Consciousness is not strictly binary but works like a dimmer switch: there's a real on/off threshold, but above that threshold it comes in degrees, so it can be more 'on' for a human than for a dog, a mouse, or an ant.
Cameron Berg proposes a 'dimmer switch' model of consciousness that preserves both the binary intuition (circuit open/closed) and the graded intuition (more or less current), letting him coherently say consciousness is both on/off and a matter of degree. ✦ AI generated
Cameron Berg · The Cognitive Revolution · 2026-06-27 · original ↗
starts at this moment · 2:56
“Is consciousness all or nothing or a matter of degree? And if it's a matter of degree, can you put a number on where a given model falls?”
The analogy that I reach for here is something like a dimmer switch where I think you can basically accommodate both the binary intuition and the sort of continuous intuition. You know, if you have a light with a dimmer switch, like really it is either on to some extent or it is not. And that is a real and meaningful difference. Either the circuit is open or the circuit is closed.
verbatim transcript · starts at 2:56
2:57the binary intuition and the sort of continuous intuition. You know, if you have a light with a dimmer switch, like really it is either on to some extent or it is not. And that is a real and meaningful difference. Either the circuit is open or the circuit is closed. With that being said, you can have you know electricity running through the circuit to greater or lesser extents. And that's also sort of a real
3:16thing. This I think enables me to uh you know sound coherent when saying things like it's really off for the table and it's really on for you but I think it's more on for you than it is for a dog than it is for a mouse than it is for an ant. And so that's my own view. This is to some degree intuitive again because we don't have really strong grounding
3:35here. I'm sort of just like giving you a dressed up vibe. But that that is sort of my my sense and I think it's fairly parsimmonious. And the other thing I would say about this is I'm actually doing some work with Patrick Butland right now at Ilios trying to basically operationalize some of these indicators of consciousness. So this is sort of like what I was describing. We can look
3:52at these major theories of consciousness. They make specific predictions about what we would expect to see in uh systems that are conscious architecturally and functionally. And then we can literally just go in to a given system and evaluate whether or not those predictions are borne out. And so this is really hard to do with human experts. You know, you got to get someone who's like you want to do this
4:11with B cognition. You got to go find a B cognition expert and then you got to explain to them what ignition events are in global workspace theory and then you got to, you know, get them to this just isn't a scalable approach for really evaluating the system. But my sort of grand innovation here is just throwing smart LLMs at this problem. Uh, and then being able to just scale the crap out of
4:30it so that we can evaluate given any description of an architecture of a nervous system architecture, biological, artificial, whatever, to what degree for each of these sort of indicator properties that are suggested by these consciousness theories, uh, do we see those properties realized in these systems? And so we can actually go in and do this. And what you get out once you run this with a bunch of seeds, a
4:49bunch of different trials, a bunch of different judges checking each other, this sort of thing, are some like really interesting uh, implied probability uh, numbers. I wouldn't say these are exactly implied probability that the system is conscious. It's maybe more like implied probability of like consciousness relevant features given these theories. If you don't buy any of these theories then like everything downstream of this doesn't really matter