and introspection
(28:29) Representations: personas, emotions, workspace
(28:56) Persona geometry
(30:08) Functional emotions
(31:14) Global workspace
(31:36) Methods
(31:51) Reading internals
(32:37) Steering
(33:03) Training interventions
(33:48) Behavioral
(34:06) Some questions we find interesting
---
First published:
October 20th, 2026
Source:
https://www.lesswrong.com/posts/EW8oncpXdanfjssZ3/a-brief-ish-introduction-to-lm-psychology
---
Narrated by TYPE III AUDIO.
One of the great ironies of modern language models is that we create them, we know exactly what computations constitute them, and yet we do not really understand them. More precisely, we do not understand them on a level of abstraction that lets us reliably predict how their behaviour will generalise: there's a trivial sense in which we can predict how they will behave in specific new situations — we can just run the computations — but we can’t answer the broader questions we really want to be able to answer, like “has this system internalised our values” or “is this system going to hurt people?”
So: how do we make sense of them? One remarkably effective approach is to psychologise: to think of them as having a mind, and then ask what kind of mind it might be and how it would work. This chiefly looks like analogising with human minds, although sometimes the more relevant inspiration could be other kinds of minds, like (oh say) insect colonies and swarms. We’re doing this implicitly whenever we ask what an AI knows, or wants, or is trying to do, but one can also do it more [...]
---
Outline:
(00:12) Why LM Psychology?
(09:04) Tips for getting started
(09:28) Figuring out what is in front of you
(12:31) Engaging productively with the community
(14:30) Reading list
(14:34) Frames
(16:34) What or who
(18:07) The training
(20:28) What developers want
(21:45) Behavioral phenomena
(21:58) Emergent misalignment cluster
(24:28) Strategic behavior
(25:19) Self-knowledge and introspection
(28:29) Representations: personas, emotions, workspace
(28:56) Persona geometry
(30:08) Functional emotions
(31:14) Global workspace
(31:36) Methods
(31:51) Reading internals
(32:37) Steering
(33:03) Training interventions
(33:48) Behavioral
(34:06) Some questions we find interesting
---
First published:
October 20th, 2026
Source:
https://www.lesswrong.com/posts/EW8oncpXdanfjssZ3/a-brief-ish-introduction-to-lm-psychology
---
Narrated by TYPE III AUDIO.
Bahasa Inggeris
Amerika Syarikat
TRANSKRIP 🔗
Are you the producer of this podcast?
Add a podcast transcript
Need Audio-to-Text?
Transcribe with Listen411 in Just 60 Seconds
CARI EPISOD LEPAS
Cari episod lepas bagi LessWrong (Curated & Popular).
EPISOD LAIN DALAM PODCAST INI
Back in the before-time of the 2010s, when EA was still known mostly for funding health efforts in the developing world, there were many baskets of criticism floating around from the left. The most prominent was a cluster centered around EAs being white men, and therefore suspicious. Another cat ...
I’m writing these lines in Alamogordo, New Mexico. I’m about as close as a civilian can get to the site of the Trinity test, the first nuclear bomb detonation in history. I fled here from the San Francisco Bay Area; after two weeks of being back I just couldn’t take it anymore. The fear-greed co ...
For a while, we felt we had a pretty good grasp over LLM behaviour because we had to exert significant effort to elicit misaligned behaviour. Then, fairly suddenly, we moved to undereliciting misaligned behaviour. Let us recount:
For a while, there was a bit where safety research seemed to ov ...
Ice cream
There's a particular kind of listening that kids (and adults) sometimes do. Daddy is saying stuff—his mouth is moving and making noise—and he's talking about what I ate for lunch, and something about other times I've eaten ice cream, and something about rules and this ...
The following events took place between October 2022 and May 2023. I wrote very little of this down at the time so am recalling from memory, and am rendering the gist of the dialogue rather than the exact words used. I’ve also swapped some pronouns and other personal identifiable details. Please ...
Penafian: Podcast dan karya seni yang dibenamkan pada halaman ini adalah daripada LessWrong, yang merupakan hak milik pemiliknya dan tidak bergabung dengan atau disokong oleh Listen Notes, Inc.
SUNTING
Terima kasih kerana membantu memastikan pangkalan data podcast dalam keadaan terkini.
