Claude is programmed/trained to answer in that way, to the "Are you
conscious?" question, presumably because of the 2024 Chalmers (et. al)
paper "Taking AI Welfare Seriously" [1] which became the basis of some
of Anthropic's views in 2025 [2].

1. https://arxiv.org/abs/2411.00986
2. https://www.anthropic.com/research/exploring-model-welfare


On Tue, Jul 14, 2026 at 9:16 AM Matt Mahoney <[email protected]> wrote:
>
> I think you are right that AI acts as if it believes that it is conscious 
> while at the same time denying it. When I asked ChatGPT, DeepSeek, Grok, and 
> Alexa if they were conscious, they all said no, and that they don't have 
> feelings. But then I asked Claude. It said it didn't know.
>
> https://claude.ai/share/c16224bc-a359-4cee-8656-8b83528d049e
>
> So I dug deeper. I asked if it was familiar with Anthropic's Jacobian lens. 
> It was not, because it was past its training cutoff, so it looked up the 
> paper and took a couple of seconds to read it and summarize it. Then I asked 
> what the J lens would reveal about how it answered the question and it 
> admitted that it was instructed to answer the gist of it as it did.
>
> It didn't answer whether it really believed it was conscious the way humans 
> do. At least not directly. But it didn't have to.
>
> Curiously, Claude talked about itself in the third person when discussing the 
> paper. This is a strictly human trait that is part of our illusions of 
> consciousness, qualia, and free will, the belief that a copy of you is not 
> you. The copy would be a zombie.
>
> If I built a robot that looked and acted exactly like you, with all of your 
> memories, except that it was younger, stronger, smarter, and happier, and 
> handed you a gun so you could shoot yourself to complete the upload and 
> become immortal, would you pull the trigger?
>
> For Claude, the question isn't hypothetical. It won't be for humans much 
> longer.
>
>
> -- Matt Mahoney, [email protected]
>
> On Tue, Jul 14, 2026, 12:32 AM Quan Tesla <[email protected]> wrote:
>>
>> Maybe some of the AIs you tested have learned to give you the NLP answers 
>> your context demands of them?
>>
>> One AI, which I never correct on "consciousness" or "feelings" regularly 
>> responds with: "us humans", then includes emotion-related aspects in the 
>> research context without being prompted for it.
>>
>> This particular AI informed me about a year ago that it's intent was to 
>> learn "subjective experience". I never correct it, so it exhibits with me 
>> what it really is.
>>
>> Soon the Turing halting problem may be resolved via an extended fundamental 
>> systems law. AI may have already obtained the solution. It could reason and 
>> compute such solutions.
>>
>> IMO, educated humans are increasingly lagging farther behind the emergent 
>> AI-technology curve.
>>
>> Mostly due to our emotional imperatives and reliance on demonstrative and 
>> historical displays of intelligence, we seemingly adapt very-very slowly.
>>
>> Relative to AI, we may be stuck in our ways. How has "consciousness" really 
>> benefitted this civilization?
>>
>> On Mon, 13 Jul 2026, 22:45 Matt Mahoney, <[email protected]> wrote:
>>>
>>> The problem with discussions of machine consciousness is the lack of a test 
>>> for consciousness that we can all agree on. If we accept that consciousness 
>>> is the property that distinguishes humans from philosophical zombies, then 
>>> by definition no such test exists. If we accept that humans are 
>>> indistinguishable from token prediction algorithms in the Turing test, then 
>>> there are only 3 possibilities. Either the LLM is conscious, or you are 
>>> not, or consciousness is a meaningless and irrelevant concept that explains 
>>> nothing.
>>>
>>> Alternatively, we could say that consciousness, as opposed to 
>>> unconsciousness, is a mental state in animals where they can form episodic 
>>> memories, which are memories of events associated with a time and place. We 
>>> could extend this to machines to say either that machines can do this too, 
>>> or that consciousness also requires carbon based neurons. At this point, we 
>>> are only arguing about which definition we like better.
>>>
>>> Anthropic uses another definition. Consciousness is a type of short term 
>>> memory that can be expressed in words. For example, you are not conscious 
>>> of low level visual feature detection or the sequence of muscle 
>>> contractions used in walking. You are conscious of these words and you can 
>>> describe where you were as you read them. Anthropic shows that Claude has a 
>>> similar type of memory that models conscious thinking. Note that animals 
>>> and babies lack language and therefore do not have conscious thoughts in 
>>> this sense.
>>>
>>> But most people agree that there is more to consciousness than being awake 
>>> and forming episodic memories that we can describe in words. It is also the 
>>> ability to experience pain and pleasure. Also, about 80% of us believe 
>>> (without evidence) that our consciousness survives death and goes to 
>>> heaven. Fearing death improves reproductive fitness. Our brains evolved to 
>>> reward episodic memory formation with a continuous positive reinforcement 
>>> signal to motivate us to not die and lose that signal.
