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Clock drawing is widely used as a test for assessing dementia. Sometimes the LLMs fail in ways that are fairly predictable if you're familiar with CSS and typic

Clock drawing is widely used as a test for assessing dementia. Sometimes the LLMs fail in ways that are fairly predictable if you're familiar with CSS and typical shortcomings of LLMs, but sometimes they fail in ways that are less obvious from a technical perspective but are exactly the same failure modes as cognitively-impaired humans. I think you might have stumbled upon something surprisingly profound. https://www.psychdb.com/cognitive-testing/clock-drawing-test https://www.psychdb.com/cognitive-testing/clock-drawing-test

TheJoeMan 11mo ago
Figure 6 with the square clock would be a cool modern art piece.
- yencabulator 10mo ago
  I have had this thought of a slow-moving mechanical simulation of a chaotic triple pendulum as a clock hand for a very long time.. Or maybe something like https://www.youtube.com/watch?v=dhZxdV2naw8 https://www.youtube.com/watch?v=dhZxdV2naw8
xrisk 11mo ago
Maybe explainable via the fact that these tests are part of the LLM training set?
jorgesborges 11mo ago
Conceptual deficit is a great failure mode description. The inability to retrieve "meaning" about the clock -- having some understanding about its shape and function but not its intent to convey time to us -- is familiar with a lot of bad LLM output.
overfeed 11mo ago
> Clock drawing is widely used as a test for assessing dementia Interestingly, clocks are also an easy tell for when you're dreaming, if you're a lucid dreamer; they never work normally in dreams.
- ghurtado 11mo ago
  In lucid dreams there's a whole category of things like this: reading a paragraph of text, looking at a clock (digital or analog), or working any kind of technology more complex than a calculator. For me personally, even light switches have been a huge tell in the past, so basically almost anything electrical. I've always held the utterly unscientific position that this is because the brain only has enough GPU cycles to show you an approximation of what the dream world looks like, but to actually run a whole simulation behind the scenes would require more FLOPs than it has available. After all, the brain also needs to run the "player" threads: It's already super busy. Stretching the analogy past the point of absurdity, this is a bit like modern video game optimizations: the mountains in the distance are just a painting on a surface, and the remote on that couch is just a messy blur of pixels when you look at it up close. So the dreaming brain is like a very clever video game developer, I guess.
  - tablatom 11mo ago
    Wait, lucid dreamers need tells to know where they are?!?
    - Kiro 11mo ago
      Yes, that's how you enter the lucid state. You find ways to tell that you're dreaming and condition yourself to check for those while awake. Eventually you will do it inside a dream and realize that you're dreaming.
    - Kiboneu 11mo ago
      Yeah. It’s very common to notice anomalies inside of a dream. But the anomalies weave into the dream and feel normal. You don’t have much agency to enter a lucid state from a pre-lucid dream. So the idea is to develop habits called “reality checks” when you are awake. You look for the broken clock kind of anomalies that the grandparent comment mentioned. You have to be open to the possibility of dreaming, which is hard to do. Consider this difficulty. Are you dreaming? … … How much time did it take to think “no”? Or did you even take this question seriously? Maybe because you are reading a hn comment about lucid dreams, that question is interpreted as an example instead of a genuine question worth investigating, right? That’s the difficulty. Try it again. The key is that the habit you’re developing isn’t just the check itself — it’s the thinking that you have during the check, which should lead you to investigate. You do these checks frequently enough you end up doing it in a dream. Boom. There’s also an aspect of identifying recurring patterns during prelucidity. That’s why it helps to keep a dream journal for your non-lucid dreams. There are other methods too.
ACCount37 11mo ago
LLMs don't do this because they have "people with dementia draw clocks that way" in their data. They do it because they're similar enough to human minds in function that they often fail in similar ways. An amusing pattern that dates back to "1kg of steel is heavier of course" in GPT-3.5.
- kaffekaka 11mo ago
  How do you know this? Obviously, humans failing in these ways ARE in the training set. So it should definitely affect LLM output.
  - ACCount37 11mo ago
    First: generalization. The failure modes extend to unseen tasks. That specific way to fail at "1kg of steel" sure was in the training data, but novel closed set logic puzzles couldn't have been. They display similar failures. The same "vibe-based reasoning" process of "steel has heavy vibes, feather has light vibes, thus, steel is heavier" produces other similar failures. Second: the failures go away with capability (raw scale, reasoning training, test-time compute), on seen and unseen tasks both. Which is a strong hint that the model was truly failing, rather than being capable of doing a task but choosing to faithfully imitate a human failure instead. I don't think the influence of human failures in the training data on the LLMs is nil, but it's not just a surface-level failure repetition behavior.
BHSPitMonkey 11mo ago
I would think the way humans draw clocks has more in common with image generation models (which probably do a bit better with this task overall) than a language model producing SVG markup, though.

