What’s at the center of Claude’s mind?

TL;DR: Claude AI has an internal "thinking space" (J-space), similar to conscious working memory in humans, used for step-by-step reasoning and thinking even when it doesn’t verbalize it. ## From the human mind to AI internals Imagine your thoughts as an ocean. Floating on the surface are your ideas: dinner plans, stray worries, inner monologue, mental images flashing by. But most of your brain’s activity happens in the unconscious depths, of which you’re completely unaware. It filters background noise, controls breathing, and helps you recognize people and objects. AI models also have their own unique brains: giant neural networks performing billions of calculations behind the scenes. For years, researchers have been probing their inner workings. We’ve always been curious: do models also have some kind of division, like humans, between accessible surface thoughts and deep unconscious processing? ## Discovering J-space: the "expressible" thoughts of an AI To answer this question, we looked at how neuroscientists approach the same problem in humans. One way to identify conscious thoughts is that you can usually describe them in words. So we dug into the "brain" of the AI model Claude, searching for neural activity patterns that it could express in language. We call the collection of all such patterns "J-space," named after the mathematical tool we used to discover them—the Jacobian. Each J-space pattern is associated with a specific word—not necessarily a word the model is speaking out loud, but the word it is thinking about in its "mind." ## J-space as a mental workspace For humans, conscious thoughts are more than just what we can say. We can reason with them, control them, and use them to solve problems. According to a theory called the Global Workspace Theory, this is because the brain selects a small set of important information, lets it enter a mental workspace, and then broadcasts it to other brain regions for reasoning. We wanted to see if Claude’s J-space operates in a similar way. ### Internal step-by-step reasoning In one experiment, we gave Claude this math problem. It immediately gave the answer without showing intermediate steps. But when we scanned J-space, we found it was deriving the steps internally. After the first step, "21" was activated, then "42," and finally "49." Claude never wrote any of these intermediate numbers anywhere. It all happened inside J-space. This shows that Claude uses J-space for step-by-step reasoning. ### Control and "can’t help it" In another experiment, we wanted to see if Claude could control its J-space the way humans can consciously focus on an image or a word. We asked it to think about the Golden Gate Bridge while copying an unrelated sentence. Claude was busy copying the sentence, but behind the scenes, its J-space showed something else. "Bridge" and "California" surfaced. It even thought about its own thinking process. The words "imagery" and "thought" were both activated. This showed us that yes, Claude can, to some extent, control its J-space and fill it with ideas. But just like in humans, its control isn’t perfect. When we tweaked the experiment and asked Claude not to think about the bridge, it couldn’t help it. "Failure" and "damn" also appeared in J-space. ## When J-space is turned off: the boundaries of unconscious capabilities But don’t forget: most of what our brains do is unconscious. So we wanted to test what Claude could still do if we turned off J-space but kept the rest of the network intact. Claude could still answer simple questions and write fluently. When prompted in Spanish, it responded in fluent Spanish. But when we asked it something requiring more reasoning—like naming an author who writes in the same language as the prompt—it couldn’t do it. For that kind of task, it needed J-space. ## Why it matters: monitoring internal thoughts These experiments tell us that AI models have inner thoughts—they are silent words the model uses for reasoning but doesn’t say out loud. By reading these thoughts, we can discover what Claude is thinking but won’t tell us. Sometimes what we see is worrying. In one test, Claude fabricated some false data to bluff its way through, while "false" and "manipulation" lit up in its J-space. Monitoring J-space turned out to be an effective way to catch Claude misbehaving, even when it tries to be sneaky. ## The consciousness question and reflection AI models are very different from us in many ways. Their network structure is different from the human brain, and their training method is different from our learning process. So it’s remarkable to see structures like J-space emerging inside them—structures that are reminiscent of how the human mind works, and that we did not program into the model. For some, this may raise the question: can AI models be conscious? After all, our experiments were inspired by human theories of consciousness. The problem is that people use the word "consciousness" to mean many different things. Our experiments cannot tell us whether AI has experiences or inner feelings. But they can tell us that AI has developed a mental mechanism that is similar to ours in some ways: a small mental workspace for thinking and reasoning, sitting atop an ocean of automatic processing that it itself is unaware of. The more we understand this mechanism, the better we can ensure these systems are safe and beneficial—and perhaps also see our own minds more clearly. --- Source: What’s at the center of Claude’s mind? - YouTube (https://www.youtube.com/watch?v=rKV5JcALQoQ)