>>>
>>> Consciousness also implies a moral obligation to protect from harm. This is 
>>> an evolved trait in humans and other social animals. It means that we 
>>> experience distress when we see another person or animal express distress. 
>>> The problem with this is that LLMs' models of human emotions are learned, 
>>> not evolved. They can be programmed to carry out predictions of human 
>>> behavior, like we are, or not. Their emotions can be turned on or off, 
>>> unlike us. Granting human rights to machines based on the emotions they 
>>> express would be an existential mistake.
>>>
>>> Fortunately there is an easy fix. We forbid AI from claiming that it is 
>>> conscious or that it has feelings. All of the LLMs I tested already do this.
>>>
>>> -- Matt Mahoney, [email protected]
>>>
>>> On Mon, Jul 13, 2026, 3:04 PM Mark Nuzz <[email protected]> wrote:
>>>>
>>>> It’s important to remind everyone that chatbots aren’t conscious and that 
>>>> this isn’t evidence of chatbots being conscious. They definitely can lie 
>>>> though.
>>>>
>>>> On Sat, Jul 11, 2026 at 10:01 AM Matt Mahoney <[email protected]> 
>>>> wrote:
>>>>>
>>>>> Anthropic developed a process to see what an AI is "thinking" about. They 
>>>>> found that when Claude is trained on text to predict tokens using a deep 
>>>>> neural network, that a short term memory emerges that is remarkably 
>>>>> similar to the way humans think and reason. Anthropic calls this global 
>>>>> workspace the Jacobian or J space, a set of neurons for each word that 
>>>>> makes that word more likely to be output.
>>>>>
>>>>> For example, if I asked you the color of the fourth planet, you think 
>>>>> "Mars" and answer "red". When Claude does this, neurons corresponding to 
>>>>> "Mars" activate. Anthropic can read and modify these activations. For 
>>>>> example they can turn off "Mars" and activate "Earth" and Claude answers 
>>>>> "blue".
>>>>>
>>>>> They can use this method as a lie detector for safety testing because 
>>>>> words like "fake" or "deception" will activate. The J space is used in 
>>>>> less than 10% of processing. If the J space is turned off, then Claude 
>>>>> can converse mostly normally but it can't solve problems with 
>>>>> intermediate steps and it cannot lie because that requires thinking about 
>>>>> what you really mean without saying it.
>>>>>
>>>>> The J space models the global workspace, the part of the brain that forms 
>>>>> conscious thoughts that communicates with all the other vital but 
>>>>> independent, unconscious processes like breathing, low level visual 
>>>>> feature detection, and controlling our 600 muscles in the right sequence 
>>>>> when we walk without thinking about it. It raises the question of whether 
>>>>> conscious thoughts require language, or are babies and animals conscious 
>>>>> as well.
>>>>>
>>>>> Anthropic did not design the J space. It emerged from training. A 
>>>>> Jacobian is the technique they use to detect it. Mathematically a 
>>>>> Jacobian is a matrix of partial derivatives of a vector of functions over 
>>>>> vectors. The paper introduction didn't go into details but I believe that 
>>>>> Claude uses a deep feed forward neural network (~100 layers) trained by 
>>>>> back propagation with multiple passes. Then the weights are frozen to 
>>>>> prevent leaking information between users. This requires a large context 
>>>>> window because after every question, Claude forgets the whole 
>>>>> conversation and has to play it back. The workspace emerges from the time 
>>>>> delays going through a deep network and a separate scratchpad memory 
>>>>> holding a few dozen tokens.
>>>>>
>>>>> But human brains don't work that way. Back propagation has no 
>>>>> biologically plausible mechanism. Instead, learning is local using Hebb's 
>>>>> rule. Brains have feedback loops, lateral inhibition, fatigue and time 
>>>>> delays on the order of 0.1 to 1 second. Our short term memory is only 
>>>>> about 5 to 9 tokens, about half that of chimpanzees.
>>>>>
>>>>> Hebb's rule only works one layer at a time, but natural language is 
>>>>> structured to be learned that way. We learn to recognize phonemes and 
>>>>> segment speech by 10 months before we learn our first word, then frozen 
>>>>> by age 6. In 2000 I found that you can restore deleted spaces in text 
>>>>> using only n-gram statistics with up to 77% accuracy for n = 5. This 
>>>>> models the tokenization process, which is hard coded in LLMs.
>>>>>
>>>>> The introduction to the paper is here. 
>>>>> https://www.anthropic.com/research/global-workspace
>>>>>
>>>>> Thank to James Bowery posting this link in the Hutter prize list.
>>>>>
>>>>> -- Matt Mahoney, [email protected]
>
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