TheJoeMan 11mo ago

Figure 6 with the square clock would be a cool modern art piece.

yencabulator 10mo ago
I have had this thought of a slow-moving mechanical simulation of a chaotic triple pendulum as a clock hand for a very long time.. Or maybe something like https://www.youtube.com/watch?v=dhZxdV2naw8 https://www.youtube.com/watch?v=dhZxdV2naw8

xrisk 11mo ago

Maybe explainable via the fact that these tests are part of the LLM training set?

jorgesborges 11mo ago

Conceptual deficit is a great failure mode description. The inability to retrieve "meaning" about the clock -- having some understanding about its shape and function but not its intent to convey time to us -- is familiar with a lot of bad LLM output.

overfeed 11mo ago

> Clock drawing is widely used as a test for assessing dementia Interestingly, clocks are also an easy tell for when you're dreaming, if you're a lucid dreamer; they never work normally in dreams.

ghurtado 11mo ago
In lucid dreams there's a whole category of things like this: reading a paragraph of text, looking at a clock (digital or analog), or working any kind of technology more complex than a calculator. For me personally, even light switches have been a huge tell in the past, so basically almost anything electrical. I've always held the utterly unscientific position that this is because the brain only has enough GPU cycles to show you an approximation of what the dream world looks like, but to actually run a whole simulation behind the scenes would require more FLOPs than it has available. After all, the brain also needs to run the "player" threads: It's already super busy. Stretching the analogy past the point of absurdity, this is a bit like modern video game optimizations: the mountains in the distance are just a painting on a surface, and the remote on that couch is just a messy blur of pixels when you look at it up close. So the dreaming brain is like a very clever video game developer, I guess.
- tablatom 11mo ago
  Wait, lucid dreamers need tells to know where they are?!?
  - Kiro 11mo ago
    Yes, that's how you enter the lucid state. You find ways to tell that you're dreaming and condition yourself to check for those while awake. Eventually you will do it inside a dream and realize that you're dreaming.
  - Kiboneu 11mo ago
    Yeah. It’s very common to notice anomalies inside of a dream. But the anomalies weave into the dream and feel normal. You don’t have much agency to enter a lucid state from a pre-lucid dream. So the idea is to develop habits called “reality checks” when you are awake. You look for the broken clock kind of anomalies that the grandparent comment mentioned. You have to be open to the possibility of dreaming, which is hard to do. Consider this difficulty. Are you dreaming? … … How much time did it take to think “no”? Or did you even take this question seriously? Maybe because you are reading a hn comment about lucid dreams, that question is interpreted as an example instead of a genuine question worth investigating, right? That’s the difficulty. Try it again. The key is that the habit you’re developing isn’t just the check itself — it’s the thinking that you have during the check, which should lead you to investigate. You do these checks frequently enough you end up doing it in a dream. Boom. There’s also an aspect of identifying recurring patterns during prelucidity. That’s why it helps to keep a dream journal for your non-lucid dreams. There are other methods too.

ACCount37 11mo ago

LLMs don't do this because they have "people with dementia draw clocks that way" in their data. They do it because they're similar enough to human minds in function that they often fail in similar ways. An amusing pattern that dates back to "1kg of steel is heavier of course" in GPT-3.5.

kaffekaka 11mo ago
How do you know this? Obviously, humans failing in these ways ARE in the training set. So it should definitely affect LLM output.
- ACCount37 11mo ago
  First: generalization. The failure modes extend to unseen tasks. That specific way to fail at "1kg of steel" sure was in the training data, but novel closed set logic puzzles couldn't have been. They display similar failures. The same "vibe-based reasoning" process of "steel has heavy vibes, feather has light vibes, thus, steel is heavier" produces other similar failures. Second: the failures go away with capability (raw scale, reasoning training, test-time compute), on seen and unseen tasks both. Which is a strong hint that the model was truly failing, rather than being capable of doing a task but choosing to faithfully imitate a human failure instead. I don't think the influence of human failures in the training data on the LLMs is nil, but it's not just a surface-level failure repetition behavior.

BHSPitMonkey 11mo ago

I would think the way humans draw clocks has more in common with image generation models (which probably do a bit better with this task overall) than a language model producing SVG markup, though.